Leydet_GEOG6160_Lab08
David Leydet
2023-03-21
Neural Networks
Introduction
Note: In this lab, we’ll go over two neural network examples. These are simple one or two hidden layer networks, and the main purpose of the exercise is to demonstrate how to build the networks and what options are available to modify these. We’ll also walk through tuning these simple networks.
##Set Working Directory
setwd("~/Desktop/University of Utah PhD /Course Work/Spring 2023 Semester/GEOG6160 - Spatial Modeling/Labs/lab08/")
##Required Libraries
library(mlr3verse) #loads the entire mlr3 package family## Loading required package: mlr3library(dplyr) #data manipulation##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(GGally) ##ggplot extension for plotting correlation matrices## Loading required package: ggplot2## Registered S3 method overwritten by 'GGally':
## method from
## +.gg ggplot2library(ggplot2) ##data visualization
library(RColorBrewer) ##colorpalettesNeural Network Regression
Note: We’ll start with an example of using a neural network for a regression task. The data are taken from a Kaggle competition and are based on a set of 77 breakfast cereals. A description of the data is given in the appendix. The last field in the file (rating) is the outcome variable that we will build the network for.
## Read in the data
data = read.csv("../datafiles/cereals.csv")
## Look at the header
head(data)## name mfr type calories protein fat sodium fiber carbo
## 1 100% Bran N C 70 4 1 130 10.0 5.0
## 2 100% Natural Bran Q C 120 3 5 15 2.0 8.0
## 3 All-Bran K C 70 4 1 260 9.0 7.0
## 4 All-Bran with Extra Fiber K C 50 4 0 140 14.0 8.0
## 5 Almond Delight R C 110 2 2 200 1.0 14.0
## 6 Apple Cinnamon Cheerios G C 110 2 2 180 1.5 10.5
## sugars potass vitamins shelf weight cups rating
## 1 6 280 25 3 1 0.33 68.40
## 2 8 135 0 3 1 1.00 33.98
## 3 5 320 25 3 1 0.33 59.43
## 4 0 330 25 3 1 0.50 93.70
## 5 8 -1 25 3 1 0.75 34.38
## 6 10 70 25 1 1 0.75 29.51## Subset the numeric features for the modeling
## The outcome variable is "rating"
mydat = data %>%
select(rating, calories, protein, fat, sodium, fiber)
## Check
head(mydat)## rating calories protein fat sodium fiber
## 1 68.40 70 4 1 130 10.0
## 2 33.98 120 3 5 15 2.0
## 3 59.43 70 4 1 260 9.0
## 4 93.70 50 4 0 140 14.0
## 5 34.38 110 2 2 200 1.0
## 6 29.51 110 2 2 180 1.5## Correlation Plot
ggcorr(data = mydat,
label = TRUE,
nbreaks = 6,
palette ="RdBu")
## Histogram for cereal rating
ggplot(data = mydat, aes(x = rating)) +
geom_histogram(aes(y = after_stat(density)),
binwidth = 5,
fill = "dodgerblue3",
color = "black") +
geom_density(col = "red",
linetype = 1) +
theme_bw()
Neural Network in mlr3
Note: Regression neural networks are provided in mlr3 from the nnet package (regr.nnet).
As the network uses weighted sums of the input features, it’s important that none of these are on very different scales. The easiest way to avoid this is to scale all variables to approximately the same range. The scaling we use here is a min-max transformation or normalization (i.e. each variable is converted to a 0-1 range). This transformation is given by the following equation.
We do this in three steps:
- First calculate the maximum then minimum value for each variable using the apply() function.
- Then we use these to scale the data - effectively setting the smallest value of each variable to 0, the highest value to 1
- Lastly, we make a new dataset that combines these scaled values with the output (rating)
##MinMax Normalization
## Set a vector with all of the feature/variable names
feature_names = c("calories", "protein", "fat", "sodium", "fiber")
## Calculate and apply the maximum values
## Margin selects either rows (1) or columns (2)
maxs = apply(X = mydat[ , feature_names],
MARGIN = 2,
FUN = max)
## Calculate and apply the minimum values
mins = apply(mydat[ , feature_names],
MARGIN = 2,
FUN = min)
## Scale the data - setting the smallest value as 0 and the highest to 1
scaled_features = as.data.frame(scale(mydat[ , feature_names],
center = mins,
scale = maxs - mins))
## Combine the scaled data with the rating
scaled_data = data.frame(rating = mydat$rating,
scaled_features)
## Check
dim(scaled_data)## [1] 77 6head(scaled_data)## rating calories protein fat sodium fiber
## 1 68.40 0.1818182 0.6 0.2 0.406250 0.71428571
## 2 33.98 0.6363636 0.4 1.0 0.046875 0.14285714
## 3 59.43 0.1818182 0.6 0.2 0.812500 0.64285714
## 4 93.70 0.0000000 0.6 0.0 0.437500 1.00000000
## 5 34.38 0.5454545 0.2 0.4 0.625000 0.07142857
## 6 29.51 0.5454545 0.2 0.4 0.562500 0.10714286Now we’ll go through the usual steps of defining our task, performance metric and resampling strategy first.
Note that we use the scaled data to create the task, and that we create an outer resampler using k-fold cross-validation, to allow tuning later.
## Create the cereal task
## Reminder our target is the cereal rating
cereal_task = TaskRegr$new(id = "cereal",
backend = scaled_data,
target = "rating")## Use the RMSE as our performance measure
msr_rmse = msr("regr.rmse")## k-fold cross validation strategy
## 5 folds
rsmp_outer = rsmp("cv",
folds = 5)Before building the neural network, we’ll test a simple linear model to give us a baseline performance score, and to allow us to judge whether a neural network represents an improvement.
## Using a simple linear regression learner to test
lrn_lm = lrn("regr.lm")Initial cross-validation
## Initial run of our linear models via cross validation
cereal_lm = resample(task = cereal_task,
learner = lrn_lm,
resampling = rsmp_outer,
store_models = TRUE)## INFO [10:30:53.027] [mlr3] Applying learner 'regr.lm' on task 'cereal' (iter 1/5)
## INFO [10:30:53.052] [mlr3] Applying learner 'regr.lm' on task 'cereal' (iter 2/5)
## INFO [10:30:53.061] [mlr3] Applying learner 'regr.lm' on task 'cereal' (iter 3/5)
## INFO [10:30:53.067] [mlr3] Applying learner 'regr.lm' on task 'cereal' (iter 4/5)
## INFO [10:30:53.073] [mlr3] Applying learner 'regr.lm' on task 'cereal' (iter 5/5)## Initial RMSE score for our linear model run
cereal_lm$aggregate(msr_rmse)## regr.rmse
## 6.208639Note: Now we’ll set up a neural network learner. Note that we can specify here the number of nodes in the hidden layer. We’ll start with 3 nodes to give us a simple model. Note that we specify this directly in the setup of the learner.
## Setup the neural network learner
## size = 3 is the number of nodes in the hidden layer (the next layer after the input/feature layer)
lrn_nn = lrn("regr.nnet",
size = 3)## Initial Neural Network Run
cereal_nn = resample(task = cereal_task,
learner = lrn_nn,
resampling = rsmp_outer,
store_models = TRUE)## INFO [10:30:53.118] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/5)
## # weights: 22
## initial value 109691.129282
## final value 8733.951056
## converged
## INFO [10:30:53.125] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/5)
## # weights: 22
## initial value 130268.979153
## final value 13434.235028
## converged
## INFO [10:30:53.136] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/5)
## # weights: 22
## initial value 130709.380986
## final value 12603.749236
## converged
## INFO [10:30:53.143] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 4/5)
## # weights: 22
## initial value 126064.441278
## iter 10 value 2266.358110
## iter 20 value 1361.812223
## iter 30 value 1124.954492
## iter 40 value 1042.095052
## iter 50 value 963.015243
## iter 60 value 951.414054
## iter 70 value 895.506921
## iter 80 value 817.741084
## iter 90 value 815.239610
## iter 100 value 815.153424
## final value 815.153424
## stopped after 100 iterations
## INFO [10:30:53.151] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 5/5)
## # weights: 22
## initial value 123704.942224
## iter 10 value 5900.534627
## iter 20 value 2879.868461
## iter 30 value 2523.651660
## iter 40 value 2168.818620
## iter 50 value 2109.775465
## iter 60 value 2103.964153
## iter 70 value 2101.633341
## iter 80 value 2100.599119
## iter 90 value 2100.381508
## final value 2100.354694
## converged## RMSE
cereal_nn$aggregate(msr_rmse)## regr.rmse
## 11.26956Our RMSE for this step is 11.2695644. Let’s see if increasing the number of hidden nodes to 5 and the number of learning iterations will improve this:
## Increase the number of hidden nodes to 5
lrn_nn = lrn("regr.nnet",
size = 5)
## Re-run the models
cereal_nn = resample(task = cereal_task,
learner = lrn_nn,
resampling = rsmp_outer,
store_models = TRUE)## INFO [10:30:53.195] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/5)
## # weights: 36
## initial value 118488.719848
## iter 10 value 3553.038128
## iter 20 value 2423.636520
## iter 30 value 2245.340078
## iter 40 value 2115.456412
## iter 50 value 1868.084185
## iter 60 value 1748.292920
## iter 70 value 1654.556202
## iter 80 value 1645.679434
## iter 90 value 1635.283813
## iter 100 value 1631.884641
## final value 1631.884641
## stopped after 100 iterations
## INFO [10:30:53.203] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/5)
## # weights: 36
## initial value 114234.177183
## iter 10 value 6984.670107
## iter 20 value 4081.937397
## iter 30 value 3061.851765
## iter 40 value 2078.764949
## iter 50 value 1960.031518
## iter 60 value 1933.389901
## iter 70 value 1927.931163
## iter 80 value 1926.776365
## iter 90 value 1926.666499
## iter 100 value 1926.591191
## final value 1926.591191
## stopped after 100 iterations
## INFO [10:30:53.210] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/5)
## # weights: 36
## initial value 125497.170753
## iter 10 value 5089.068770
## iter 20 value 2465.534543
## iter 30 value 1680.768387
## iter 40 value 1046.823709
## iter 50 value 973.410794
## iter 60 value 917.892725
## iter 70 value 871.824609
## iter 80 value 856.561265
## iter 90 value 853.831830
## iter 100 value 845.438930
## final value 845.438930
## stopped after 100 iterations
## INFO [10:30:53.218] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 4/5)
## # weights: 36
## initial value 136493.478662
## iter 10 value 8809.151378
## iter 20 value 4128.083586
## iter 30 value 3953.836937
## iter 40 value 3635.719031
## iter 50 value 2558.283676
## iter 60 value 2103.710445
## iter 70 value 1985.672070
## iter 80 value 1968.691793
## iter 90 value 1964.904869
## iter 100 value 1964.597681
## final value 1964.597681
## stopped after 100 iterations
## INFO [10:30:53.225] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 5/5)
## # weights: 36
## initial value 125959.617974
## iter 10 value 2904.348040
## iter 20 value 1084.096688
## iter 30 value 888.360080
## iter 40 value 866.928380
## iter 50 value 865.157326
## iter 60 value 863.646561
## iter 70 value 833.566823
## iter 80 value 797.673694
## iter 90 value 780.583145
## iter 100 value 768.747924
## final value 768.747924
## stopped after 100 iterations## RMSE
cereal_nn$aggregate(msr_rmse)## regr.rmse
## 10.98426Note: There is no improvement over our previous models.
Tuning Neural Networks
Let’s now tune the model to see if we can choose the optimal value for this parameter. First, let’s check the available parameters for regr.nnet:
lrn_nn$param_set## <ParamSet>
## id class lower upper nlevels default value
## 1: Hess ParamLgl NA NA 2 FALSE
## 2: MaxNWts ParamInt 1 Inf Inf 1000
## 3: Wts ParamUty NA NA Inf <NoDefault[3]>
## 4: abstol ParamDbl -Inf Inf Inf 1e-04
## 5: censored ParamLgl NA NA 2 FALSE
## 6: contrasts ParamUty NA NA Inf
## 7: decay ParamDbl -Inf Inf Inf 0
## 8: mask ParamUty NA NA Inf <NoDefault[3]>
## 9: maxit ParamInt 1 Inf Inf 100
## 10: na.action ParamUty NA NA Inf <NoDefault[3]>
## 11: rang ParamDbl -Inf Inf Inf 0.7
## 12: reltol ParamDbl -Inf Inf Inf 1e-08
## 13: size ParamInt 0 Inf Inf 3 5
## 14: skip ParamLgl NA NA 2 FALSE
## 15: subset ParamUty NA NA Inf <NoDefault[3]>
## 16: trace ParamLgl NA NA 2 TRUENote: In addition to the number of neurons (size), we’ll also tune the number of iterations (maxit) and the learning decay rate (decay). Next, load the paradox library, and define the parameter space that we will explore:
## Load paradox library for working with parameter spaces and algorithms
library(paradox)## Tuning the following parameters
## size - number of neurons
## maxit - number of iterations
## decay - learning decay rate
tune_ps = ParamSet$new(list(
ParamInt$new("size", lower = 1, upper = 10),
ParamInt$new("maxit", lower = 50, upper = 500),
ParamDbl$new("decay", lower = 0, upper = 1e-4)
))
## Check
tune_ps## <ParamSet>
## id class lower upper nlevels default value
## 1: size ParamInt 1 1e+01 10 <NoDefault[3]>
## 2: maxit ParamInt 50 5e+02 451 <NoDefault[3]>
## 3: decay ParamDbl 0 1e-04 Inf <NoDefault[3]>Note: We will use a random search strategy to select values of the parameters to test
## Tuner setup
tuner = tnr("random_search")We’ll define a stopping condition. We’ll run this for 20 iterations here (20 parameter values). This is a relatively low number to explore a three dimensional parameter space, in practice you would want to increase this (or use a different search strategy).
## Set this for 20 iterations
evals = trm("evals",
n_evals = 20)Lastly, we’ll set up an inner cross-validation strategy for the tuning process. We’ll use the same k-fold strategy as above, but with k=3:
Please see the image below for the difference between outer and inner resampling:
[]resampling.png
## Cross Validation
## 3 folds
rsmp_inner = rsmp("cv",
folds = 3)Build the autotuner!
## AutoTuner
at_nn = AutoTuner$new(tuner = tuner,
learner = lrn_nn,
resampling = rsmp_inner,
measure = msr_rmse,
search_space = tune_ps,
terminator = evals)And finally(!), run the resample function with this. This will run for a little while as it is building 3 * 5 * 20 models.
## Reproducability?
set.seed(1)
## Resample Re-run
cereal_nn = resample(task = cereal_task,
learner = at_nn,
resampling = rsmp_outer,
store_models = TRUE)## INFO [10:30:53.302] [mlr3] Applying learner 'regr.nnet.tuned' on task 'cereal' (iter 1/5)
## INFO [10:30:53.326] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorEvals> [n_evals=20, k=0]'
## INFO [10:30:53.334] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.342] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.345] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 81285.592193
## iter 10 value 1772.589334
## iter 20 value 838.465321
## iter 30 value 571.671898
## iter 40 value 451.041076
## iter 50 value 431.229282
## iter 60 value 397.996825
## iter 70 value 394.550448
## iter 80 value 392.851724
## iter 90 value 392.113585
## iter 100 value 389.595091
## iter 110 value 262.769002
## iter 120 value 159.013351
## iter 130 value 128.360777
## iter 140 value 104.850728
## iter 150 value 100.014668
## iter 160 value 96.578528
## iter 170 value 96.060748
## iter 180 value 85.631589
## iter 190 value 69.964037
## iter 200 value 68.353368
## iter 210 value 68.204235
## iter 220 value 68.019877
## iter 230 value 67.994372
## iter 240 value 67.984598
## iter 250 value 67.903133
## iter 260 value 67.246528
## iter 270 value 60.480830
## iter 280 value 54.671571
## iter 290 value 51.574170
## iter 300 value 43.905395
## final value 42.594821
## stopped after 304 iterations
## INFO [10:30:53.353] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 91669.483096
## iter 10 value 2277.811685
## iter 20 value 1703.369824
## iter 30 value 1130.550577
## iter 40 value 1055.247472
## iter 50 value 1054.298604
## iter 60 value 1048.209426
## iter 70 value 1012.750947
## iter 80 value 690.538226
## iter 90 value 607.646266
## iter 100 value 596.985029
## iter 110 value 573.750128
## iter 120 value 573.261708
## iter 130 value 573.244968
## iter 140 value 573.149444
## iter 150 value 573.125406
## iter 160 value 573.120564
## iter 170 value 571.654217
## iter 180 value 552.742174
## iter 190 value 490.377882
## iter 200 value 457.992080
## iter 210 value 347.150919
## iter 220 value 282.228730
## iter 230 value 257.510276
## iter 240 value 253.458826
## iter 250 value 253.385431
## iter 260 value 253.374515
## iter 270 value 253.353971
## iter 280 value 253.227849
## iter 290 value 253.126681
## iter 300 value 253.099225
## final value 253.072465
## stopped after 304 iterations
## INFO [10:30:53.362] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 73061.311497
## iter 10 value 1711.418334
## iter 20 value 1345.075050
## iter 30 value 1248.769867
## iter 40 value 1233.390147
## iter 50 value 1223.946736
## iter 60 value 1176.764471
## iter 70 value 1000.765332
## iter 80 value 733.793238
## iter 90 value 649.933085
## iter 100 value 643.183050
## iter 110 value 634.484536
## iter 120 value 634.358663
## iter 130 value 634.346412
## iter 140 value 634.041822
## iter 150 value 632.945214
## iter 160 value 631.419878
## iter 170 value 600.541643
## iter 180 value 560.306184
## iter 190 value 544.189218
## iter 200 value 538.407897
## iter 210 value 494.186551
## iter 220 value 295.746024
## iter 230 value 222.490375
## iter 240 value 207.376118
## iter 250 value 197.781582
## iter 260 value 183.274444
## iter 270 value 181.742159
## iter 280 value 179.978550
## iter 290 value 179.349752
## iter 300 value 178.769334
## final value 178.597784
## stopped after 304 iterations
## INFO [10:30:53.370] [mlr3] Finished benchmark
## INFO [10:30:53.381] [bbotk] Result of batch 1:
## INFO [10:30:53.382] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.382] [bbotk] 4 304 5.779849e-05 16.7903 0 0 0.011
## INFO [10:30:53.382] [bbotk] uhash
## INFO [10:30:53.382] [bbotk] e084670f-f698-4758-a3b3-5dd91e8d8518
## INFO [10:30:53.384] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.395] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.398] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 43
## initial value 86197.330319
## iter 10 value 4106.025060
## iter 20 value 2654.001316
## iter 30 value 2380.263942
## iter 40 value 1739.458439
## iter 50 value 1274.144283
## iter 60 value 1207.234058
## iter 70 value 1198.806041
## iter 80 value 1197.300747
## iter 90 value 1196.490870
## iter 100 value 1194.670741
## iter 110 value 1161.518806
## iter 120 value 1015.371271
## iter 130 value 545.781659
## iter 140 value 501.423481
## iter 150 value 477.197489
## iter 160 value 463.965450
## iter 170 value 408.165108
## iter 180 value 399.984957
## iter 190 value 396.120357
## iter 200 value 391.780415
## iter 210 value 376.253667
## iter 220 value 371.088090
## iter 230 value 366.218411
## iter 240 value 357.893506
## iter 250 value 345.107166
## iter 260 value 338.337608
## iter 270 value 336.855580
## iter 280 value 336.418563
## iter 290 value 336.364983
## iter 300 value 336.276588
## iter 310 value 336.222377
## iter 320 value 335.929128
## iter 330 value 335.110089
## iter 340 value 334.671460
## iter 350 value 334.248814
## iter 360 value 333.164693
## iter 370 value 332.248413
## iter 380 value 331.739002
## iter 390 value 331.176408
## iter 400 value 331.079974
## iter 410 value 330.175527
## iter 420 value 328.847216
## iter 430 value 326.538279
## iter 440 value 325.331868
## iter 450 value 325.252851
## iter 460 value 325.237896
## final value 325.150928
## stopped after 468 iterations
## INFO [10:30:53.409] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 43
## initial value 98145.076495
## iter 10 value 5035.468530
## iter 20 value 874.016052
## iter 30 value 389.150240
## iter 40 value 317.309482
## iter 50 value 275.118821
## iter 60 value 249.227835
## iter 70 value 238.642991
## iter 80 value 198.221448
## iter 90 value 177.026075
## iter 100 value 156.794054
## iter 110 value 146.883354
## iter 120 value 140.753541
## iter 130 value 137.113728
## iter 140 value 135.710541
## iter 150 value 134.768150
## iter 160 value 133.753924
## iter 170 value 86.651458
## iter 180 value 69.758318
## iter 190 value 63.054599
## iter 200 value 59.868611
## iter 210 value 58.428259
## iter 220 value 56.990806
## iter 230 value 56.538092
## iter 240 value 56.139441
## iter 250 value 56.001030
## iter 260 value 54.254192
## iter 270 value 53.865423
## iter 280 value 53.076067
## iter 290 value 45.491469
## iter 300 value 41.798062
## iter 310 value 40.316163
## iter 320 value 39.173742
## iter 330 value 39.040208
## iter 340 value 38.940575
## iter 350 value 38.905533
## iter 360 value 38.900306
## iter 370 value 38.891853
## iter 380 value 38.849875
## iter 390 value 38.819731
## iter 400 value 38.770772
## iter 410 value 38.721003
## iter 420 value 38.675202
## iter 430 value 38.406373
## iter 440 value 38.185233
## iter 450 value 38.172842
## iter 460 value 38.131817
## final value 38.104474
## stopped after 468 iterations
## INFO [10:30:53.421] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 43
## initial value 74664.131278
## iter 10 value 1732.282232
## iter 20 value 676.437661
## iter 30 value 440.952878
## iter 40 value 385.998222
## iter 50 value 364.830531
## iter 60 value 353.993359
## iter 70 value 345.860258
## iter 80 value 339.565967
## iter 90 value 329.767449
## iter 100 value 320.498406
## iter 110 value 298.683387
## iter 120 value 291.327727
## iter 130 value 270.430499
## iter 140 value 227.820348
## iter 150 value 178.523376
## iter 160 value 141.531739
## iter 170 value 128.856842
## iter 180 value 126.071939
## iter 190 value 125.270138
## iter 200 value 122.407595
## iter 210 value 118.235217
## iter 220 value 107.169472
## iter 230 value 98.153415
## iter 240 value 87.663012
## iter 250 value 76.106455
## iter 260 value 70.125370
## iter 270 value 69.769576
## iter 280 value 67.753426
## iter 290 value 57.142835
## iter 300 value 54.777564
## iter 310 value 51.647002
## iter 320 value 40.655951
## iter 330 value 40.495326
## iter 340 value 40.389942
## iter 350 value 40.208909
## iter 360 value 40.202754
## iter 370 value 40.193911
## iter 380 value 40.086231
## iter 390 value 39.776330
## iter 400 value 39.166397
## iter 410 value 36.158278
## iter 420 value 34.894125
## iter 430 value 33.298226
## iter 440 value 32.131163
## iter 450 value 31.273628
## iter 460 value 30.417389
## final value 30.027328
## stopped after 468 iterations
## INFO [10:30:53.431] [mlr3] Finished benchmark
## INFO [10:30:53.442] [bbotk] Result of batch 2:
## INFO [10:30:53.443] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.443] [bbotk] 6 468 1.10067e-05 9.428385 0 0 0.021
## INFO [10:30:53.443] [bbotk] uhash
## INFO [10:30:53.443] [bbotk] d913d25c-d683-4e93-a502-c8326360a5ff
## INFO [10:30:53.445] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.451] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.454] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 22
## initial value 83147.921417
## iter 10 value 3084.852175
## iter 20 value 2768.597434
## iter 30 value 2011.413585
## iter 40 value 844.404279
## iter 50 value 732.460336
## iter 60 value 701.907342
## iter 70 value 684.508501
## iter 80 value 426.032755
## iter 90 value 327.298203
## iter 100 value 283.743482
## iter 110 value 277.112382
## iter 120 value 276.210080
## iter 130 value 275.038836
## iter 140 value 273.918550
## iter 150 value 272.938842
## iter 160 value 272.727184
## final value 272.726685
## converged
## INFO [10:30:53.461] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 22
## initial value 92247.920097
## iter 10 value 6131.130217
## iter 20 value 1230.359474
## iter 30 value 897.377351
## iter 40 value 762.891249
## iter 50 value 745.316322
## iter 60 value 725.038367
## iter 70 value 645.326137
## iter 80 value 643.985977
## iter 90 value 643.625145
## final value 643.623618
## converged
## INFO [10:30:53.468] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 22
## initial value 71801.983886
## iter 10 value 4700.083011
## iter 20 value 2404.262008
## iter 30 value 1357.784625
## iter 40 value 1263.986549
## iter 50 value 1132.881627
## iter 60 value 898.819666
## iter 70 value 676.708779
## iter 80 value 650.237116
## iter 90 value 650.000503
## iter 100 value 647.454430
## iter 110 value 625.763486
## iter 120 value 438.237795
## iter 130 value 379.919324
## iter 140 value 343.321670
## iter 150 value 336.710647
## iter 160 value 330.865777
## final value 325.637231
## stopped after 168 iterations
## INFO [10:30:53.475] [mlr3] Finished benchmark
## INFO [10:30:53.486] [bbotk] Result of batch 3:
## INFO [10:30:53.486] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.486] [bbotk] 3 168 4.543677e-05 7.957372 0 0 0.008
## INFO [10:30:53.486] [bbotk] uhash
## INFO [10:30:53.486] [bbotk] 59c9ff32-1ce2-4f9f-88a7-8995ace5af17
## INFO [10:30:53.488] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.495] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.497] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 82722.701572
## iter 10 value 10227.724882
## iter 20 value 2387.162455
## iter 30 value 1415.865247
## iter 40 value 1215.058009
## iter 50 value 1195.157331
## iter 60 value 1190.131709
## iter 70 value 1076.325051
## iter 80 value 567.377964
## iter 90 value 554.276020
## iter 100 value 508.493877
## iter 110 value 502.322311
## iter 120 value 501.625830
## iter 130 value 496.979577
## iter 140 value 489.378832
## iter 150 value 487.177005
## iter 160 value 486.731608
## iter 170 value 486.680080
## iter 180 value 486.555838
## iter 190 value 485.404606
## iter 200 value 479.279964
## iter 210 value 335.268467
## iter 220 value 314.655258
## iter 230 value 313.048145
## iter 240 value 312.111076
## iter 250 value 308.358713
## iter 260 value 300.402960
## iter 270 value 265.772823
## iter 280 value 252.735153
## iter 290 value 242.243034
## iter 300 value 212.861688
## iter 310 value 159.064233
## iter 320 value 145.338921
## iter 330 value 137.499077
## iter 340 value 127.096027
## iter 350 value 117.948273
## iter 360 value 116.629304
## iter 370 value 115.410530
## final value 114.219164
## stopped after 378 iterations
## INFO [10:30:53.508] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 91116.578861
## iter 10 value 6025.417098
## iter 20 value 3421.449875
## iter 30 value 2024.997338
## iter 40 value 1253.317117
## iter 50 value 1058.014501
## iter 60 value 1054.880728
## iter 70 value 1054.361044
## iter 80 value 1053.508658
## iter 90 value 1040.487237
## iter 100 value 904.634926
## iter 110 value 901.171948
## iter 120 value 901.004027
## iter 130 value 899.412742
## iter 140 value 829.061082
## iter 150 value 617.384019
## iter 160 value 538.262594
## iter 170 value 465.051750
## iter 180 value 429.858251
## iter 190 value 403.339973
## iter 200 value 362.290201
## iter 210 value 353.650235
## iter 220 value 346.818967
## iter 230 value 341.588111
## iter 240 value 335.253364
## iter 250 value 332.112576
## iter 260 value 316.151087
## iter 270 value 264.940632
## iter 280 value 232.305546
## iter 290 value 227.804662
## iter 300 value 223.882795
## iter 310 value 219.825672
## iter 320 value 217.804694
## iter 330 value 216.220047
## iter 340 value 209.481089
## iter 350 value 193.734485
## iter 360 value 160.303216
## iter 370 value 146.135115
## final value 131.428802
## stopped after 378 iterations
## INFO [10:30:53.519] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 72135.336828
## iter 10 value 1649.756517
## iter 20 value 981.864348
## iter 30 value 662.632347
## iter 40 value 468.618101
## iter 50 value 430.604096
## iter 60 value 416.174147
## iter 70 value 411.799209
## iter 80 value 394.544919
## iter 90 value 386.319241
## iter 100 value 386.146989
## iter 110 value 386.055673
## iter 120 value 385.772835
## iter 130 value 380.518725
## iter 140 value 376.781915
## iter 150 value 367.363469
## iter 160 value 347.951656
## iter 170 value 285.529108
## iter 180 value 280.308324
## iter 190 value 279.414114
## iter 200 value 278.931632
## iter 210 value 278.107766
## iter 220 value 277.814080
## iter 230 value 275.524490
## iter 240 value 274.863475
## iter 250 value 274.757214
## iter 260 value 274.720067
## iter 270 value 274.688220
## iter 280 value 274.616064
## iter 290 value 274.357260
## iter 300 value 273.681393
## iter 310 value 272.045825
## iter 320 value 271.337108
## iter 330 value 261.123057
## iter 340 value 252.482351
## iter 350 value 243.828047
## iter 360 value 240.968710
## iter 370 value 239.868980
## final value 238.094801
## stopped after 378 iterations
## INFO [10:30:53.529] [mlr3] Finished benchmark
## INFO [10:30:53.544] [bbotk] Result of batch 4:
## INFO [10:30:53.544] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.544] [bbotk] 7 378 4.424152e-05 13.751 0 0 0.019
## INFO [10:30:53.544] [bbotk] uhash
## INFO [10:30:53.544] [bbotk] c4107be0-2b01-436f-97c7-a52836b87bc8
## INFO [10:30:53.546] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.553] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.555] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 71
## initial value 79442.370655
## iter 10 value 1001.327302
## iter 20 value 349.922128
## iter 30 value 213.375081
## iter 40 value 107.051244
## iter 50 value 90.662812
## iter 60 value 81.158660
## iter 70 value 65.355342
## iter 80 value 49.770440
## iter 90 value 34.492765
## iter 100 value 32.638289
## iter 110 value 31.690064
## iter 120 value 31.226720
## iter 130 value 30.874901
## iter 140 value 30.551430
## iter 150 value 30.046182
## iter 160 value 29.113240
## iter 170 value 28.426126
## iter 180 value 27.842485
## iter 190 value 27.402920
## iter 200 value 26.964425
## iter 210 value 26.789491
## iter 220 value 26.721821
## iter 230 value 26.552321
## iter 240 value 26.470213
## iter 250 value 26.305805
## final value 26.224998
## stopped after 252 iterations
## INFO [10:30:53.566] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 71
## initial value 94196.566579
## iter 10 value 9390.770562
## iter 20 value 2591.917393
## iter 30 value 2206.227500
## iter 40 value 1644.086103
## iter 50 value 1087.744168
## iter 60 value 1057.821418
## iter 70 value 1056.374223
## iter 80 value 1054.939786
## iter 90 value 1048.208950
## iter 100 value 834.626405
## iter 110 value 610.879044
## iter 120 value 590.086722
## iter 130 value 575.798407
## iter 140 value 573.782840
## iter 150 value 573.705020
## iter 160 value 573.684828
## iter 170 value 573.454076
## iter 180 value 570.969975
## iter 190 value 485.336591
## iter 200 value 298.259748
## iter 210 value 261.116274
## iter 220 value 257.859919
## iter 230 value 257.116673
## iter 240 value 256.289364
## iter 250 value 249.093434
## final value 248.145272
## stopped after 252 iterations
## INFO [10:30:53.577] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 71
## initial value 70839.832362
## iter 10 value 990.456207
## iter 20 value 505.658899
## iter 30 value 321.144117
## iter 40 value 244.008905
## iter 50 value 179.282632
## iter 60 value 97.935214
## iter 70 value 70.700169
## iter 80 value 49.403724
## iter 90 value 30.625218
## iter 100 value 24.667967
## iter 110 value 17.177037
## iter 120 value 7.467747
## iter 130 value 5.019371
## iter 140 value 4.130203
## iter 150 value 4.005431
## iter 160 value 3.969153
## iter 170 value 3.882741
## iter 180 value 3.734694
## iter 190 value 3.314338
## iter 200 value 3.005458
## iter 210 value 2.867537
## iter 220 value 2.655056
## iter 230 value 2.476982
## iter 240 value 2.411260
## iter 250 value 2.287482
## final value 2.267439
## stopped after 252 iterations
## INFO [10:30:53.588] [mlr3] Finished benchmark
## INFO [10:30:53.599] [bbotk] Result of batch 5:
## INFO [10:30:53.600] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.600] [bbotk] 10 252 9.609525e-05 11.31472 0 0 0.018
## INFO [10:30:53.600] [bbotk] uhash
## INFO [10:30:53.600] [bbotk] a32ea275-f4c1-4371-bccc-f98a15c30276
## INFO [10:30:53.601] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.608] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.610] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 43
## initial value 81090.528703
## iter 10 value 5048.511498
## iter 20 value 2627.185699
## iter 30 value 2604.446946
## iter 40 value 1888.500242
## iter 50 value 1267.824571
## iter 60 value 1200.293918
## iter 70 value 1189.224698
## iter 80 value 1187.636111
## iter 90 value 1186.916452
## iter 100 value 1130.107849
## iter 110 value 467.665377
## iter 120 value 370.906749
## iter 130 value 362.898197
## iter 140 value 358.985665
## iter 150 value 319.964880
## iter 160 value 223.266506
## iter 170 value 216.109766
## iter 180 value 196.157052
## iter 190 value 192.678683
## iter 200 value 185.997463
## iter 210 value 183.303588
## iter 220 value 183.024821
## iter 230 value 182.475632
## iter 240 value 176.387080
## iter 250 value 170.125071
## iter 260 value 169.363465
## iter 270 value 167.825601
## iter 280 value 157.603860
## iter 290 value 136.528436
## iter 300 value 102.472494
## iter 310 value 92.619013
## iter 320 value 72.803117
## iter 330 value 58.339557
## iter 340 value 51.528382
## iter 350 value 49.837027
## iter 360 value 48.780991
## iter 370 value 47.834613
## iter 380 value 47.352203
## iter 390 value 46.010803
## iter 400 value 45.223975
## iter 410 value 44.333897
## iter 420 value 43.560470
## iter 430 value 43.368043
## iter 440 value 43.288911
## final value 42.992351
## stopped after 445 iterations
## INFO [10:30:53.622] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 43
## initial value 95060.166345
## iter 10 value 2635.149949
## iter 20 value 2168.434208
## iter 30 value 1719.745589
## iter 40 value 1105.816949
## iter 50 value 1055.882490
## iter 60 value 1055.666523
## iter 70 value 1054.799465
## iter 80 value 1046.500797
## iter 90 value 674.001695
## iter 100 value 608.037228
## iter 110 value 582.028163
## iter 120 value 573.741802
## iter 130 value 573.612491
## iter 140 value 573.539706
## iter 150 value 572.565518
## iter 160 value 568.209084
## iter 170 value 512.116374
## iter 180 value 366.629711
## iter 190 value 296.900535
## iter 200 value 260.302525
## iter 210 value 154.590295
## iter 220 value 76.689890
## iter 230 value 64.529332
## iter 240 value 56.949615
## iter 250 value 56.306235
## iter 260 value 53.100085
## iter 270 value 48.844308
## iter 280 value 43.957502
## iter 290 value 41.611837
## iter 300 value 38.279016
## iter 310 value 35.858760
## iter 320 value 30.957684
## iter 330 value 30.533558
## iter 340 value 30.503691
## iter 350 value 30.232572
## iter 360 value 29.955606
## iter 370 value 29.730245
## iter 380 value 29.141131
## iter 390 value 28.289370
## iter 400 value 26.983520
## iter 410 value 25.119834
## iter 420 value 24.043211
## iter 430 value 23.503757
## iter 440 value 22.132216
## final value 21.264995
## stopped after 445 iterations
## INFO [10:30:53.634] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 43
## initial value 75236.091877
## iter 10 value 3210.767873
## iter 20 value 1134.278210
## iter 30 value 667.816808
## iter 40 value 467.459439
## iter 50 value 402.380981
## iter 60 value 392.236568
## iter 70 value 386.372576
## iter 80 value 361.688885
## iter 90 value 334.008396
## iter 100 value 321.303034
## iter 110 value 302.083421
## iter 120 value 225.087334
## iter 130 value 200.709437
## iter 140 value 184.777657
## iter 150 value 177.300356
## iter 160 value 175.757342
## iter 170 value 172.537231
## iter 180 value 171.678210
## iter 190 value 171.388421
## iter 200 value 170.248140
## iter 210 value 161.826556
## iter 220 value 160.073320
## iter 230 value 159.293435
## iter 240 value 157.663967
## iter 250 value 155.638422
## iter 260 value 155.150618
## iter 270 value 154.436658
## iter 280 value 153.857036
## iter 290 value 144.630382
## iter 300 value 136.287385
## iter 310 value 130.644135
## iter 320 value 128.636995
## iter 330 value 124.844855
## iter 340 value 120.944534
## iter 350 value 118.637639
## iter 360 value 118.193843
## iter 370 value 117.180514
## iter 380 value 114.444758
## iter 390 value 110.392031
## iter 400 value 107.484297
## iter 410 value 104.720781
## iter 420 value 102.412767
## iter 430 value 101.021141
## iter 440 value 98.508121
## final value 98.210877
## stopped after 445 iterations
## INFO [10:30:53.644] [mlr3] Finished benchmark
## INFO [10:30:53.655] [bbotk] Result of batch 6:
## INFO [10:30:53.656] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.656] [bbotk] 6 445 9.973919e-05 13.12515 0 0 0.021
## INFO [10:30:53.656] [bbotk] uhash
## INFO [10:30:53.656] [bbotk] 344a6ab6-95ca-48f3-ab23-1d08648fb1f1
## INFO [10:30:53.657] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.664] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.666] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 82756.480961
## iter 10 value 853.779156
## iter 20 value 251.444297
## iter 30 value 126.156621
## iter 40 value 97.631947
## iter 50 value 61.717581
## iter 60 value 50.604929
## iter 70 value 35.413754
## iter 80 value 31.205785
## iter 90 value 30.136694
## iter 100 value 29.494060
## iter 110 value 28.955692
## iter 120 value 28.572088
## iter 130 value 28.251116
## iter 140 value 27.967493
## iter 150 value 27.842235
## iter 160 value 27.202565
## iter 170 value 25.703954
## iter 180 value 23.419348
## iter 190 value 22.289446
## final value 21.694078
## stopped after 199 iterations
## INFO [10:30:53.679] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 99766.883531
## iter 10 value 1216.348503
## iter 20 value 720.265605
## iter 30 value 440.626877
## iter 40 value 360.007788
## iter 50 value 249.184302
## iter 60 value 200.866802
## iter 70 value 167.045874
## iter 80 value 153.513849
## iter 90 value 150.468964
## iter 100 value 145.425357
## iter 110 value 137.667714
## iter 120 value 130.680681
## iter 130 value 98.611929
## iter 140 value 87.427062
## iter 150 value 86.182057
## iter 160 value 85.578835
## iter 170 value 78.676887
## iter 180 value 75.139341
## iter 190 value 71.048005
## final value 69.827126
## stopped after 199 iterations
## INFO [10:30:53.688] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 74708.990177
## iter 10 value 1769.195221
## iter 20 value 1028.783713
## iter 30 value 783.741943
## iter 40 value 521.836730
## iter 50 value 439.318855
## iter 60 value 399.551813
## iter 70 value 376.485167
## iter 80 value 290.301005
## iter 90 value 234.194956
## iter 100 value 220.268844
## iter 110 value 211.084198
## iter 120 value 207.813818
## iter 130 value 205.087589
## iter 140 value 203.762626
## iter 150 value 202.353018
## iter 160 value 201.545180
## iter 170 value 201.205869
## iter 180 value 199.691054
## iter 190 value 199.071549
## final value 198.619346
## stopped after 199 iterations
## INFO [10:30:53.696] [mlr3] Finished benchmark
## INFO [10:30:53.707] [bbotk] Result of batch 7:
## INFO [10:30:53.708] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.708] [bbotk] 7 199 8.622045e-05 10.86371 0 0 0.018
## INFO [10:30:53.708] [bbotk] uhash
## INFO [10:30:53.708] [bbotk] 40fa12d1-3a3b-458f-9470-3ba3f6ec96b9
## INFO [10:30:53.709] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.716] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.719] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 36
## initial value 81488.644759
## iter 10 value 3733.698364
## iter 20 value 1778.441696
## iter 30 value 1301.525676
## iter 40 value 1208.653644
## iter 50 value 1192.986955
## iter 60 value 1189.864641
## iter 70 value 1189.746032
## iter 80 value 1178.379585
## iter 90 value 1169.317957
## iter 100 value 845.118655
## iter 110 value 538.158314
## iter 120 value 482.061113
## iter 130 value 451.682855
## iter 140 value 428.071035
## iter 150 value 410.303033
## iter 160 value 403.298147
## iter 170 value 402.455747
## iter 180 value 401.467394
## iter 190 value 399.827229
## iter 200 value 395.582710
## iter 210 value 393.792939
## iter 220 value 392.950359
## iter 230 value 390.450996
## iter 240 value 389.519110
## iter 250 value 388.824323
## final value 388.127546
## stopped after 257 iterations
## INFO [10:30:53.727] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 36
## initial value 90710.856785
## iter 10 value 9389.071533
## iter 20 value 1978.273786
## iter 30 value 1154.345322
## iter 40 value 1055.751769
## iter 50 value 1055.646182
## iter 60 value 1053.152741
## iter 70 value 1024.406832
## iter 80 value 648.177396
## iter 90 value 625.975290
## iter 100 value 598.758022
## iter 110 value 575.327067
## iter 120 value 573.888909
## iter 130 value 573.803380
## iter 140 value 573.777109
## iter 150 value 573.669098
## iter 160 value 573.341806
## iter 170 value 571.745094
## iter 180 value 532.026183
## iter 190 value 517.735296
## iter 200 value 507.960102
## iter 210 value 506.437834
## iter 220 value 504.617642
## iter 230 value 503.705293
## iter 240 value 503.700883
## iter 250 value 503.688933
## final value 503.591271
## stopped after 257 iterations
## INFO [10:30:53.736] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 36
## initial value 70631.257076
## iter 10 value 4495.482127
## iter 20 value 2448.706595
## iter 30 value 2021.779394
## iter 40 value 1216.534579
## iter 50 value 856.992696
## iter 60 value 696.864466
## iter 70 value 656.612424
## iter 80 value 636.780871
## iter 90 value 614.046876
## iter 100 value 602.757236
## iter 110 value 586.261302
## iter 120 value 580.121202
## iter 130 value 564.835963
## iter 140 value 557.411219
## iter 150 value 555.355153
## iter 160 value 554.802632
## iter 170 value 554.247228
## iter 180 value 554.093959
## iter 190 value 553.530252
## iter 200 value 552.894922
## iter 210 value 552.793481
## iter 220 value 552.725692
## iter 230 value 552.656873
## iter 240 value 552.650860
## iter 250 value 552.649902
## final value 552.648300
## stopped after 257 iterations
## INFO [10:30:53.744] [mlr3] Finished benchmark
## INFO [10:30:53.754] [bbotk] Result of batch 8:
## INFO [10:30:53.755] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.755] [bbotk] 5 257 8.446055e-05 7.535631 0 0 0.012
## INFO [10:30:53.755] [bbotk] uhash
## INFO [10:30:53.755] [bbotk] 96aab44c-ffff-4529-8e74-eddc48295752
## INFO [10:30:53.757] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.763] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.766] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 85665.386576
## iter 10 value 7251.194591
## iter 20 value 2382.607352
## iter 30 value 1950.377113
## iter 40 value 1294.839217
## iter 50 value 1199.302301
## iter 60 value 1188.159319
## iter 70 value 1187.146704
## iter 80 value 1186.046067
## iter 90 value 1163.268666
## iter 100 value 981.483831
## iter 110 value 570.431792
## iter 120 value 537.329171
## iter 130 value 521.305467
## iter 140 value 504.532884
## iter 150 value 489.910235
## iter 160 value 488.769382
## iter 170 value 488.622312
## iter 180 value 488.071647
## iter 190 value 488.013934
## iter 200 value 487.973054
## iter 210 value 487.923570
## iter 220 value 487.701787
## iter 230 value 467.990947
## iter 240 value 413.782113
## iter 250 value 395.240893
## iter 260 value 357.067397
## iter 270 value 349.133488
## iter 280 value 348.305264
## iter 290 value 347.713777
## iter 300 value 345.088086
## iter 310 value 320.820123
## iter 320 value 279.895429
## iter 330 value 268.506226
## iter 340 value 260.969355
## iter 350 value 259.160701
## final value 258.480380
## stopped after 354 iterations
## INFO [10:30:53.779] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 91306.828416
## iter 10 value 1774.909542
## iter 20 value 770.942773
## iter 30 value 678.391958
## iter 40 value 634.352625
## iter 50 value 623.231705
## iter 60 value 559.437580
## iter 70 value 504.567077
## iter 80 value 491.042748
## iter 90 value 465.027003
## iter 100 value 393.487498
## iter 110 value 366.160653
## iter 120 value 353.903441
## iter 130 value 345.024306
## iter 140 value 339.707931
## iter 150 value 337.808747
## iter 160 value 337.568163
## iter 170 value 337.342092
## iter 180 value 332.378952
## iter 190 value 305.285469
## iter 200 value 276.709274
## iter 210 value 271.655610
## iter 220 value 269.006836
## iter 230 value 267.813738
## iter 240 value 264.278521
## iter 250 value 248.857421
## iter 260 value 227.144885
## iter 270 value 226.026468
## iter 280 value 221.713048
## iter 290 value 218.462372
## iter 300 value 209.800102
## iter 310 value 193.863416
## iter 320 value 192.483102
## iter 330 value 189.150944
## iter 340 value 184.947891
## iter 350 value 181.986300
## final value 181.381046
## stopped after 354 iterations
## INFO [10:30:53.791] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 76030.469242
## iter 10 value 1440.751587
## iter 20 value 900.837585
## iter 30 value 502.655546
## iter 40 value 384.491111
## iter 50 value 236.167648
## iter 60 value 173.874182
## iter 70 value 145.588170
## iter 80 value 127.568922
## iter 90 value 118.444426
## iter 100 value 110.142095
## iter 110 value 104.930467
## iter 120 value 100.353341
## iter 130 value 92.855096
## iter 140 value 91.922868
## iter 150 value 87.133062
## iter 160 value 71.677878
## iter 170 value 58.990648
## iter 180 value 55.897802
## iter 190 value 55.151609
## iter 200 value 53.941270
## iter 210 value 47.665315
## iter 220 value 40.747138
## iter 230 value 36.525824
## iter 240 value 32.560238
## iter 250 value 28.377623
## iter 260 value 26.389032
## iter 270 value 26.223039
## iter 280 value 25.962746
## iter 290 value 23.567179
## iter 300 value 21.429114
## iter 310 value 20.637331
## iter 320 value 20.390108
## iter 330 value 20.117454
## iter 340 value 19.786209
## iter 350 value 19.587138
## final value 19.454948
## stopped after 354 iterations
## INFO [10:30:53.802] [mlr3] Finished benchmark
## INFO [10:30:53.817] [bbotk] Result of batch 9:
## INFO [10:30:53.817] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.817] [bbotk] 9 354 4.414787e-05 15.63984 0 0 0.024
## INFO [10:30:53.817] [bbotk] uhash
## INFO [10:30:53.817] [bbotk] 728ffcff-1d7b-4d5b-8a7a-f0ac9c7957a5
## INFO [10:30:53.819] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.826] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.828] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 83526.008415
## iter 10 value 2573.422157
## iter 20 value 2380.271636
## iter 30 value 2076.736706
## iter 40 value 2074.196190
## iter 50 value 2074.145376
## iter 60 value 2074.082637
## iter 70 value 2074.005287
## iter 80 value 2073.130821
## iter 90 value 2047.710482
## iter 100 value 2019.406243
## iter 110 value 2011.156829
## iter 120 value 1982.801946
## iter 130 value 1657.622055
## final value 1657.622055
## stopped after 130 iterations
## INFO [10:30:53.835] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 90525.235738
## final value 9387.456289
## converged
## INFO [10:30:53.841] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 71063.769970
## iter 10 value 1461.969272
## iter 20 value 828.400309
## iter 30 value 768.494570
## iter 40 value 756.161310
## iter 50 value 751.768268
## iter 60 value 722.109933
## iter 70 value 620.495764
## iter 80 value 618.273241
## iter 90 value 617.241615
## iter 100 value 617.232784
## iter 110 value 617.227217
## iter 120 value 616.839356
## iter 130 value 616.537813
## final value 616.537813
## stopped after 130 iterations
## INFO [10:30:53.847] [mlr3] Finished benchmark
## INFO [10:30:53.858] [bbotk] Result of batch 10:
## INFO [10:30:53.859] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.859] [bbotk] 2 130 9.173569e-05 11.67235 0 0 0.004
## INFO [10:30:53.859] [bbotk] uhash
## INFO [10:30:53.859] [bbotk] beeb57b4-ff7e-4970-869b-43092e30de08
## INFO [10:30:53.861] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.867] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.870] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 43
## initial value 79636.133558
## iter 10 value 5245.247203
## iter 20 value 2454.018347
## iter 30 value 1707.203344
## iter 40 value 1307.560487
## iter 50 value 1215.137599
## iter 60 value 1191.182083
## iter 70 value 1186.133522
## iter 80 value 1185.999976
## iter 90 value 1182.519108
## iter 100 value 1037.831136
## iter 110 value 626.688435
## iter 120 value 572.308236
## iter 130 value 561.881176
## iter 140 value 557.794624
## iter 150 value 527.645978
## iter 160 value 476.116290
## iter 170 value 463.931861
## iter 180 value 458.452855
## iter 190 value 451.731667
## iter 200 value 446.110227
## iter 210 value 445.867318
## iter 220 value 445.137170
## iter 230 value 444.132180
## iter 240 value 443.256481
## iter 250 value 442.897221
## iter 260 value 442.871114
## iter 270 value 442.406041
## iter 280 value 441.893378
## iter 290 value 441.482600
## iter 300 value 441.406909
## iter 310 value 441.347801
## iter 320 value 441.206841
## iter 330 value 440.571699
## final value 440.571699
## stopped after 330 iterations
## INFO [10:30:53.880] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 43
## initial value 94836.221534
## iter 10 value 12075.408166
## iter 20 value 1142.069710
## iter 30 value 630.369278
## iter 40 value 498.391299
## iter 50 value 473.979025
## iter 60 value 447.968411
## iter 70 value 442.696491
## iter 80 value 437.090506
## iter 90 value 408.200367
## iter 100 value 315.170162
## iter 110 value 306.490815
## iter 120 value 303.497789
## iter 130 value 294.863089
## iter 140 value 285.595374
## iter 150 value 279.734802
## iter 160 value 279.323538
## iter 170 value 279.056500
## iter 180 value 278.631320
## iter 190 value 278.385917
## iter 200 value 278.229423
## iter 210 value 278.133215
## iter 210 value 278.133215
## final value 278.133183
## converged
## INFO [10:30:53.889] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 43
## initial value 71289.919879
## iter 10 value 2612.821619
## iter 20 value 1477.287815
## iter 30 value 1303.523446
## iter 40 value 1235.440031
## iter 50 value 1229.635603
## iter 60 value 1228.392711
## iter 70 value 1228.296389
## iter 80 value 1225.365539
## iter 90 value 1186.080151
## iter 100 value 970.766209
## iter 110 value 660.451231
## iter 120 value 650.993676
## iter 130 value 650.419430
## iter 140 value 648.891961
## iter 150 value 609.080442
## iter 160 value 576.824669
## iter 170 value 559.602759
## iter 180 value 553.441875
## iter 190 value 552.896804
## iter 200 value 552.614173
## iter 210 value 552.505141
## iter 220 value 552.278482
## iter 230 value 552.253290
## iter 240 value 552.106313
## iter 250 value 552.036886
## iter 260 value 551.991768
## iter 270 value 551.961330
## iter 280 value 551.567048
## iter 290 value 545.224876
## iter 300 value 460.371443
## iter 310 value 330.000219
## iter 320 value 311.694705
## iter 330 value 306.418319
## final value 306.418319
## stopped after 330 iterations
## INFO [10:30:53.898] [mlr3] Finished benchmark
## INFO [10:30:53.909] [bbotk] Result of batch 11:
## INFO [10:30:53.909] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.909] [bbotk] 6 330 5.967503e-05 11.19307 0 0 0.016
## INFO [10:30:53.909] [bbotk] uhash
## INFO [10:30:53.909] [bbotk] d9eb5ee4-5d63-4a56-b680-522d7846fce2
## INFO [10:30:53.911] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.917] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.920] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 82399.121083
## iter 10 value 2173.802398
## iter 20 value 979.260853
## iter 30 value 491.218844
## iter 40 value 209.096161
## iter 50 value 121.335456
## iter 60 value 88.408134
## iter 70 value 78.301142
## iter 80 value 73.549396
## iter 90 value 68.258364
## iter 100 value 58.150625
## iter 110 value 54.375975
## iter 120 value 53.628419
## iter 130 value 53.286319
## iter 140 value 53.190432
## iter 150 value 53.041689
## iter 160 value 52.908596
## iter 170 value 52.729727
## iter 180 value 52.646827
## iter 190 value 52.368048
## iter 200 value 48.876465
## iter 210 value 34.589864
## iter 220 value 24.985624
## iter 230 value 21.548361
## iter 240 value 20.083392
## iter 250 value 19.727624
## iter 260 value 19.715237
## iter 270 value 19.613373
## iter 280 value 18.269044
## iter 290 value 13.725701
## iter 300 value 9.798220
## iter 310 value 5.327121
## iter 320 value 3.320596
## iter 330 value 2.891799
## iter 340 value 2.516395
## iter 350 value 2.188505
## iter 360 value 1.865785
## iter 370 value 1.757789
## final value 1.748058
## stopped after 375 iterations
## INFO [10:30:53.932] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 90872.777689
## iter 10 value 1322.389031
## iter 20 value 604.274565
## iter 30 value 313.360306
## iter 40 value 238.103380
## iter 50 value 219.845836
## iter 60 value 208.298844
## iter 70 value 164.541149
## iter 80 value 129.740960
## iter 90 value 123.375683
## iter 100 value 119.371061
## iter 110 value 116.451846
## iter 120 value 115.490310
## iter 130 value 115.323802
## iter 140 value 115.263693
## iter 150 value 115.167598
## iter 160 value 114.912126
## iter 170 value 114.469377
## iter 180 value 112.274514
## iter 190 value 100.074941
## iter 200 value 77.725218
## iter 210 value 74.263167
## iter 220 value 72.813958
## iter 230 value 71.362546
## iter 240 value 70.879225
## iter 250 value 68.332842
## iter 260 value 60.453201
## iter 270 value 58.690750
## iter 280 value 58.108263
## iter 290 value 57.160692
## iter 300 value 56.622766
## iter 310 value 55.969941
## iter 320 value 55.419200
## iter 330 value 55.216045
## iter 340 value 54.851598
## iter 350 value 54.773205
## iter 360 value 54.760108
## iter 370 value 54.730510
## final value 54.697289
## stopped after 375 iterations
## INFO [10:30:53.948] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 74152.731462
## iter 10 value 6196.108952
## iter 20 value 3736.803184
## iter 30 value 2413.888138
## iter 40 value 2291.850154
## iter 50 value 2259.960527
## iter 60 value 2141.934892
## iter 70 value 2105.072485
## iter 80 value 1806.942259
## iter 90 value 1469.172155
## iter 100 value 1015.590197
## iter 110 value 867.788402
## iter 120 value 854.731535
## iter 130 value 817.352466
## iter 140 value 785.924371
## iter 150 value 784.957679
## iter 160 value 783.947949
## iter 170 value 783.463220
## iter 180 value 783.220465
## iter 190 value 782.461445
## iter 200 value 782.309269
## iter 210 value 765.697176
## iter 220 value 740.007740
## iter 230 value 736.205654
## iter 240 value 712.179666
## iter 250 value 703.470341
## iter 260 value 698.533504
## iter 270 value 697.501779
## iter 280 value 697.325203
## iter 290 value 696.707405
## iter 300 value 696.519476
## iter 310 value 696.460665
## iter 320 value 696.000034
## iter 330 value 692.488132
## iter 340 value 554.350074
## iter 350 value 527.966766
## iter 360 value 526.754412
## iter 370 value 526.252214
## final value 526.117605
## stopped after 375 iterations
## INFO [10:30:53.959] [mlr3] Finished benchmark
## INFO [10:30:53.970] [bbotk] Result of batch 12:
## INFO [10:30:53.970] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:53.970] [bbotk] 8 375 3.046366e-05 10.47677 0 0 0.022
## INFO [10:30:53.970] [bbotk] uhash
## INFO [10:30:53.970] [bbotk] 2667574f-24f3-49b8-a40d-23951ceae7ae
## INFO [10:30:53.972] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:53.979] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:53.981] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 83304.497617
## final value 10213.586790
## converged
## INFO [10:30:53.988] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 96557.705485
## iter 10 value 1937.823336
## iter 20 value 1428.015146
## iter 30 value 1054.731678
## iter 40 value 1054.241533
## iter 50 value 1054.211974
## final value 1054.205576
## converged
## INFO [10:30:53.994] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 74656.934215
## iter 10 value 6196.384232
## iter 10 value 6196.384212
## final value 6196.384212
## converged
## INFO [10:30:54.001] [mlr3] Finished benchmark
## INFO [10:30:54.012] [bbotk] Result of batch 13:
## INFO [10:30:54.013] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.013] [bbotk] 2 388 5.57986e-05 12.87737 0 0 0.005
## INFO [10:30:54.013] [bbotk] uhash
## INFO [10:30:54.013] [bbotk] 6d74e0e0-4c15-4cb8-b490-ff880c03623f
## INFO [10:30:54.015] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.021] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.024] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 71
## initial value 78380.265783
## iter 10 value 6062.804461
## iter 20 value 2633.420211
## iter 30 value 1979.100540
## iter 40 value 1378.903561
## iter 50 value 819.377784
## iter 60 value 384.320474
## iter 70 value 310.772018
## iter 80 value 294.847693
## iter 90 value 128.492609
## iter 100 value 110.234406
## iter 110 value 100.005184
## iter 120 value 96.407656
## iter 130 value 94.277438
## iter 140 value 85.547150
## iter 150 value 76.082626
## iter 160 value 75.281462
## iter 170 value 74.894498
## iter 180 value 74.220900
## iter 190 value 71.582009
## final value 70.733365
## stopped after 197 iterations
## INFO [10:30:54.034] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 71
## initial value 93292.199688
## iter 10 value 1128.739213
## iter 20 value 518.165172
## iter 30 value 347.320866
## iter 40 value 219.655085
## iter 50 value 172.692857
## iter 60 value 148.938210
## iter 70 value 131.431465
## iter 80 value 124.732948
## iter 90 value 109.185991
## iter 100 value 97.935256
## iter 110 value 82.746873
## iter 120 value 78.656500
## iter 130 value 76.236648
## iter 140 value 74.146852
## iter 150 value 73.633737
## iter 160 value 70.980537
## iter 170 value 65.870566
## iter 180 value 64.709445
## iter 190 value 63.443562
## final value 62.983988
## stopped after 197 iterations
## INFO [10:30:54.045] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 71
## initial value 73186.733313
## iter 10 value 1102.020836
## iter 20 value 631.799835
## iter 30 value 387.795109
## iter 40 value 269.433803
## iter 50 value 200.327095
## iter 60 value 131.849743
## iter 70 value 97.747650
## iter 80 value 68.568269
## iter 90 value 55.799112
## iter 100 value 41.485683
## iter 110 value 31.849085
## iter 120 value 22.187898
## iter 130 value 13.385345
## iter 140 value 10.779871
## iter 150 value 9.077982
## iter 160 value 8.776718
## iter 170 value 8.495442
## iter 180 value 8.166468
## iter 190 value 7.051369
## final value 6.637890
## stopped after 197 iterations
## INFO [10:30:54.054] [mlr3] Finished benchmark
## INFO [10:30:54.066] [bbotk] Result of batch 14:
## INFO [10:30:54.067] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.067] [bbotk] 10 197 4.718307e-05 21.98697 0 0 0.017
## INFO [10:30:54.067] [bbotk] uhash
## INFO [10:30:54.067] [bbotk] dd868135-705a-4dad-bcc5-cb1dc8642e79
## INFO [10:30:54.072] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.079] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.081] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 22
## initial value 82588.715460
## iter 10 value 3441.393252
## iter 20 value 1396.262597
## iter 30 value 510.900663
## iter 40 value 295.507986
## iter 50 value 284.425299
## iter 60 value 281.988739
## iter 70 value 281.067366
## iter 80 value 281.050640
## iter 90 value 280.854013
## iter 100 value 280.702675
## iter 110 value 280.655638
## iter 120 value 280.646882
## final value 280.646874
## converged
## INFO [10:30:54.088] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 22
## initial value 94582.412305
## iter 10 value 6527.851924
## iter 20 value 1462.297628
## iter 30 value 1132.267811
## iter 40 value 1049.546777
## iter 50 value 984.576001
## iter 60 value 873.284690
## iter 70 value 832.313449
## iter 80 value 753.639722
## iter 90 value 540.100949
## iter 100 value 470.453780
## iter 110 value 366.368441
## iter 120 value 337.411381
## iter 130 value 336.433752
## iter 140 value 336.322440
## iter 150 value 336.263905
## iter 160 value 335.211698
## iter 170 value 335.203986
## iter 180 value 335.163374
## final value 335.162254
## converged
## INFO [10:30:54.096] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 22
## initial value 71034.157386
## iter 10 value 2008.928109
## iter 20 value 823.325166
## iter 30 value 757.416850
## iter 40 value 680.374197
## iter 50 value 636.656520
## iter 60 value 635.387202
## iter 70 value 579.207291
## iter 80 value 572.106054
## iter 90 value 571.811993
## iter 100 value 571.344959
## iter 110 value 571.342817
## final value 571.342590
## converged
## INFO [10:30:54.102] [mlr3] Finished benchmark
## INFO [10:30:54.113] [bbotk] Result of batch 15:
## INFO [10:30:54.114] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.114] [bbotk] 3 468 7.639612e-06 8.031909 0 0 0.006
## INFO [10:30:54.114] [bbotk] uhash
## INFO [10:30:54.114] [bbotk] ef3ce57f-2760-41d7-9d0a-0800de8754d0
## INFO [10:30:54.116] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.122] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.125] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 81314.189388
## iter 10 value 2509.426049
## iter 20 value 1222.136972
## iter 30 value 817.546688
## iter 40 value 749.916669
## iter 50 value 699.871423
## iter 60 value 687.796082
## iter 70 value 659.269074
## iter 80 value 649.504890
## iter 90 value 648.071909
## iter 100 value 647.197922
## iter 110 value 645.168530
## iter 120 value 644.853470
## iter 130 value 644.791646
## iter 140 value 644.550962
## iter 150 value 644.540071
## iter 150 value 644.540069
## final value 644.540044
## converged
## INFO [10:30:54.133] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 93711.090933
## iter 10 value 5898.522032
## iter 20 value 2582.053813
## iter 30 value 868.887474
## iter 40 value 649.992599
## iter 50 value 573.986412
## iter 60 value 564.761837
## iter 70 value 564.444572
## iter 80 value 564.328657
## iter 90 value 564.194744
## iter 100 value 564.139625
## iter 110 value 564.131956
## iter 120 value 564.124405
## final value 564.123454
## converged
## INFO [10:30:54.140] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 69975.286002
## iter 10 value 1541.122759
## iter 20 value 1333.893095
## iter 30 value 1242.329923
## iter 40 value 1231.283308
## iter 50 value 1227.937534
## iter 60 value 1227.668936
## iter 70 value 1227.613656
## iter 80 value 1226.606861
## iter 90 value 1181.451100
## iter 100 value 777.451377
## iter 110 value 664.551588
## iter 120 value 652.432772
## iter 130 value 642.677958
## iter 140 value 634.223781
## iter 150 value 633.554872
## iter 160 value 633.496513
## iter 170 value 633.217075
## iter 180 value 633.142551
## iter 180 value 633.142550
## iter 180 value 633.142550
## final value 633.142550
## converged
## INFO [10:30:54.147] [mlr3] Finished benchmark
## INFO [10:30:54.158] [bbotk] Result of batch 16:
## INFO [10:30:54.158] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.158] [bbotk] 2 325 9.797454e-05 8.744332 0 0 0.008
## INFO [10:30:54.158] [bbotk] uhash
## INFO [10:30:54.158] [bbotk] 0434d79c-d8fb-491f-8788-c54952196aff
## INFO [10:30:54.160] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.167] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.169] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 79977.495241
## iter 10 value 2816.707525
## iter 20 value 764.358071
## iter 30 value 480.137966
## iter 40 value 446.790860
## iter 50 value 424.794967
## iter 60 value 297.663224
## iter 70 value 282.449484
## iter 80 value 281.082705
## iter 90 value 280.920574
## iter 100 value 280.915255
## iter 110 value 280.859430
## iter 120 value 280.849118
## iter 130 value 280.516732
## iter 140 value 264.219611
## iter 150 value 124.369576
## iter 160 value 109.598822
## iter 170 value 104.578827
## iter 180 value 95.746123
## iter 190 value 92.351014
## iter 200 value 89.769187
## iter 210 value 89.467470
## iter 220 value 89.146365
## iter 230 value 88.657389
## iter 240 value 88.442512
## iter 250 value 88.438762
## final value 88.437505
## stopped after 254 iterations
## INFO [10:30:54.180] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 93072.122663
## iter 10 value 1255.905523
## iter 20 value 490.129386
## iter 30 value 275.081993
## iter 40 value 188.881928
## iter 50 value 159.404862
## iter 60 value 147.278807
## iter 70 value 141.195425
## iter 80 value 135.984888
## iter 90 value 132.470695
## iter 100 value 128.003054
## iter 110 value 126.379700
## iter 120 value 125.777812
## iter 130 value 125.285751
## iter 140 value 123.621978
## iter 150 value 120.637690
## iter 160 value 119.979551
## iter 170 value 119.901709
## iter 180 value 119.715008
## iter 190 value 119.515214
## iter 200 value 119.299445
## iter 210 value 119.223555
## iter 220 value 118.342614
## iter 230 value 115.993512
## iter 240 value 115.299658
## iter 250 value 114.727403
## final value 114.468011
## stopped after 254 iterations
## INFO [10:30:54.193] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 70411.577377
## iter 10 value 1512.028079
## iter 20 value 592.717491
## iter 30 value 288.078199
## iter 40 value 147.104424
## iter 50 value 89.487636
## iter 60 value 80.024272
## iter 70 value 74.890404
## iter 80 value 71.762720
## iter 90 value 69.998044
## iter 100 value 69.116169
## iter 110 value 68.512528
## iter 120 value 67.906348
## iter 130 value 67.502247
## iter 140 value 65.911785
## iter 150 value 51.654545
## iter 160 value 49.363559
## iter 170 value 49.101263
## iter 180 value 48.833104
## iter 190 value 48.611851
## iter 200 value 46.423534
## iter 210 value 42.263167
## iter 220 value 32.575811
## iter 230 value 27.070810
## iter 240 value 25.689631
## iter 250 value 24.858624
## final value 24.209430
## stopped after 254 iterations
## INFO [10:30:54.203] [mlr3] Finished benchmark
## INFO [10:30:54.214] [bbotk] Result of batch 17:
## INFO [10:30:54.214] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.214] [bbotk] 8 254 1.869049e-05 12.67996 0 0 0.019
## INFO [10:30:54.214] [bbotk] uhash
## INFO [10:30:54.214] [bbotk] 7a37b4d1-6d89-4da6-bb8b-f87517d6dcaf
## INFO [10:30:54.216] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.223] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.226] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 84812.034772
## iter 10 value 1369.699687
## iter 20 value 514.646355
## iter 30 value 235.874150
## iter 40 value 153.652414
## iter 50 value 143.300444
## iter 60 value 139.009170
## iter 70 value 138.061437
## iter 80 value 132.121360
## iter 90 value 128.404964
## iter 100 value 127.920573
## iter 110 value 127.703287
## iter 120 value 127.498537
## iter 130 value 127.431584
## iter 140 value 127.179158
## iter 150 value 120.628891
## iter 160 value 75.213576
## iter 170 value 58.612555
## iter 180 value 56.045767
## final value 55.359221
## stopped after 185 iterations
## INFO [10:30:54.235] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 93062.566124
## iter 10 value 1731.531066
## iter 20 value 730.734190
## iter 30 value 459.564653
## iter 40 value 377.782238
## iter 50 value 343.191731
## iter 60 value 305.472638
## iter 70 value 273.579238
## iter 80 value 271.323407
## iter 90 value 268.915280
## iter 100 value 268.331324
## iter 110 value 268.146760
## iter 120 value 268.123313
## iter 130 value 268.100760
## iter 140 value 268.029071
## iter 150 value 267.798299
## iter 160 value 266.585781
## iter 170 value 263.592866
## iter 180 value 232.268886
## final value 230.600332
## stopped after 185 iterations
## INFO [10:30:54.244] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 73338.507367
## iter 10 value 3488.106582
## iter 20 value 1454.892265
## iter 30 value 1325.571767
## iter 40 value 1251.485783
## iter 50 value 1232.114554
## iter 60 value 1225.956003
## iter 70 value 1217.446557
## iter 80 value 1148.930003
## iter 90 value 1068.162607
## iter 100 value 1053.687821
## iter 110 value 782.640978
## iter 120 value 624.137058
## iter 130 value 603.765716
## iter 140 value 599.736813
## iter 150 value 580.483463
## iter 160 value 577.856753
## iter 170 value 574.230878
## iter 180 value 572.830272
## final value 572.639300
## stopped after 185 iterations
## INFO [10:30:54.251] [mlr3] Finished benchmark
## INFO [10:30:54.263] [bbotk] Result of batch 18:
## INFO [10:30:54.263] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.263] [bbotk] 8 185 4.781939e-06 8.27891 0 0 0.011
## INFO [10:30:54.263] [bbotk] uhash
## INFO [10:30:54.263] [bbotk] 9d3ab2d7-2799-4dd0-ac9b-c6ab163f25e7
## INFO [10:30:54.265] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.272] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.274] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 84679.186352
## iter 10 value 3051.238128
## iter 20 value 2338.916070
## iter 30 value 1768.527276
## iter 40 value 1619.210956
## iter 50 value 1273.195758
## iter 60 value 1163.948832
## iter 70 value 858.076898
## iter 80 value 501.962501
## iter 90 value 330.395638
## iter 100 value 275.354349
## iter 110 value 187.047910
## iter 120 value 153.198680
## iter 130 value 147.711375
## iter 140 value 143.339885
## iter 150 value 142.677449
## iter 160 value 142.649075
## iter 170 value 141.885884
## iter 180 value 139.178302
## iter 190 value 109.797428
## final value 100.511879
## stopped after 195 iterations
## INFO [10:30:54.282] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 89528.992131
## iter 10 value 7585.338203
## iter 20 value 1950.803305
## iter 30 value 1584.321193
## iter 40 value 1061.593980
## iter 50 value 1054.859696
## iter 60 value 1054.330179
## iter 70 value 1052.655418
## iter 80 value 1045.858571
## iter 90 value 955.700718
## iter 100 value 587.858247
## iter 110 value 483.283274
## iter 120 value 467.569072
## iter 130 value 465.000636
## iter 140 value 464.158064
## iter 150 value 462.553356
## iter 160 value 461.637722
## iter 170 value 461.618000
## iter 180 value 461.576244
## iter 190 value 461.325083
## final value 459.458901
## stopped after 195 iterations
## INFO [10:30:54.290] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 71620.247325
## iter 10 value 2025.889874
## iter 20 value 1621.018493
## iter 30 value 1544.914978
## iter 40 value 1309.178980
## iter 50 value 1242.964948
## iter 60 value 1232.737144
## iter 70 value 1228.670479
## iter 80 value 1228.435556
## iter 90 value 1227.776393
## iter 100 value 1222.302633
## iter 110 value 1209.749624
## iter 120 value 1006.872849
## iter 130 value 741.973800
## iter 140 value 651.816122
## iter 150 value 650.822330
## iter 160 value 650.536492
## iter 170 value 650.498930
## iter 180 value 650.387231
## iter 190 value 650.385247
## final value 650.382901
## stopped after 195 iterations
## INFO [10:30:54.298] [mlr3] Finished benchmark
## INFO [10:30:54.309] [bbotk] Result of batch 19:
## INFO [10:30:54.309] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.309] [bbotk] 4 195 9.59708e-05 8.559207 0 0 0.007
## INFO [10:30:54.309] [bbotk] uhash
## INFO [10:30:54.309] [bbotk] 0ed045f2-e0aa-456f-85be-b3b7dedb0f6d
## INFO [10:30:54.314] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.321] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.324] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 80164.203510
## iter 10 value 3353.416712
## iter 20 value 1483.428501
## iter 30 value 1229.306336
## iter 40 value 1193.156544
## iter 50 value 1174.923281
## iter 60 value 652.911179
## iter 70 value 594.223388
## iter 80 value 531.700278
## iter 90 value 503.330463
## iter 100 value 490.772083
## iter 110 value 490.739804
## iter 120 value 485.496364
## iter 130 value 471.518004
## iter 140 value 449.615822
## iter 150 value 446.307830
## iter 160 value 445.554485
## iter 170 value 442.000923
## iter 180 value 441.434654
## iter 190 value 441.411321
## iter 200 value 441.407580
## iter 210 value 441.383456
## iter 220 value 441.188828
## iter 230 value 438.290074
## iter 240 value 423.389148
## iter 250 value 339.119115
## iter 260 value 299.706717
## iter 270 value 295.758957
## iter 280 value 293.932473
## iter 290 value 293.788532
## iter 300 value 293.745018
## iter 310 value 293.270093
## iter 320 value 291.202797
## iter 330 value 287.409031
## iter 340 value 243.620960
## iter 350 value 227.172110
## iter 360 value 212.119781
## iter 370 value 206.150268
## final value 203.531674
## stopped after 377 iterations
## INFO [10:30:54.334] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 95338.099703
## iter 10 value 1279.515843
## iter 20 value 811.543025
## iter 30 value 551.592036
## iter 40 value 531.629612
## iter 50 value 524.008567
## iter 60 value 520.062676
## iter 70 value 509.902287
## iter 80 value 431.743742
## iter 90 value 408.786510
## iter 100 value 402.197063
## iter 110 value 399.930782
## iter 120 value 398.841227
## iter 130 value 390.600003
## iter 140 value 371.509264
## iter 150 value 323.296854
## iter 160 value 253.568118
## iter 170 value 227.545542
## iter 180 value 221.711984
## iter 190 value 218.254035
## iter 200 value 212.773766
## iter 210 value 198.902423
## iter 220 value 191.662435
## iter 230 value 190.143517
## iter 240 value 188.499591
## iter 250 value 184.283264
## iter 260 value 183.179151
## iter 270 value 182.263639
## iter 280 value 181.759870
## final value 181.759268
## converged
## INFO [10:30:54.343] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 73293.754851
## iter 10 value 2254.147713
## iter 20 value 1241.204852
## iter 30 value 1162.715463
## iter 40 value 1063.389599
## iter 50 value 908.093354
## iter 60 value 789.599929
## iter 70 value 775.702807
## iter 80 value 763.744912
## iter 90 value 760.926744
## iter 100 value 758.491555
## iter 110 value 758.222134
## iter 120 value 758.115193
## iter 130 value 758.020011
## final value 758.019546
## converged
## INFO [10:30:54.349] [mlr3] Finished benchmark
## INFO [10:30:54.360] [bbotk] Result of batch 20:
## INFO [10:30:54.361] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.361] [bbotk] 4 377 7.073213e-05 9.926329 0 0 0.012
## INFO [10:30:54.361] [bbotk] uhash
## INFO [10:30:54.361] [bbotk] e70725a1-f490-4da0-897d-1ed9ba54d3a7
## INFO [10:30:54.364] [bbotk] Finished optimizing after 20 evaluation(s)
## INFO [10:30:54.365] [bbotk] Result:
## INFO [10:30:54.365] [bbotk] size maxit decay learner_param_vals x_domain regr.rmse
## INFO [10:30:54.365] [bbotk] 5 257 8.446055e-05 <list[3]> <list[3]> 7.535631
## # weights: 36
## initial value 127901.355743
## iter 10 value 6804.759814
## iter 20 value 3303.920358
## iter 30 value 2270.356172
## iter 40 value 1940.492304
## iter 50 value 1913.868451
## iter 60 value 1909.736810
## iter 70 value 1906.178731
## iter 80 value 1876.327485
## iter 90 value 1785.985142
## iter 100 value 1361.090282
## iter 110 value 1197.696364
## iter 120 value 1187.815554
## iter 130 value 1185.528538
## iter 140 value 1183.831801
## iter 150 value 1183.390725
## iter 160 value 1182.595410
## iter 170 value 1182.325020
## iter 180 value 1181.208723
## iter 190 value 1180.018153
## iter 200 value 1154.999100
## iter 210 value 1048.866278
## iter 220 value 952.566535
## iter 230 value 948.318255
## iter 240 value 936.864848
## iter 250 value 934.998290
## final value 934.841760
## stopped after 257 iterations
## INFO [10:30:54.382] [mlr3] Applying learner 'regr.nnet.tuned' on task 'cereal' (iter 2/5)
## INFO [10:30:54.400] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorEvals> [n_evals=20, k=0]'
## INFO [10:30:54.406] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.412] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.415] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 87511.987406
## iter 10 value 2915.940434
## iter 20 value 1337.078126
## iter 30 value 743.112404
## iter 40 value 589.473416
## iter 50 value 533.016543
## iter 60 value 485.848911
## iter 70 value 459.397828
## iter 80 value 447.172808
## iter 90 value 414.463300
## iter 100 value 401.023472
## iter 110 value 395.365489
## iter 120 value 394.403504
## iter 130 value 390.189913
## iter 140 value 382.840960
## iter 150 value 380.804766
## iter 160 value 379.540906
## iter 170 value 378.841870
## iter 180 value 378.326727
## iter 190 value 377.263313
## iter 200 value 375.523934
## iter 210 value 372.141655
## iter 220 value 371.416101
## iter 230 value 369.394672
## iter 240 value 365.972789
## iter 250 value 365.189187
## iter 260 value 363.775150
## iter 270 value 351.336057
## iter 280 value 277.246975
## iter 290 value 182.700352
## final value 181.232664
## stopped after 291 iterations
## INFO [10:30:54.429] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 87861.820382
## final value 8477.423873
## converged
## INFO [10:30:54.436] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 74752.699146
## iter 10 value 2971.457295
## iter 20 value 1076.624197
## iter 30 value 965.092184
## iter 40 value 915.145656
## iter 50 value 911.666283
## iter 60 value 911.060186
## iter 70 value 910.572299
## iter 80 value 877.520049
## iter 90 value 686.236485
## iter 100 value 648.530498
## iter 110 value 624.798198
## iter 120 value 621.496656
## iter 130 value 616.626386
## iter 140 value 615.068124
## iter 150 value 604.420646
## iter 160 value 587.994646
## iter 170 value 587.120081
## iter 180 value 569.663058
## iter 190 value 508.258357
## iter 200 value 491.027542
## iter 210 value 486.508749
## iter 220 value 472.688600
## iter 230 value 435.076371
## iter 240 value 411.805494
## iter 250 value 407.577239
## iter 260 value 405.493300
## iter 270 value 382.742905
## iter 280 value 350.474030
## iter 290 value 337.213030
## final value 337.110597
## stopped after 291 iterations
## INFO [10:30:54.445] [mlr3] Finished benchmark
## INFO [10:30:54.455] [bbotk] Result of batch 1:
## INFO [10:30:54.456] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.456] [bbotk] 7 291 8.033919e-05 23.07666 0 0 0.017
## INFO [10:30:54.456] [bbotk] uhash
## INFO [10:30:54.456] [bbotk] d7e3abbf-c594-439f-a052-897e5f25655b
## INFO [10:30:54.458] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.464] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.467] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 22
## initial value 82967.620929
## iter 10 value 2596.137926
## iter 20 value 1391.496126
## iter 30 value 1182.376107
## iter 40 value 784.510911
## iter 50 value 557.027099
## iter 60 value 461.903777
## iter 70 value 412.620698
## iter 80 value 410.951873
## iter 90 value 410.173826
## iter 100 value 403.804007
## iter 110 value 402.912153
## iter 120 value 401.382729
## iter 130 value 367.007835
## iter 140 value 254.294164
## iter 150 value 237.871902
## iter 160 value 230.685628
## iter 170 value 230.370981
## iter 180 value 229.604286
## iter 190 value 228.539782
## iter 200 value 228.257575
## iter 210 value 227.997574
## iter 220 value 227.950336
## iter 230 value 227.737112
## iter 240 value 227.505693
## iter 250 value 227.429614
## iter 260 value 227.347105
## iter 270 value 227.313670
## iter 280 value 227.305177
## iter 290 value 227.265644
## iter 300 value 227.259169
## iter 310 value 227.258376
## iter 320 value 227.248583
## iter 330 value 227.245862
## final value 227.245862
## stopped after 330 iterations
## INFO [10:30:54.476] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 22
## initial value 82098.887986
## iter 10 value 4509.072690
## iter 20 value 2066.117416
## iter 30 value 1587.578656
## iter 40 value 1387.818509
## iter 50 value 1271.403803
## iter 60 value 791.386812
## iter 70 value 715.483153
## iter 80 value 678.915550
## iter 90 value 580.714922
## iter 100 value 542.734983
## iter 110 value 530.899829
## iter 120 value 525.679962
## iter 130 value 516.798485
## iter 140 value 508.370488
## iter 150 value 507.549191
## final value 507.545092
## converged
## INFO [10:30:54.483] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 22
## initial value 75898.243322
## iter 10 value 5512.813432
## iter 20 value 1023.961775
## iter 30 value 981.607080
## iter 40 value 928.760992
## iter 50 value 912.022234
## iter 60 value 910.654020
## iter 70 value 910.247713
## iter 80 value 910.223549
## iter 90 value 910.213466
## iter 100 value 910.162721
## iter 110 value 909.983156
## iter 120 value 907.607645
## iter 130 value 871.836396
## iter 140 value 558.401676
## iter 150 value 466.299008
## iter 160 value 461.005444
## iter 170 value 459.859768
## iter 180 value 459.619756
## iter 190 value 459.308080
## iter 200 value 450.072419
## iter 210 value 448.523209
## iter 220 value 448.106342
## iter 230 value 447.134916
## iter 240 value 446.730041
## iter 250 value 445.837217
## iter 260 value 445.360426
## iter 260 value 445.360426
## final value 445.360426
## converged
## INFO [10:30:54.491] [mlr3] Finished benchmark
## INFO [10:30:54.502] [bbotk] Result of batch 2:
## INFO [10:30:54.502] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.502] [bbotk] 3 330 3.144581e-05 7.846788 0 0 0.011
## INFO [10:30:54.502] [bbotk] uhash
## INFO [10:30:54.502] [bbotk] c01665ff-80fa-451e-861f-4f5fd887e0f7
## INFO [10:30:54.504] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.511] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.513] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 78685.418636
## iter 10 value 3286.478429
## iter 20 value 2277.330955
## iter 30 value 2259.259207
## iter 40 value 2139.134521
## iter 50 value 1901.234382
## iter 60 value 1563.090197
## iter 70 value 1454.446144
## iter 80 value 1444.543037
## iter 90 value 1442.182373
## iter 100 value 1442.057716
## final value 1442.055462
## converged
## INFO [10:30:54.520] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 85905.993576
## iter 10 value 3284.373414
## iter 20 value 2313.941951
## iter 30 value 1765.071798
## iter 40 value 1464.270178
## iter 50 value 1365.667716
## iter 60 value 1357.467392
## iter 70 value 1346.479315
## iter 80 value 1345.963002
## iter 90 value 1344.393609
## iter 100 value 1344.305756
## iter 110 value 1343.457049
## iter 120 value 1343.153368
## iter 130 value 1342.938900
## iter 140 value 1342.887658
## iter 150 value 1342.823482
## iter 150 value 1342.823478
## iter 150 value 1342.823477
## final value 1342.823477
## converged
## INFO [10:30:54.527] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 77348.377645
## final value 7044.087912
## converged
## INFO [10:30:54.533] [mlr3] Finished benchmark
## INFO [10:30:54.548] [bbotk] Result of batch 3:
## INFO [10:30:54.548] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.548] [bbotk] 1 479 4.288808e-06 9.572197 0 0 0.006
## INFO [10:30:54.548] [bbotk] uhash
## INFO [10:30:54.548] [bbotk] 2e431fd1-7bec-442c-b82f-8a28dc94e3bf
## INFO [10:30:54.550] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.557] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.559] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 36
## initial value 84033.038879
## iter 10 value 1385.762341
## iter 20 value 827.283786
## iter 30 value 671.274771
## iter 40 value 662.299290
## iter 50 value 655.480146
## iter 60 value 652.382961
## iter 70 value 652.166040
## iter 80 value 652.046847
## final value 652.032192
## converged
## INFO [10:30:54.567] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 36
## initial value 86131.659908
## iter 10 value 2611.766592
## iter 20 value 1717.306577
## iter 30 value 1408.213682
## iter 40 value 1366.770511
## iter 50 value 1350.571397
## iter 60 value 1347.349889
## iter 70 value 1346.983931
## iter 80 value 1339.759114
## iter 90 value 1327.724199
## iter 100 value 1138.767594
## iter 110 value 1067.780603
## iter 120 value 1040.238949
## iter 130 value 1024.581113
## iter 140 value 1013.161784
## iter 150 value 997.569140
## iter 160 value 823.665477
## iter 170 value 753.573931
## iter 180 value 750.217460
## iter 190 value 749.818489
## iter 200 value 749.374246
## iter 210 value 743.159198
## iter 220 value 740.798897
## iter 230 value 734.193355
## iter 240 value 619.379411
## iter 250 value 441.628926
## iter 260 value 342.696096
## iter 270 value 280.099902
## iter 280 value 252.651563
## iter 290 value 250.436409
## iter 300 value 249.175287
## iter 310 value 248.750530
## iter 320 value 247.696160
## iter 330 value 246.226466
## iter 340 value 244.005015
## iter 350 value 239.669297
## iter 360 value 239.509359
## iter 370 value 239.223683
## iter 380 value 237.273185
## iter 390 value 235.245823
## iter 400 value 234.947074
## final value 234.910240
## stopped after 407 iterations
## INFO [10:30:54.577] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 36
## initial value 79240.148912
## final value 7045.680397
## converged
## INFO [10:30:54.583] [mlr3] Finished benchmark
## INFO [10:30:54.594] [bbotk] Result of batch 4:
## INFO [10:30:54.595] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.595] [bbotk] 5 407 9.082541e-05 12.11542 0 0 0.01
## INFO [10:30:54.595] [bbotk] uhash
## INFO [10:30:54.595] [bbotk] 31ba20aa-3a0e-47a0-81f4-46a26df11aef
## INFO [10:30:54.596] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.603] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.606] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 84498.335885
## iter 10 value 1867.168156
## iter 20 value 985.174694
## iter 30 value 541.991277
## iter 40 value 418.486207
## iter 50 value 315.848310
## iter 60 value 292.039226
## iter 70 value 283.626416
## iter 80 value 283.267859
## iter 90 value 282.013681
## iter 100 value 280.402615
## iter 110 value 279.102179
## iter 120 value 277.542744
## iter 130 value 265.352600
## iter 140 value 264.410301
## iter 150 value 264.020971
## iter 160 value 263.760686
## iter 170 value 262.695287
## iter 180 value 262.693666
## iter 190 value 262.681497
## iter 200 value 262.650120
## iter 210 value 262.520541
## iter 220 value 262.517975
## final value 262.503110
## converged
## INFO [10:30:54.614] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 85643.156442
## final value 8475.126660
## converged
## INFO [10:30:54.620] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 75823.398374
## iter 10 value 6694.715873
## iter 20 value 1849.105416
## iter 30 value 981.424330
## iter 40 value 942.116477
## iter 50 value 912.527790
## iter 60 value 911.321115
## iter 70 value 909.969339
## iter 80 value 839.834353
## iter 90 value 673.093731
## iter 100 value 624.074160
## iter 110 value 612.945609
## iter 120 value 605.494102
## iter 130 value 596.741712
## iter 140 value 594.428028
## iter 150 value 581.136898
## iter 160 value 534.638094
## iter 170 value 493.305003
## iter 180 value 477.073071
## iter 190 value 473.940477
## iter 200 value 472.806850
## iter 210 value 471.616944
## iter 220 value 471.529677
## iter 230 value 471.507498
## iter 240 value 469.985980
## iter 250 value 445.832957
## iter 260 value 397.349839
## iter 270 value 375.178460
## iter 280 value 359.269155
## iter 290 value 356.900576
## iter 300 value 356.639975
## iter 310 value 356.280907
## iter 320 value 354.898233
## iter 330 value 354.460221
## iter 340 value 354.309921
## iter 350 value 352.365328
## iter 360 value 342.912368
## iter 370 value 314.541605
## iter 380 value 292.219649
## iter 390 value 265.099835
## iter 400 value 237.131251
## iter 410 value 219.341296
## iter 420 value 217.889263
## iter 430 value 214.975215
## iter 440 value 213.926399
## iter 450 value 202.561353
## iter 460 value 195.940934
## iter 470 value 179.899299
## final value 176.153657
## stopped after 479 iterations
## INFO [10:30:54.630] [mlr3] Finished benchmark
## INFO [10:30:54.640] [bbotk] Result of batch 5:
## INFO [10:30:54.641] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.641] [bbotk] 4 479 8.879083e-05 9.78283 0 0 0.011
## INFO [10:30:54.641] [bbotk] uhash
## INFO [10:30:54.641] [bbotk] 0eee644a-0aa6-40e5-9b6a-a0cd284ce9b1
## INFO [10:30:54.643] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.650] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.655] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 43
## initial value 79984.980413
## iter 10 value 8587.465479
## iter 20 value 3647.952069
## iter 30 value 2732.806869
## iter 40 value 2717.210874
## iter 50 value 2706.722918
## iter 60 value 2706.564705
## iter 70 value 2704.521578
## iter 80 value 2593.212885
## iter 90 value 1332.534108
## iter 100 value 1312.799366
## iter 110 value 1308.815954
## iter 120 value 1300.108501
## iter 130 value 1296.650003
## iter 140 value 1296.541118
## iter 150 value 1296.027454
## iter 160 value 1279.395880
## iter 170 value 1182.367982
## iter 180 value 1157.447485
## iter 190 value 1156.904719
## iter 200 value 1156.872509
## iter 210 value 1156.836669
## final value 1156.834165
## stopped after 212 iterations
## INFO [10:30:54.665] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 43
## initial value 83249.906022
## iter 10 value 6000.716963
## iter 20 value 2032.442358
## iter 30 value 1677.687011
## iter 40 value 1389.673714
## iter 50 value 1357.071445
## iter 60 value 1348.970800
## iter 70 value 1347.263522
## iter 80 value 1346.833029
## iter 90 value 1346.467620
## iter 100 value 1343.617199
## iter 110 value 1277.894344
## iter 120 value 1111.847253
## iter 130 value 1066.020363
## iter 140 value 1010.887531
## iter 150 value 890.501530
## iter 160 value 794.052777
## iter 170 value 766.330924
## iter 180 value 752.886515
## iter 190 value 749.444335
## iter 200 value 749.201350
## iter 210 value 747.945479
## final value 747.829006
## stopped after 212 iterations
## INFO [10:30:54.673] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 43
## initial value 80521.861949
## iter 10 value 3033.602970
## iter 20 value 1535.029055
## iter 30 value 944.815854
## iter 40 value 743.529872
## iter 50 value 721.059803
## iter 60 value 717.067529
## iter 70 value 713.606908
## iter 80 value 684.752852
## iter 90 value 531.056243
## iter 100 value 485.252432
## iter 110 value 472.957615
## iter 120 value 469.925579
## iter 130 value 468.574243
## iter 140 value 467.810810
## iter 150 value 467.103306
## iter 160 value 466.979932
## iter 170 value 466.612765
## iter 180 value 464.063588
## iter 190 value 462.723229
## iter 200 value 461.466543
## iter 210 value 461.331080
## final value 461.308100
## stopped after 212 iterations
## INFO [10:30:54.681] [mlr3] Finished benchmark
## INFO [10:30:54.692] [bbotk] Result of batch 6:
## INFO [10:30:54.693] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.693] [bbotk] 6 212 7.319643e-05 7.891372 0 0 0.012
## INFO [10:30:54.693] [bbotk] uhash
## INFO [10:30:54.693] [bbotk] 3e80b976-533f-4424-a736-9d58d75da91f
## INFO [10:30:54.695] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.701] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.704] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 77506.134182
## iter 10 value 2466.219924
## iter 20 value 2226.101058
## iter 30 value 1702.609438
## iter 40 value 926.539687
## iter 50 value 443.624591
## iter 60 value 381.373566
## iter 70 value 361.361526
## iter 80 value 342.100308
## iter 90 value 336.279890
## iter 100 value 331.878901
## iter 110 value 329.900271
## iter 120 value 326.882557
## iter 130 value 314.972193
## iter 140 value 314.711461
## iter 150 value 314.684906
## iter 160 value 314.555896
## iter 170 value 313.965411
## iter 180 value 313.441881
## iter 190 value 312.908298
## iter 200 value 312.862526
## final value 312.862434
## converged
## INFO [10:30:54.712] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 83656.898959
## iter 10 value 2430.672986
## iter 20 value 1617.423121
## iter 30 value 1271.136633
## iter 40 value 1064.877237
## iter 50 value 827.087251
## iter 60 value 674.463684
## iter 70 value 574.663984
## iter 80 value 549.318389
## iter 90 value 532.381620
## iter 100 value 522.204401
## iter 110 value 521.329877
## iter 120 value 519.638052
## iter 130 value 519.433724
## iter 140 value 519.136968
## iter 150 value 515.091606
## iter 160 value 513.661318
## iter 170 value 512.912270
## iter 180 value 512.878930
## iter 190 value 512.815108
## iter 200 value 512.751579
## iter 210 value 512.742455
## iter 220 value 512.742052
## iter 230 value 512.691995
## iter 240 value 512.679649
## iter 250 value 512.672726
## iter 260 value 512.665881
## iter 270 value 512.665371
## final value 512.665159
## stopped after 271 iterations
## INFO [10:30:54.721] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 79859.798733
## iter 10 value 5098.824697
## iter 20 value 1136.656180
## iter 30 value 997.786769
## iter 40 value 921.534783
## iter 50 value 911.531021
## iter 60 value 910.341469
## final value 910.339767
## converged
## INFO [10:30:54.727] [mlr3] Finished benchmark
## INFO [10:30:54.738] [bbotk] Result of batch 7:
## INFO [10:30:54.738] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.738] [bbotk] 4 271 3.390402e-05 10.0576 0 0 0.011
## INFO [10:30:54.738] [bbotk] uhash
## INFO [10:30:54.738] [bbotk] b88b3a73-385c-4e6f-aa43-29b5fb9b6804
## INFO [10:30:54.740] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.747] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.750] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 43
## initial value 84835.858450
## iter 10 value 1760.267174
## iter 20 value 1149.509727
## iter 30 value 904.391641
## iter 40 value 822.544425
## iter 50 value 794.781689
## iter 60 value 787.045574
## iter 70 value 739.662549
## iter 80 value 664.385601
## iter 90 value 652.405219
## iter 100 value 648.317282
## iter 110 value 642.584777
## iter 120 value 609.404471
## iter 130 value 605.552689
## iter 140 value 600.455259
## iter 150 value 555.536131
## iter 160 value 549.555408
## iter 170 value 540.834408
## iter 180 value 538.343950
## iter 190 value 537.377089
## iter 200 value 511.501870
## iter 210 value 449.194755
## iter 220 value 441.122064
## iter 230 value 437.518916
## iter 240 value 436.130247
## iter 250 value 435.898379
## iter 260 value 435.883080
## iter 270 value 435.855367
## iter 280 value 435.743090
## iter 290 value 435.621249
## iter 300 value 435.346367
## iter 310 value 435.189669
## iter 320 value 434.671679
## iter 330 value 427.622144
## iter 340 value 398.387312
## iter 350 value 318.258632
## iter 360 value 287.667892
## iter 370 value 267.142498
## iter 380 value 246.156803
## iter 390 value 234.744399
## iter 400 value 205.816485
## iter 410 value 197.648620
## iter 420 value 197.069255
## iter 430 value 196.829614
## iter 440 value 196.708532
## iter 450 value 195.976368
## iter 460 value 192.229171
## iter 470 value 184.656202
## final value 183.171041
## stopped after 471 iterations
## INFO [10:30:54.762] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 43
## initial value 87982.412500
## iter 10 value 3169.654078
## iter 20 value 1647.376282
## iter 30 value 1276.886923
## iter 40 value 722.051977
## iter 50 value 504.100087
## iter 60 value 428.772214
## iter 70 value 387.319211
## iter 80 value 364.527898
## iter 90 value 351.379484
## iter 100 value 343.185654
## iter 110 value 328.445961
## iter 120 value 322.512540
## iter 130 value 315.053736
## iter 140 value 305.322048
## iter 150 value 298.203611
## iter 160 value 293.759646
## iter 170 value 290.308894
## iter 180 value 289.257815
## iter 190 value 287.915372
## iter 200 value 285.101960
## iter 210 value 284.533212
## iter 220 value 282.378311
## iter 230 value 278.258821
## iter 240 value 275.441472
## iter 250 value 275.075151
## iter 260 value 273.762222
## iter 270 value 271.553246
## iter 280 value 271.063415
## iter 290 value 270.682837
## iter 300 value 270.567257
## iter 310 value 268.454139
## iter 320 value 268.096744
## iter 330 value 268.044729
## iter 340 value 268.022622
## iter 350 value 267.413535
## iter 360 value 256.149605
## iter 370 value 208.726285
## iter 380 value 159.367233
## iter 390 value 133.025773
## iter 400 value 107.275947
## iter 410 value 94.651481
## iter 420 value 91.718828
## iter 430 value 90.097900
## iter 440 value 89.772131
## iter 450 value 89.681237
## iter 460 value 89.387771
## iter 470 value 89.192463
## final value 89.133145
## stopped after 471 iterations
## INFO [10:30:54.778] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 43
## initial value 78930.936925
## iter 10 value 4644.581070
## iter 20 value 851.005652
## iter 30 value 619.704405
## iter 40 value 521.834305
## iter 50 value 448.259318
## iter 60 value 421.995948
## iter 70 value 370.950440
## iter 80 value 336.002583
## iter 90 value 318.888143
## iter 100 value 313.214340
## iter 110 value 298.061126
## iter 120 value 276.287215
## iter 130 value 262.058709
## iter 140 value 255.401270
## iter 150 value 254.795136
## iter 160 value 253.916603
## iter 170 value 253.529125
## iter 180 value 252.903999
## iter 190 value 252.728543
## iter 200 value 251.293172
## iter 210 value 247.710868
## iter 220 value 246.666647
## iter 230 value 246.385595
## iter 240 value 246.182816
## iter 250 value 245.793422
## iter 260 value 245.724857
## iter 270 value 245.720472
## iter 280 value 245.702838
## iter 290 value 245.529923
## iter 300 value 245.339245
## iter 310 value 245.084319
## iter 320 value 245.005886
## iter 330 value 244.898587
## iter 340 value 244.875173
## iter 350 value 244.771963
## iter 360 value 244.767325
## iter 370 value 244.761272
## iter 380 value 244.725678
## iter 390 value 244.672841
## iter 400 value 244.567481
## iter 410 value 244.515082
## iter 420 value 244.336190
## iter 430 value 244.170837
## iter 440 value 243.987044
## iter 450 value 243.915934
## iter 460 value 242.673462
## iter 470 value 202.898370
## final value 200.870767
## stopped after 471 iterations
## INFO [10:30:54.789] [mlr3] Finished benchmark
## INFO [10:30:54.800] [bbotk] Result of batch 8:
## INFO [10:30:54.801] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.801] [bbotk] 6 471 4.253373e-05 11.30139 0 0 0.026
## INFO [10:30:54.801] [bbotk] uhash
## INFO [10:30:54.801] [bbotk] 5a8d2717-36bb-4ef6-826b-a70cb299e18b
## INFO [10:30:54.803] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.809] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.812] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 36
## initial value 83231.426531
## iter 10 value 3979.158592
## iter 20 value 1320.123711
## iter 30 value 597.584550
## iter 40 value 414.092222
## iter 50 value 327.126434
## final value 290.058899
## stopped after 59 iterations
## INFO [10:30:54.819] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 36
## initial value 86763.710555
## iter 10 value 8472.675855
## iter 20 value 2755.285181
## iter 30 value 1791.841196
## iter 40 value 1449.644821
## iter 50 value 1363.208675
## final value 1349.345023
## stopped after 59 iterations
## INFO [10:30:54.826] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 36
## initial value 74499.664153
## iter 10 value 6057.578748
## iter 20 value 991.824993
## iter 30 value 892.314122
## iter 40 value 771.519110
## iter 50 value 720.659145
## final value 708.317786
## stopped after 59 iterations
## INFO [10:30:54.832] [mlr3] Finished benchmark
## INFO [10:30:54.843] [bbotk] Result of batch 9:
## INFO [10:30:54.844] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.844] [bbotk] 5 59 4.82801e-05 9.175178 0 0 0.008
## INFO [10:30:54.844] [bbotk] uhash
## INFO [10:30:54.844] [bbotk] 56c4372a-c949-42c7-a8c5-b9f892ed56ea
## INFO [10:30:54.845] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.852] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.855] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 36
## initial value 82577.474321
## iter 10 value 4894.358563
## iter 20 value 1478.542899
## iter 30 value 887.050034
## iter 40 value 768.871271
## iter 50 value 666.962241
## iter 60 value 639.049833
## iter 70 value 631.143283
## iter 80 value 630.985783
## final value 630.967122
## stopped after 84 iterations
## INFO [10:30:54.862] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 36
## initial value 83899.269887
## final value 8474.654362
## converged
## INFO [10:30:54.868] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 36
## initial value 79712.738025
## iter 10 value 1475.510608
## iter 20 value 922.721764
## iter 30 value 768.081063
## iter 40 value 597.660827
## iter 50 value 533.255736
## iter 60 value 499.387735
## iter 70 value 403.385110
## iter 80 value 389.664131
## final value 386.364127
## stopped after 84 iterations
## INFO [10:30:54.875] [mlr3] Finished benchmark
## INFO [10:30:54.889] [bbotk] Result of batch 10:
## INFO [10:30:54.890] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.890] [bbotk] 5 84 3.118007e-05 11.15122 0 0 0.007
## INFO [10:30:54.890] [bbotk] uhash
## INFO [10:30:54.890] [bbotk] 83d76e0e-2815-4474-999d-fc9ad06825f4
## INFO [10:30:54.892] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.899] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.901] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 76195.736417
## iter 10 value 1375.016213
## iter 20 value 495.265946
## iter 30 value 365.010817
## iter 40 value 294.615235
## iter 50 value 245.534913
## iter 60 value 178.360589
## iter 70 value 145.587360
## iter 80 value 115.378928
## iter 90 value 74.505312
## iter 100 value 45.016758
## iter 110 value 31.367774
## iter 120 value 23.298761
## iter 130 value 17.009215
## iter 140 value 15.485086
## iter 150 value 12.375692
## iter 160 value 6.770308
## iter 170 value 4.924783
## iter 180 value 3.809487
## iter 190 value 2.915429
## iter 200 value 2.503239
## iter 210 value 2.398052
## iter 220 value 2.325077
## iter 230 value 2.119926
## iter 240 value 1.966610
## iter 250 value 1.734394
## iter 260 value 1.625711
## iter 270 value 1.617086
## iter 280 value 1.581797
## iter 290 value 1.558577
## iter 300 value 1.519108
## iter 310 value 1.478588
## iter 320 value 1.428759
## iter 330 value 1.305338
## iter 340 value 1.150853
## iter 350 value 1.092090
## iter 360 value 1.007639
## iter 370 value 0.975896
## iter 380 value 0.945167
## iter 390 value 0.933111
## final value 0.933066
## stopped after 391 iterations
## INFO [10:30:54.915] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 84500.497247
## iter 10 value 2639.527973
## iter 20 value 1825.953180
## iter 30 value 1321.557407
## iter 40 value 1271.017576
## iter 50 value 1200.738137
## iter 60 value 1028.962864
## iter 70 value 971.505855
## iter 80 value 926.721259
## iter 90 value 758.171380
## iter 100 value 715.983690
## iter 110 value 671.917753
## iter 120 value 627.757806
## iter 130 value 568.374696
## iter 140 value 555.059470
## iter 150 value 550.776204
## iter 160 value 547.063789
## iter 170 value 545.806368
## iter 180 value 540.846719
## iter 190 value 489.524887
## iter 200 value 326.424590
## iter 210 value 303.300762
## iter 220 value 291.217240
## iter 230 value 286.072223
## iter 240 value 282.724592
## iter 250 value 271.638667
## iter 260 value 239.116584
## iter 270 value 226.638155
## iter 280 value 225.435042
## iter 290 value 213.289026
## iter 300 value 210.065891
## iter 310 value 208.119419
## iter 320 value 206.913695
## iter 330 value 205.637300
## iter 340 value 204.858076
## iter 350 value 200.660840
## iter 360 value 191.073259
## iter 370 value 174.320846
## iter 380 value 144.279764
## iter 390 value 125.012247
## final value 122.868110
## stopped after 391 iterations
## INFO [10:30:54.928] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 81770.380294
## iter 10 value 4704.729275
## iter 20 value 939.319913
## iter 30 value 731.520698
## iter 40 value 653.298926
## iter 50 value 644.593921
## iter 60 value 538.758502
## iter 70 value 433.292992
## iter 80 value 379.960497
## iter 90 value 368.497172
## iter 100 value 337.019635
## iter 110 value 257.703407
## iter 120 value 221.355669
## iter 130 value 181.812834
## iter 140 value 152.148240
## iter 150 value 149.195050
## iter 160 value 149.148763
## iter 170 value 148.908511
## iter 180 value 148.220237
## iter 190 value 148.168527
## iter 200 value 148.112463
## iter 210 value 148.091856
## iter 220 value 148.080934
## iter 230 value 147.919925
## iter 240 value 147.822049
## iter 250 value 145.182680
## iter 260 value 140.664862
## iter 270 value 137.173614
## iter 280 value 135.705934
## iter 290 value 131.893152
## iter 300 value 130.435546
## iter 310 value 130.027248
## iter 320 value 129.590323
## iter 330 value 129.058699
## iter 340 value 128.610453
## iter 350 value 127.983540
## iter 360 value 127.959774
## iter 370 value 127.958408
## iter 380 value 127.953517
## iter 390 value 127.948475
## final value 127.947398
## stopped after 391 iterations
## INFO [10:30:54.941] [mlr3] Finished benchmark
## INFO [10:30:54.952] [bbotk] Result of batch 11:
## INFO [10:30:54.953] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:54.953] [bbotk] 9 391 4.517636e-05 22.30202 0 0 0.027
## INFO [10:30:54.953] [bbotk] uhash
## INFO [10:30:54.953] [bbotk] 9c2be935-936f-427a-a3e8-39d3bf6c548b
## INFO [10:30:54.954] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:54.961] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:54.964] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 43
## initial value 77911.391652
## iter 10 value 4429.906774
## iter 20 value 1841.116029
## iter 30 value 1002.798414
## iter 40 value 818.097946
## iter 50 value 764.709061
## iter 60 value 712.548874
## iter 70 value 615.517337
## iter 80 value 541.536114
## iter 90 value 521.131548
## iter 100 value 497.317785
## iter 110 value 494.300753
## iter 120 value 492.867281
## iter 130 value 487.690988
## iter 140 value 473.347854
## iter 150 value 472.714329
## iter 160 value 471.468991
## iter 170 value 471.272398
## iter 180 value 471.048846
## iter 190 value 470.887617
## iter 200 value 470.880639
## iter 210 value 468.991513
## iter 220 value 464.229231
## iter 230 value 419.160165
## iter 240 value 380.904877
## iter 250 value 329.137872
## iter 260 value 292.986400
## iter 270 value 259.844266
## iter 280 value 236.430357
## iter 290 value 224.758904
## iter 300 value 223.827523
## iter 310 value 223.786502
## iter 320 value 223.274278
## iter 330 value 221.540213
## iter 340 value 220.653680
## iter 350 value 220.310450
## iter 360 value 218.973831
## iter 370 value 218.758212
## final value 218.746017
## stopped after 378 iterations
## INFO [10:30:54.976] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 43
## initial value 89523.216558
## iter 10 value 1542.583264
## iter 20 value 1051.072270
## iter 30 value 981.119072
## iter 40 value 961.446017
## iter 50 value 803.066585
## iter 60 value 619.038971
## iter 70 value 500.229731
## iter 80 value 481.031187
## iter 90 value 477.121109
## iter 100 value 473.911927
## iter 110 value 473.043138
## iter 120 value 472.365957
## iter 130 value 472.277266
## iter 140 value 472.200467
## iter 150 value 471.965457
## iter 160 value 471.690825
## iter 170 value 471.677003
## iter 180 value 471.669626
## iter 190 value 471.602299
## iter 200 value 464.182763
## iter 210 value 357.740595
## iter 220 value 283.849536
## iter 230 value 213.273406
## iter 240 value 159.967936
## iter 250 value 109.858097
## iter 260 value 97.666771
## iter 270 value 96.249384
## iter 280 value 93.715069
## iter 290 value 91.013134
## iter 300 value 88.616045
## iter 310 value 88.248245
## iter 320 value 87.167478
## iter 330 value 77.632441
## iter 340 value 54.903981
## iter 350 value 41.381081
## iter 360 value 37.426987
## iter 370 value 36.215952
## final value 35.455886
## stopped after 378 iterations
## INFO [10:30:54.987] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 43
## initial value 76334.191224
## iter 10 value 1276.702279
## iter 20 value 460.237556
## iter 30 value 434.715992
## iter 40 value 420.500207
## iter 50 value 294.497536
## iter 60 value 260.577008
## iter 70 value 229.523399
## iter 80 value 221.863192
## iter 90 value 220.169640
## iter 100 value 218.050586
## iter 110 value 216.530700
## iter 120 value 213.871206
## iter 130 value 212.934265
## iter 140 value 212.621644
## iter 150 value 211.271047
## iter 160 value 211.032589
## iter 170 value 210.177956
## iter 180 value 204.553420
## iter 190 value 185.522216
## iter 200 value 141.068661
## iter 210 value 125.210471
## iter 220 value 123.869589
## iter 230 value 120.999032
## iter 240 value 118.947776
## iter 250 value 118.123953
## iter 260 value 117.943214
## iter 270 value 117.692095
## iter 280 value 117.315308
## iter 290 value 116.618167
## iter 300 value 115.952922
## iter 310 value 114.877458
## iter 320 value 114.083419
## iter 330 value 113.969600
## iter 340 value 113.933643
## iter 350 value 113.930809
## iter 360 value 113.919843
## iter 370 value 113.768822
## final value 113.073720
## stopped after 378 iterations
## INFO [10:30:54.997] [mlr3] Finished benchmark
## INFO [10:30:55.011] [bbotk] Result of batch 12:
## INFO [10:30:55.012] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.012] [bbotk] 6 378 8.757184e-05 17.30878 0 0 0.02
## INFO [10:30:55.012] [bbotk] uhash
## INFO [10:30:55.012] [bbotk] b4b9967a-4f26-4cec-8781-b57837236432
## INFO [10:30:55.014] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.021] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.023] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 43
## initial value 81260.705248
## iter 10 value 5906.886193
## iter 20 value 1577.526413
## iter 30 value 946.081944
## iter 40 value 699.806554
## iter 50 value 527.286941
## iter 60 value 499.640462
## iter 70 value 441.097593
## iter 80 value 377.211476
## iter 90 value 356.659671
## iter 100 value 342.544418
## iter 110 value 341.621670
## iter 120 value 341.556700
## iter 130 value 331.141566
## iter 140 value 289.657100
## iter 150 value 281.737069
## iter 160 value 245.719073
## iter 170 value 231.210898
## iter 180 value 228.844066
## iter 190 value 225.519426
## iter 200 value 224.440070
## iter 210 value 224.364064
## iter 220 value 224.267843
## iter 230 value 224.177498
## iter 240 value 224.175089
## iter 250 value 224.172223
## iter 260 value 224.068859
## iter 270 value 224.008983
## iter 280 value 223.921324
## iter 290 value 223.901631
## iter 300 value 223.879757
## iter 310 value 223.833277
## final value 223.832520
## converged
## INFO [10:30:55.034] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 43
## initial value 86110.491632
## iter 10 value 8474.572548
## iter 20 value 3607.563576
## iter 30 value 2607.403671
## iter 40 value 1859.031436
## iter 50 value 1444.472327
## iter 60 value 1370.280893
## iter 70 value 1347.790515
## iter 80 value 1344.392177
## iter 90 value 1343.661492
## iter 100 value 1343.591759
## iter 110 value 1343.252512
## iter 110 value 1343.252510
## iter 110 value 1343.252510
## final value 1343.252510
## converged
## INFO [10:30:55.041] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 43
## initial value 79766.328069
## iter 10 value 1232.547620
## iter 20 value 910.763519
## iter 30 value 910.193379
## iter 40 value 910.189810
## iter 40 value 910.189809
## iter 40 value 910.189809
## final value 910.189809
## converged
## INFO [10:30:55.047] [mlr3] Finished benchmark
## INFO [10:30:55.058] [bbotk] Result of batch 13:
## INFO [10:30:55.059] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.059] [bbotk] 6 372 1.271797e-05 7.792831 0 0 0.011
## INFO [10:30:55.059] [bbotk] uhash
## INFO [10:30:55.059] [bbotk] 137eaf7c-0784-4a1f-9477-37de0d9e0381
## INFO [10:30:55.061] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.067] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.070] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 79204.852731
## iter 10 value 2461.524063
## iter 20 value 1985.258439
## iter 30 value 1607.138782
## iter 40 value 1452.884945
## iter 50 value 1442.983168
## iter 60 value 1441.965745
## iter 70 value 1413.411544
## iter 80 value 1043.220770
## iter 90 value 851.568961
## iter 100 value 748.106399
## iter 110 value 743.698088
## iter 120 value 734.439051
## iter 130 value 700.481035
## iter 140 value 686.117554
## iter 150 value 685.390330
## iter 160 value 684.567549
## iter 170 value 683.400913
## iter 180 value 681.726234
## iter 190 value 675.251628
## iter 200 value 670.590883
## iter 210 value 647.171131
## iter 220 value 588.363726
## iter 230 value 520.655860
## iter 240 value 443.393227
## iter 250 value 430.978631
## iter 260 value 412.187364
## iter 270 value 405.151808
## iter 280 value 404.021906
## iter 290 value 402.943274
## iter 300 value 399.540034
## iter 310 value 372.711079
## iter 320 value 307.611781
## iter 330 value 275.928248
## iter 340 value 272.456371
## iter 350 value 271.922522
## iter 360 value 271.827264
## iter 370 value 271.780382
## iter 380 value 271.716247
## iter 390 value 271.259169
## iter 400 value 271.094240
## iter 410 value 271.092763
## final value 271.092688
## converged
## INFO [10:30:55.080] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 86385.375653
## iter 10 value 7699.696507
## iter 20 value 2851.432208
## iter 30 value 2730.464990
## iter 40 value 2728.925382
## iter 50 value 2724.005543
## iter 60 value 2513.849994
## iter 70 value 2095.197456
## iter 80 value 1545.153696
## iter 90 value 1380.847883
## iter 100 value 1353.809208
## iter 110 value 1346.278930
## iter 120 value 1345.608287
## iter 130 value 1345.585211
## iter 140 value 1344.755573
## iter 150 value 1344.448135
## iter 160 value 1344.345258
## iter 170 value 1344.342209
## iter 180 value 1344.284304
## final value 1344.284264
## converged
## INFO [10:30:55.088] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 78116.872071
## iter 10 value 7044.528830
## iter 20 value 5442.584869
## iter 30 value 1895.754916
## iter 40 value 1445.022665
## iter 50 value 1440.654782
## iter 60 value 1408.326029
## iter 70 value 1129.217262
## iter 80 value 958.427046
## iter 90 value 915.054936
## iter 100 value 911.099487
## iter 110 value 910.782665
## iter 120 value 910.552420
## iter 130 value 909.053520
## iter 140 value 711.594856
## iter 150 value 642.916605
## iter 160 value 638.167502
## iter 170 value 612.329986
## iter 180 value 576.519187
## iter 190 value 569.964775
## iter 200 value 565.211022
## iter 210 value 565.132487
## iter 220 value 565.126209
## iter 230 value 565.096220
## iter 240 value 565.074551
## iter 250 value 565.038770
## iter 260 value 564.746762
## iter 270 value 564.033429
## iter 280 value 544.809972
## iter 290 value 518.103841
## iter 300 value 489.309180
## iter 310 value 464.548283
## iter 320 value 457.785870
## iter 330 value 454.760747
## iter 340 value 454.085122
## iter 350 value 453.912181
## iter 360 value 453.678754
## iter 370 value 453.620748
## iter 380 value 453.359633
## iter 390 value 453.152380
## iter 400 value 453.117571
## final value 453.117249
## converged
## INFO [10:30:55.097] [mlr3] Finished benchmark
## INFO [10:30:55.111] [bbotk] Result of batch 14:
## INFO [10:30:55.112] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.112] [bbotk] 4 457 3.549095e-05 7.445906 0 0 0.016
## INFO [10:30:55.112] [bbotk] uhash
## INFO [10:30:55.112] [bbotk] e3c74e30-820d-4f90-b033-9c12d3f09a08
## INFO [10:30:55.114] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.121] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.123] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 80900.597314
## iter 10 value 943.562868
## iter 20 value 585.391323
## iter 30 value 400.462138
## iter 40 value 315.167001
## iter 50 value 281.470987
## iter 60 value 226.722203
## iter 70 value 173.849290
## iter 80 value 150.901442
## iter 90 value 143.093727
## iter 100 value 138.570155
## iter 110 value 136.526795
## final value 134.974445
## stopped after 117 iterations
## INFO [10:30:55.132] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 90330.703479
## iter 10 value 3182.169946
## iter 20 value 1046.902601
## iter 30 value 554.035582
## iter 40 value 383.421295
## iter 50 value 351.068897
## iter 60 value 347.801113
## iter 70 value 345.853999
## iter 80 value 345.172000
## iter 90 value 344.463904
## iter 100 value 344.261032
## iter 110 value 344.137444
## final value 344.068279
## stopped after 117 iterations
## INFO [10:30:55.140] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 76871.563063
## iter 10 value 1027.475845
## iter 20 value 577.816513
## iter 30 value 314.186585
## iter 40 value 219.180489
## iter 50 value 136.082838
## iter 60 value 112.875874
## iter 70 value 72.743921
## iter 80 value 53.962282
## iter 90 value 36.925948
## iter 100 value 30.372678
## iter 110 value 28.102247
## final value 24.266769
## stopped after 117 iterations
## INFO [10:30:55.147] [mlr3] Finished benchmark
## INFO [10:30:55.158] [bbotk] Result of batch 15:
## INFO [10:30:55.159] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.159] [bbotk] 8 117 8.89469e-05 9.050975 0 0 0.01
## INFO [10:30:55.159] [bbotk] uhash
## INFO [10:30:55.159] [bbotk] 868ec8d2-7223-4053-89c2-c1de869a7dc9
## INFO [10:30:55.161] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.168] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.170] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 78984.253109
## iter 10 value 9739.708045
## iter 20 value 2876.168509
## iter 30 value 1993.813738
## iter 40 value 1758.655331
## iter 50 value 1517.360918
## iter 60 value 1459.170943
## iter 70 value 1447.422596
## iter 80 value 1443.138857
## iter 90 value 1442.713199
## final value 1442.703130
## converged
## INFO [10:30:55.177] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 82759.379700
## iter 10 value 5537.119070
## iter 20 value 3855.138819
## iter 30 value 3324.660963
## iter 40 value 2508.264145
## iter 50 value 2202.638917
## iter 60 value 1666.276154
## iter 70 value 1422.804156
## iter 80 value 1370.030413
## iter 90 value 1350.304396
## iter 100 value 1347.254991
## iter 110 value 1345.533305
## iter 120 value 1345.351921
## iter 130 value 1344.199857
## iter 140 value 1344.056127
## iter 150 value 1343.903202
## iter 160 value 1343.716960
## iter 170 value 1343.684735
## final value 1343.684706
## converged
## INFO [10:30:55.184] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 76081.178490
## final value 7044.117188
## converged
## INFO [10:30:55.190] [mlr3] Finished benchmark
## INFO [10:30:55.201] [bbotk] Result of batch 16:
## INFO [10:30:55.202] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.202] [bbotk] 1 271 2.278679e-05 9.569035 0 0 0.006
## INFO [10:30:55.202] [bbotk] uhash
## INFO [10:30:55.202] [bbotk] 47e4a025-d9c8-4cd5-8e9c-db2ca50dedb0
## INFO [10:30:55.203] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.213] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.216] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 22
## initial value 81616.149688
## iter 10 value 2053.812555
## iter 20 value 891.294935
## iter 30 value 608.069587
## iter 40 value 517.417936
## iter 50 value 449.456534
## iter 60 value 347.360586
## iter 70 value 275.214610
## iter 80 value 214.404274
## iter 90 value 170.955256
## iter 100 value 169.291875
## iter 110 value 162.902679
## iter 120 value 160.617582
## iter 130 value 157.345552
## iter 140 value 157.315461
## iter 150 value 157.312246
## iter 160 value 156.915327
## iter 170 value 156.388312
## iter 180 value 156.309175
## iter 190 value 156.305295
## iter 200 value 156.300284
## iter 210 value 156.238012
## iter 220 value 156.235115
## iter 230 value 156.229462
## iter 240 value 156.229275
## final value 156.229275
## stopped after 240 iterations
## INFO [10:30:55.225] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 22
## initial value 82502.969812
## iter 10 value 3032.345520
## iter 20 value 1200.893280
## iter 30 value 995.317008
## iter 40 value 902.241196
## iter 50 value 724.396019
## iter 60 value 573.072194
## iter 70 value 519.714684
## iter 80 value 479.079170
## iter 90 value 415.666149
## iter 100 value 405.264393
## iter 110 value 395.497334
## iter 120 value 388.138750
## iter 130 value 386.708896
## iter 140 value 386.561303
## iter 150 value 386.158662
## iter 160 value 386.101559
## final value 386.101547
## converged
## INFO [10:30:55.232] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 22
## initial value 82293.388596
## iter 10 value 1242.852718
## iter 20 value 843.800111
## iter 30 value 590.772954
## iter 40 value 421.618805
## iter 50 value 375.757387
## iter 60 value 333.092006
## iter 70 value 307.725906
## iter 80 value 295.386092
## iter 90 value 273.920420
## iter 100 value 270.694664
## iter 110 value 270.247445
## iter 120 value 270.193633
## iter 130 value 270.137093
## iter 140 value 270.079482
## iter 150 value 270.033087
## final value 270.031839
## converged
## INFO [10:30:55.239] [mlr3] Finished benchmark
## INFO [10:30:55.250] [bbotk] Result of batch 17:
## INFO [10:30:55.251] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.251] [bbotk] 3 240 6.485391e-05 11.66431 0 0 0.01
## INFO [10:30:55.251] [bbotk] uhash
## INFO [10:30:55.251] [bbotk] 7c7f1fed-c7c3-43a5-b54d-f9a0f686db6c
## INFO [10:30:55.252] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.259] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.262] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 79189.966558
## iter 10 value 3058.887013
## iter 20 value 2679.471446
## iter 30 value 2591.359216
## iter 40 value 2443.191372
## iter 50 value 2190.054141
## iter 60 value 1554.311598
## iter 70 value 1477.395723
## iter 80 value 1446.454234
## iter 90 value 1443.659721
## iter 100 value 1442.669688
## iter 110 value 1442.630653
## final value 1442.630501
## converged
## INFO [10:30:55.269] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 86105.298045
## iter 10 value 3214.968411
## iter 20 value 3118.378899
## iter 30 value 2883.468467
## final value 2881.943004
## converged
## INFO [10:30:55.275] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 76213.764248
## iter 10 value 2207.005840
## iter 20 value 995.533438
## iter 30 value 934.438358
## iter 40 value 915.534022
## iter 50 value 910.289493
## iter 60 value 910.269006
## final value 910.267203
## converged
## INFO [10:30:55.281] [mlr3] Finished benchmark
## INFO [10:30:55.292] [bbotk] Result of batch 18:
## INFO [10:30:55.293] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.293] [bbotk] 1 404 4.320416e-05 9.230552 0 0 0.007
## INFO [10:30:55.293] [bbotk] uhash
## INFO [10:30:55.293] [bbotk] d801814d-357e-47dc-b76f-4ce37be5beca
## INFO [10:30:55.294] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.301] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.304] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 80745.581553
## final value 9739.911094
## converged
## INFO [10:30:55.314] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 86404.428851
## iter 10 value 3982.546485
## iter 20 value 2297.195712
## iter 30 value 1809.005564
## iter 40 value 1531.930726
## iter 50 value 1384.082206
## iter 60 value 1364.535127
## iter 70 value 1349.021056
## iter 80 value 1348.415226
## iter 90 value 1346.786974
## iter 100 value 1346.671041
## iter 110 value 1346.384736
## iter 120 value 1346.123430
## iter 130 value 1346.054806
## iter 140 value 1346.027877
## final value 1346.026406
## converged
## INFO [10:30:55.321] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 77238.399733
## final value 7044.173433
## converged
## INFO [10:30:55.326] [mlr3] Finished benchmark
## INFO [10:30:55.337] [bbotk] Result of batch 19:
## INFO [10:30:55.338] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.338] [bbotk] 1 431 7.060476e-05 11.59058 0 0 0.007
## INFO [10:30:55.338] [bbotk] uhash
## INFO [10:30:55.338] [bbotk] 3c5947ff-75c4-4d6a-82ce-dd2871ba4f93
## INFO [10:30:55.340] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.347] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.349] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 78568.878896
## iter 10 value 2575.897669
## iter 20 value 854.995874
## iter 30 value 582.694022
## iter 40 value 518.488338
## iter 50 value 456.816077
## iter 60 value 417.877936
## final value 417.505685
## stopped after 69 iterations
## INFO [10:30:55.357] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 88128.458607
## iter 10 value 3076.773867
## iter 20 value 915.937089
## iter 30 value 596.917217
## iter 40 value 579.472101
## iter 50 value 543.192322
## iter 60 value 487.512220
## final value 482.979961
## stopped after 69 iterations
## INFO [10:30:55.364] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 75976.139310
## iter 10 value 4319.403000
## iter 20 value 1117.509861
## iter 30 value 978.477132
## iter 40 value 916.014660
## iter 50 value 910.841597
## iter 60 value 910.619797
## final value 909.365983
## stopped after 69 iterations
## INFO [10:30:55.370] [mlr3] Finished benchmark
## INFO [10:30:55.381] [bbotk] Result of batch 20:
## INFO [10:30:55.382] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.382] [bbotk] 4 69 8.809209e-05 7.999984 0 0 0.008
## INFO [10:30:55.382] [bbotk] uhash
## INFO [10:30:55.382] [bbotk] 349043ff-bf1f-4543-b355-31a684c3f604
## INFO [10:30:55.385] [bbotk] Finished optimizing after 20 evaluation(s)
## INFO [10:30:55.385] [bbotk] Result:
## INFO [10:30:55.385] [bbotk] size maxit decay learner_param_vals x_domain regr.rmse
## INFO [10:30:55.385] [bbotk] 4 457 3.549095e-05 <list[3]> <list[3]> 7.445906
## # weights: 29
## initial value 123513.830574
## iter 10 value 7320.399062
## iter 20 value 2949.336828
## iter 30 value 2776.809584
## iter 40 value 2351.374207
## iter 50 value 2106.205582
## iter 60 value 2068.044925
## iter 70 value 2065.849906
## iter 80 value 2061.401113
## iter 90 value 2061.127702
## final value 2061.127572
## converged
## INFO [10:30:55.399] [mlr3] Applying learner 'regr.nnet.tuned' on task 'cereal' (iter 3/5)
## INFO [10:30:55.458] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorEvals> [n_evals=20, k=0]'
## INFO [10:30:55.464] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.471] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.474] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 85565.891525
## iter 10 value 3464.939840
## iter 20 value 2912.134019
## iter 30 value 2599.609432
## iter 40 value 1970.667667
## iter 50 value 1331.843152
## iter 60 value 1223.435188
## iter 70 value 1206.460940
## iter 80 value 1188.165636
## iter 90 value 1187.380360
## iter 100 value 1185.091267
## iter 110 value 1184.991268
## final value 1184.797888
## converged
## INFO [10:30:55.481] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 85269.799950
## final value 9441.535143
## converged
## INFO [10:30:55.487] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 89732.717899
## iter 10 value 6602.090454
## iter 20 value 3842.028348
## iter 30 value 2089.189763
## iter 40 value 2080.045155
## iter 50 value 2066.998663
## iter 60 value 2049.019808
## iter 70 value 2042.852574
## iter 80 value 1962.715686
## iter 90 value 1897.304048
## iter 100 value 1894.394482
## final value 1894.314453
## converged
## INFO [10:30:55.493] [mlr3] Finished benchmark
## INFO [10:30:55.503] [bbotk] Result of batch 1:
## INFO [10:30:55.504] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.504] [bbotk] 1 326 6.290984e-05 9.705129 0 0 0.007
## INFO [10:30:55.504] [bbotk] uhash
## INFO [10:30:55.504] [bbotk] a10275e3-e5f7-4687-8090-e0db9f721ab4
## INFO [10:30:55.506] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.513] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.515] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 82250.251960
## final value 7932.697127
## converged
## INFO [10:30:55.522] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 89374.416854
## iter 10 value 2172.218649
## iter 20 value 1361.696072
## iter 30 value 591.453999
## iter 40 value 514.170205
## iter 50 value 486.797070
## iter 60 value 456.447815
## iter 70 value 455.233784
## iter 80 value 452.857829
## iter 90 value 451.753317
## iter 100 value 451.308556
## iter 110 value 451.147310
## iter 120 value 451.059950
## iter 130 value 450.929581
## iter 140 value 450.891323
## iter 150 value 450.840636
## iter 160 value 450.818028
## iter 170 value 450.806080
## iter 180 value 450.788427
## iter 190 value 450.767313
## final value 450.761982
## converged
## INFO [10:30:55.530] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 89363.168206
## iter 10 value 2323.919981
## iter 20 value 1072.978372
## iter 30 value 756.216071
## iter 40 value 697.730068
## iter 50 value 678.550690
## iter 60 value 667.989172
## iter 70 value 660.390243
## iter 80 value 651.493089
## iter 90 value 646.359516
## iter 100 value 645.860342
## iter 110 value 645.802788
## iter 120 value 645.575318
## final value 645.503914
## converged
## INFO [10:30:55.537] [mlr3] Finished benchmark
## INFO [10:30:55.548] [bbotk] Result of batch 2:
## INFO [10:30:55.549] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.549] [bbotk] 2 403 8.831228e-05 8.311261 0 0 0.007
## INFO [10:30:55.549] [bbotk] uhash
## INFO [10:30:55.549] [bbotk] e62fcfc7-6e36-4a5d-a1ce-259c22255687
## INFO [10:30:55.551] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.564] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.567] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 85804.276518
## iter 10 value 972.254000
## iter 20 value 596.037877
## iter 30 value 494.863419
## iter 40 value 438.754458
## iter 50 value 375.960935
## iter 60 value 320.624589
## iter 70 value 232.759092
## iter 80 value 188.061199
## iter 90 value 164.258548
## iter 100 value 146.494482
## iter 110 value 134.686465
## iter 120 value 110.170231
## iter 130 value 105.222917
## iter 140 value 103.181599
## iter 150 value 97.305654
## iter 160 value 88.427416
## iter 170 value 78.752997
## iter 180 value 76.008779
## iter 190 value 75.609383
## iter 200 value 75.329296
## iter 210 value 74.838636
## iter 220 value 74.690956
## iter 230 value 74.532674
## iter 240 value 74.386847
## iter 250 value 74.362004
## iter 260 value 74.141934
## iter 270 value 73.329439
## iter 280 value 69.948368
## iter 290 value 68.817074
## iter 300 value 67.747730
## final value 67.360497
## stopped after 303 iterations
## INFO [10:30:55.579] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 87518.850153
## iter 10 value 4592.582299
## iter 20 value 1478.708015
## iter 30 value 862.083148
## iter 40 value 580.391857
## iter 50 value 444.919250
## iter 60 value 411.576004
## iter 70 value 377.321168
## iter 80 value 352.832400
## iter 90 value 345.995947
## iter 100 value 344.546025
## iter 110 value 324.414152
## iter 120 value 310.807679
## iter 130 value 308.711641
## iter 140 value 308.501128
## iter 150 value 307.943218
## iter 160 value 307.060479
## iter 170 value 305.123364
## iter 180 value 267.797548
## iter 190 value 209.981385
## iter 200 value 195.425053
## iter 210 value 183.247033
## iter 220 value 179.191554
## iter 230 value 177.933756
## iter 240 value 172.655413
## iter 250 value 149.550795
## iter 260 value 133.745943
## iter 270 value 119.446171
## iter 280 value 118.341032
## iter 290 value 116.678440
## iter 300 value 115.962973
## final value 115.162903
## stopped after 303 iterations
## INFO [10:30:55.590] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 87404.008540
## iter 10 value 2098.521375
## iter 20 value 1501.467333
## iter 30 value 1152.414678
## iter 40 value 1033.547579
## iter 50 value 929.824650
## iter 60 value 911.291453
## iter 70 value 892.585311
## iter 80 value 699.990691
## iter 90 value 619.445839
## iter 100 value 576.637757
## iter 110 value 474.578174
## iter 120 value 417.385257
## iter 130 value 383.503002
## iter 140 value 373.405579
## iter 150 value 371.547659
## iter 160 value 370.406781
## iter 170 value 370.016217
## iter 180 value 369.066754
## iter 190 value 368.114659
## iter 200 value 366.807825
## iter 210 value 366.644036
## iter 220 value 366.419713
## iter 230 value 366.006670
## iter 240 value 365.766471
## iter 250 value 365.703369
## iter 260 value 365.511046
## iter 270 value 365.421134
## iter 280 value 365.377944
## iter 290 value 365.273428
## iter 300 value 365.235460
## final value 365.232232
## stopped after 303 iterations
## INFO [10:30:55.601] [mlr3] Finished benchmark
## INFO [10:30:55.612] [bbotk] Result of batch 3:
## INFO [10:30:55.613] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.613] [bbotk] 8 303 4.388317e-05 10.43645 0 0 0.019
## INFO [10:30:55.613] [bbotk] uhash
## INFO [10:30:55.613] [bbotk] 93a9623d-8fa3-44f0-841f-c4472783c88e
## INFO [10:30:55.614] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.621] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.624] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 83316.048971
## iter 10 value 3011.310230
## iter 20 value 1326.259197
## iter 30 value 771.202060
## iter 40 value 547.108935
## iter 50 value 455.848349
## iter 60 value 404.652152
## iter 70 value 390.094163
## iter 80 value 371.591260
## iter 90 value 354.110288
## iter 100 value 350.705731
## iter 110 value 343.894121
## iter 120 value 342.466020
## iter 130 value 339.967876
## iter 140 value 327.867018
## iter 150 value 287.144464
## iter 160 value 110.881911
## iter 170 value 75.410415
## iter 180 value 67.668182
## iter 190 value 61.648176
## iter 200 value 60.301921
## iter 210 value 59.253329
## iter 220 value 58.670885
## iter 230 value 58.427473
## iter 240 value 58.004557
## iter 250 value 57.934346
## iter 260 value 57.415116
## iter 270 value 56.632127
## iter 280 value 51.631946
## iter 290 value 41.754224
## iter 300 value 38.507302
## iter 310 value 36.780264
## iter 320 value 36.245176
## iter 330 value 35.837181
## iter 340 value 35.494952
## iter 350 value 35.401392
## iter 360 value 35.155489
## iter 370 value 34.019753
## iter 380 value 26.850435
## iter 390 value 25.034137
## iter 400 value 24.017622
## iter 410 value 22.570641
## final value 21.766132
## stopped after 419 iterations
## INFO [10:30:55.637] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 85465.507940
## final value 9442.456618
## converged
## INFO [10:30:55.644] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 87904.500788
## iter 10 value 6602.430689
## iter 20 value 2275.993474
## iter 30 value 2173.887544
## iter 40 value 2007.805378
## iter 50 value 2007.392062
## iter 60 value 2006.255562
## iter 70 value 2005.656753
## iter 80 value 1477.563099
## iter 90 value 1143.023921
## iter 100 value 1074.772408
## iter 110 value 1013.657261
## iter 120 value 737.269918
## iter 130 value 596.409041
## iter 140 value 580.302605
## iter 150 value 573.710740
## iter 160 value 564.526723
## iter 170 value 533.814270
## iter 180 value 398.966706
## iter 190 value 388.979834
## iter 200 value 387.276224
## iter 210 value 386.564312
## iter 220 value 385.387271
## iter 230 value 376.039880
## iter 240 value 348.237592
## iter 250 value 281.506966
## iter 260 value 229.095709
## iter 270 value 191.796695
## iter 280 value 173.215281
## iter 290 value 159.954504
## iter 300 value 138.192976
## iter 310 value 126.135363
## iter 320 value 117.820088
## iter 330 value 112.107218
## iter 340 value 109.023787
## iter 350 value 105.041773
## iter 360 value 98.253592
## iter 370 value 91.256658
## iter 380 value 86.795283
## iter 390 value 85.655044
## iter 400 value 84.181472
## iter 410 value 83.219768
## final value 80.788466
## stopped after 419 iterations
## INFO [10:30:55.656] [mlr3] Finished benchmark
## INFO [10:30:55.667] [bbotk] Result of batch 4:
## INFO [10:30:55.668] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.668] [bbotk] 7 419 6.328378e-05 12.84977 0 0 0.019
## INFO [10:30:55.668] [bbotk] uhash
## INFO [10:30:55.668] [bbotk] ae44cbcb-7b63-447a-b1a8-2f875effb1de
## INFO [10:30:55.669] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.676] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.679] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 83598.316889
## iter 10 value 2486.163326
## iter 20 value 1188.434909
## iter 30 value 922.581325
## iter 40 value 453.730324
## iter 50 value 250.362407
## iter 60 value 238.463529
## iter 70 value 236.639968
## iter 80 value 229.875489
## iter 90 value 223.699036
## iter 100 value 214.911926
## iter 110 value 211.580867
## iter 120 value 205.846939
## iter 130 value 194.165498
## iter 140 value 188.822838
## iter 150 value 175.850744
## final value 171.392192
## stopped after 157 iterations
## INFO [10:30:55.687] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 86118.120319
## iter 10 value 2810.008753
## iter 20 value 1374.447475
## iter 30 value 868.740591
## iter 40 value 780.225686
## iter 50 value 671.111046
## iter 60 value 519.947258
## iter 70 value 462.688306
## iter 80 value 436.901612
## iter 90 value 429.406150
## iter 100 value 429.072426
## iter 110 value 414.540031
## iter 120 value 260.215595
## iter 130 value 202.097143
## iter 140 value 185.032423
## iter 150 value 175.956017
## final value 156.113080
## stopped after 157 iterations
## INFO [10:30:55.695] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 87760.931922
## iter 10 value 2262.562316
## iter 20 value 1587.061485
## iter 30 value 1287.329712
## iter 40 value 1054.344476
## iter 50 value 744.822043
## iter 60 value 539.642931
## iter 70 value 483.951483
## iter 80 value 422.570266
## iter 90 value 358.257507
## iter 100 value 325.110975
## iter 110 value 306.196883
## iter 120 value 300.956816
## iter 130 value 281.698721
## iter 140 value 235.902368
## iter 150 value 189.304470
## final value 183.171056
## stopped after 157 iterations
## INFO [10:30:55.708] [mlr3] Finished benchmark
## INFO [10:30:55.721] [bbotk] Result of batch 5:
## INFO [10:30:55.721] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.721] [bbotk] 4 157 4.263465e-05 15.485 0 0 0.014
## INFO [10:30:55.721] [bbotk] uhash
## INFO [10:30:55.721] [bbotk] c2c54955-d05b-4a37-bd11-4ffd258e0587
## INFO [10:30:55.723] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.730] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.733] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 85306.281250
## iter 10 value 5177.718365
## iter 20 value 2111.612827
## iter 30 value 1307.352520
## iter 40 value 1139.615898
## iter 50 value 1132.674061
## iter 60 value 1124.785528
## iter 70 value 1118.367424
## iter 80 value 1076.366256
## iter 90 value 737.106661
## iter 100 value 621.548068
## iter 110 value 559.941637
## iter 120 value 518.055989
## iter 130 value 421.276803
## iter 140 value 418.950758
## iter 150 value 418.726650
## iter 160 value 418.134036
## iter 170 value 405.718665
## iter 180 value 358.595710
## iter 190 value 337.681728
## iter 200 value 320.727926
## iter 210 value 267.308050
## iter 220 value 223.362928
## iter 230 value 173.121033
## iter 240 value 125.551777
## iter 250 value 106.305476
## iter 260 value 100.957606
## iter 270 value 92.890717
## iter 280 value 80.360788
## iter 290 value 76.541206
## iter 300 value 76.317970
## iter 310 value 76.218812
## iter 320 value 75.892168
## iter 330 value 75.673756
## iter 340 value 75.604385
## iter 350 value 75.536089
## iter 360 value 75.394785
## final value 75.388791
## stopped after 361 iterations
## INFO [10:30:55.744] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 89020.185805
## iter 10 value 3023.705178
## iter 20 value 1216.531954
## iter 30 value 789.267825
## iter 40 value 734.339210
## iter 50 value 605.349181
## iter 60 value 340.505542
## iter 70 value 284.660284
## iter 80 value 195.942428
## iter 90 value 151.499131
## iter 100 value 130.631021
## iter 110 value 115.690591
## iter 120 value 109.548418
## iter 130 value 107.134476
## iter 140 value 105.703870
## iter 150 value 103.740710
## iter 160 value 100.108714
## iter 170 value 94.764773
## iter 180 value 91.750494
## iter 190 value 86.827491
## iter 200 value 85.560575
## iter 210 value 84.549454
## iter 220 value 84.360358
## iter 230 value 83.593028
## iter 240 value 80.952236
## iter 250 value 79.739130
## iter 260 value 78.792906
## iter 270 value 78.116518
## iter 280 value 78.046988
## iter 290 value 77.929587
## iter 300 value 77.811548
## iter 310 value 77.745272
## iter 320 value 77.744271
## iter 330 value 77.724269
## iter 340 value 77.676246
## iter 350 value 77.571407
## iter 360 value 77.522966
## final value 77.521684
## stopped after 361 iterations
## INFO [10:30:55.756] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 88796.300403
## iter 10 value 1983.511156
## iter 20 value 945.289915
## iter 30 value 507.772968
## iter 40 value 324.449806
## iter 50 value 223.871020
## iter 60 value 182.241777
## iter 70 value 158.259209
## iter 80 value 152.757040
## iter 90 value 148.931764
## iter 100 value 144.304762
## iter 110 value 143.614875
## iter 120 value 143.011734
## iter 130 value 142.321242
## iter 140 value 141.916342
## iter 150 value 141.191848
## iter 160 value 140.574968
## iter 170 value 140.469501
## iter 180 value 140.208346
## iter 190 value 138.314261
## iter 200 value 133.086352
## iter 210 value 132.166430
## iter 220 value 131.973548
## iter 230 value 131.186343
## iter 240 value 128.170409
## iter 250 value 125.478190
## iter 260 value 121.062824
## iter 270 value 114.492589
## iter 280 value 106.074982
## iter 290 value 99.383969
## iter 300 value 88.919304
## iter 310 value 86.258478
## iter 320 value 84.984726
## iter 330 value 83.077783
## iter 340 value 81.328680
## iter 350 value 80.998639
## iter 360 value 80.199670
## final value 80.130991
## stopped after 361 iterations
## INFO [10:30:55.767] [mlr3] Finished benchmark
## INFO [10:30:55.777] [bbotk] Result of batch 6:
## INFO [10:30:55.778] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.778] [bbotk] 7 361 5.214211e-05 9.719313 0 0 0.019
## INFO [10:30:55.778] [bbotk] uhash
## INFO [10:30:55.778] [bbotk] 5ed5ee53-33c8-4e2b-8e63-54f2a942db3c
## INFO [10:30:55.780] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.787] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.789] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 82440.267665
## iter 10 value 3685.542355
## iter 20 value 2861.742941
## iter 30 value 2379.015327
## iter 40 value 1339.050286
## iter 50 value 1218.585074
## iter 60 value 1206.022527
## iter 70 value 1187.929971
## iter 80 value 1186.097366
## iter 90 value 1184.196160
## iter 100 value 1183.702667
## iter 110 value 1183.570768
## iter 110 value 1183.570761
## final value 1183.570309
## stopped after 114 iterations
## INFO [10:30:55.797] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 82871.035805
## iter 10 value 3598.741194
## iter 20 value 2452.216479
## iter 30 value 2137.882107
## iter 40 value 1664.495413
## iter 50 value 1259.105775
## iter 60 value 1055.159884
## iter 70 value 1025.040487
## iter 80 value 1022.260451
## iter 90 value 1021.582708
## final value 1021.579852
## converged
## INFO [10:30:55.803] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 88794.821046
## final value 6602.085092
## converged
## INFO [10:30:55.809] [mlr3] Finished benchmark
## INFO [10:30:55.820] [bbotk] Result of batch 7:
## INFO [10:30:55.820] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.820] [bbotk] 1 114 8.800508e-06 10.23851 0 0 0.005
## INFO [10:30:55.820] [bbotk] uhash
## INFO [10:30:55.820] [bbotk] 96cd6989-8ad8-4da8-b8ee-1f252c3f61f4
## INFO [10:30:55.825] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.835] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.838] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 82554.993397
## iter 10 value 3183.495903
## iter 20 value 1226.169656
## iter 30 value 1199.458477
## iter 40 value 1196.194217
## iter 50 value 1181.504448
## iter 60 value 1181.449521
## iter 70 value 1176.537574
## iter 80 value 719.756605
## iter 90 value 686.550198
## iter 100 value 667.241691
## iter 110 value 665.030511
## iter 120 value 664.820421
## final value 664.517408
## converged
## INFO [10:30:55.846] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 85427.447982
## final value 9441.472559
## converged
## INFO [10:30:55.852] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 89726.739999
## iter 10 value 2769.239390
## iter 20 value 2682.673812
## iter 30 value 2674.103844
## iter 40 value 2654.032571
## final value 2654.018535
## converged
## INFO [10:30:55.858] [mlr3] Finished benchmark
## INFO [10:30:55.869] [bbotk] Result of batch 8:
## INFO [10:30:55.870] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.870] [bbotk] 2 297 5.113329e-05 11.12655 0 0 0.008
## INFO [10:30:55.870] [bbotk] uhash
## INFO [10:30:55.870] [bbotk] 16db9419-37ed-409f-9bc3-f48ca0ea0db0
## INFO [10:30:55.872] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.879] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.881] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 83454.249028
## iter 10 value 7914.342548
## iter 20 value 2890.217311
## iter 30 value 2387.316944
## iter 40 value 1299.585760
## iter 50 value 1222.101894
## iter 60 value 1192.843299
## iter 70 value 1186.243308
## iter 80 value 1185.049409
## iter 90 value 1184.809762
## iter 100 value 1184.787846
## iter 110 value 1184.720367
## iter 120 value 1184.663040
## iter 120 value 1184.663035
## final value 1184.662522
## converged
## INFO [10:30:55.890] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 85582.235378
## iter 10 value 1158.926240
## iter 20 value 504.672458
## iter 30 value 319.215577
## iter 40 value 243.616759
## iter 50 value 218.289199
## iter 60 value 114.520160
## iter 70 value 51.856360
## iter 80 value 35.533347
## iter 90 value 26.595389
## iter 100 value 22.300680
## iter 110 value 21.199028
## iter 120 value 20.430834
## iter 130 value 19.986161
## iter 140 value 19.069620
## final value 18.996481
## stopped after 141 iterations
## INFO [10:30:55.899] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 90745.622259
## iter 10 value 2845.649339
## iter 20 value 1156.995099
## iter 30 value 907.519723
## iter 40 value 814.121843
## iter 50 value 797.132139
## iter 60 value 778.542867
## iter 70 value 740.580480
## iter 80 value 677.838445
## iter 90 value 664.535241
## iter 100 value 656.425975
## iter 110 value 647.367788
## iter 120 value 641.071392
## iter 130 value 640.755586
## iter 140 value 640.730823
## final value 640.706243
## stopped after 141 iterations
## INFO [10:30:55.906] [mlr3] Finished benchmark
## INFO [10:30:55.917] [bbotk] Result of batch 9:
## INFO [10:30:55.918] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.918] [bbotk] 8 141 5.933146e-05 8.938647 0 0 0.013
## INFO [10:30:55.918] [bbotk] uhash
## INFO [10:30:55.918] [bbotk] 9cdbe5c3-5ba7-4983-99dd-e95fc54286db
## INFO [10:30:55.920] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.926] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.929] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 22
## initial value 83079.692637
## iter 10 value 5766.674710
## iter 20 value 2412.951514
## iter 30 value 1807.720644
## iter 40 value 1266.600288
## iter 50 value 1201.462044
## iter 60 value 1195.740618
## iter 70 value 1186.898408
## iter 80 value 1184.705467
## iter 90 value 1184.293692
## iter 100 value 1184.262542
## final value 1184.262242
## converged
## INFO [10:30:55.936] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 22
## initial value 86716.743918
## iter 10 value 1099.121358
## iter 20 value 791.181156
## iter 30 value 607.431814
## iter 40 value 508.170177
## iter 50 value 427.321685
## iter 60 value 416.227382
## iter 70 value 393.402303
## iter 80 value 383.733405
## iter 90 value 379.485959
## iter 100 value 378.888296
## iter 110 value 378.513527
## iter 120 value 378.454792
## iter 130 value 378.397272
## iter 140 value 378.193647
## iter 150 value 378.192398
## iter 160 value 378.188462
## iter 170 value 378.163877
## iter 180 value 378.132212
## final value 378.127317
## converged
## INFO [10:30:55.947] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 22
## initial value 89442.877960
## iter 10 value 2249.428292
## iter 20 value 1320.570314
## iter 30 value 725.901236
## iter 40 value 577.557603
## iter 50 value 510.390682
## iter 60 value 494.360949
## iter 70 value 493.351503
## iter 80 value 472.212776
## iter 90 value 457.035929
## iter 100 value 448.974713
## iter 110 value 446.436890
## iter 120 value 445.722237
## iter 130 value 443.547843
## iter 140 value 441.911448
## iter 150 value 439.568511
## iter 160 value 439.556440
## iter 170 value 439.546463
## iter 180 value 439.544170
## iter 190 value 439.540468
## final value 439.537145
## converged
## INFO [10:30:55.958] [mlr3] Finished benchmark
## INFO [10:30:55.969] [bbotk] Result of batch 10:
## INFO [10:30:55.970] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:55.970] [bbotk] 3 300 4.119386e-05 8.295178 0 0 0.011
## INFO [10:30:55.970] [bbotk] uhash
## INFO [10:30:55.970] [bbotk] 93280622-32c3-4532-bca5-84f33dc0177c
## INFO [10:30:55.971] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:55.978] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:55.981] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 84835.500513
## iter 10 value 3133.755191
## iter 20 value 2942.857818
## iter 30 value 2251.228786
## iter 40 value 1325.643798
## iter 50 value 1216.650303
## iter 60 value 1191.484895
## iter 70 value 1184.894078
## iter 80 value 1157.746938
## iter 90 value 941.375349
## iter 100 value 865.885724
## iter 110 value 793.094054
## iter 120 value 785.280436
## iter 130 value 753.369077
## iter 140 value 752.838461
## iter 150 value 748.836365
## iter 160 value 741.536741
## iter 170 value 420.964072
## iter 180 value 283.288243
## iter 190 value 247.733538
## iter 200 value 234.271054
## iter 210 value 231.421447
## iter 220 value 231.212610
## iter 230 value 231.109335
## iter 240 value 229.869562
## iter 250 value 227.527767
## iter 260 value 224.098411
## iter 270 value 220.008541
## iter 280 value 219.940023
## iter 290 value 216.351327
## iter 300 value 209.330800
## iter 310 value 207.640185
## final value 207.640185
## stopped after 310 iterations
## INFO [10:30:55.990] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 87685.440026
## iter 10 value 1678.478836
## iter 20 value 715.310368
## iter 30 value 613.876297
## iter 40 value 472.439764
## iter 50 value 413.641906
## iter 60 value 340.715188
## iter 70 value 322.878113
## iter 80 value 285.316676
## iter 90 value 265.380338
## iter 100 value 259.939858
## iter 110 value 258.896456
## iter 120 value 258.587488
## iter 130 value 258.393164
## iter 140 value 258.267259
## iter 150 value 257.993210
## iter 160 value 256.188974
## iter 170 value 244.787715
## iter 180 value 244.288631
## iter 190 value 243.906904
## iter 200 value 242.580581
## iter 210 value 241.948786
## iter 220 value 241.175173
## iter 230 value 240.086756
## iter 240 value 239.717614
## iter 250 value 239.579297
## iter 260 value 236.519448
## iter 270 value 230.332971
## iter 280 value 229.558062
## iter 290 value 229.387460
## iter 300 value 229.281068
## iter 310 value 229.262186
## final value 229.262186
## stopped after 310 iterations
## INFO [10:30:56.000] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 89032.560650
## iter 10 value 2207.769530
## iter 20 value 1103.426740
## iter 30 value 866.782548
## iter 40 value 677.435944
## iter 50 value 619.249390
## iter 60 value 561.490569
## iter 70 value 554.022088
## iter 80 value 553.704334
## iter 90 value 553.684452
## iter 100 value 553.628981
## iter 110 value 553.604866
## iter 120 value 553.584973
## iter 130 value 553.550314
## iter 140 value 553.497180
## iter 150 value 553.201931
## iter 160 value 546.970373
## iter 170 value 542.044901
## iter 180 value 541.471308
## iter 190 value 540.208779
## iter 200 value 524.218997
## iter 210 value 507.550917
## iter 220 value 507.338890
## iter 230 value 506.117857
## iter 240 value 502.589032
## iter 250 value 500.487991
## iter 260 value 500.414230
## iter 270 value 499.973861
## iter 280 value 499.966969
## iter 290 value 499.633042
## iter 300 value 499.386626
## iter 310 value 499.241021
## final value 499.241021
## stopped after 310 iterations
## INFO [10:30:56.008] [mlr3] Finished benchmark
## INFO [10:30:56.019] [bbotk] Result of batch 11:
## INFO [10:30:56.020] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.020] [bbotk] 4 310 5.420773e-05 13.69372 0 0 0.014
## INFO [10:30:56.020] [bbotk] uhash
## INFO [10:30:56.020] [bbotk] 1cccbc39-4681-4c27-bd92-581500e7bef0
## INFO [10:30:56.022] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.029] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.031] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 83925.899988
## iter 10 value 2814.305682
## iter 20 value 1370.614178
## iter 30 value 903.603252
## iter 40 value 553.073401
## iter 50 value 444.287507
## iter 60 value 405.417538
## iter 70 value 361.033842
## iter 80 value 289.084089
## iter 90 value 281.050047
## iter 100 value 271.579023
## iter 110 value 271.504917
## final value 271.489108
## converged
## INFO [10:30:56.040] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 89129.646768
## iter 10 value 1459.556658
## iter 20 value 849.129330
## iter 30 value 697.731900
## iter 40 value 596.867483
## iter 50 value 499.865479
## iter 60 value 485.965325
## iter 70 value 460.342775
## iter 80 value 429.208160
## iter 90 value 354.344793
## iter 100 value 235.586486
## iter 110 value 205.793780
## iter 120 value 189.011887
## iter 130 value 166.971896
## iter 140 value 133.936952
## iter 150 value 121.691700
## iter 160 value 110.682062
## iter 170 value 100.979403
## iter 180 value 94.385450
## iter 190 value 88.209097
## iter 200 value 85.859538
## iter 210 value 84.444443
## iter 220 value 82.727754
## iter 230 value 72.726222
## iter 240 value 70.709507
## iter 250 value 66.684201
## iter 260 value 56.554101
## iter 270 value 55.788346
## iter 280 value 53.887917
## iter 290 value 51.661577
## iter 300 value 50.530625
## iter 310 value 49.737746
## iter 320 value 48.874626
## iter 330 value 47.579862
## iter 340 value 47.288068
## iter 350 value 47.216658
## iter 360 value 47.194043
## iter 370 value 47.168806
## iter 380 value 47.021399
## iter 390 value 46.994884
## iter 400 value 46.958948
## final value 46.941009
## stopped after 403 iterations
## INFO [10:30:56.053] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 92735.024675
## iter 10 value 1938.837003
## iter 20 value 1016.538870
## iter 30 value 855.678313
## iter 40 value 818.598594
## iter 50 value 813.442038
## iter 60 value 808.747710
## iter 70 value 792.588393
## iter 80 value 617.841820
## iter 90 value 460.706729
## iter 100 value 364.671269
## iter 110 value 302.813955
## iter 120 value 280.706557
## iter 130 value 275.071134
## iter 140 value 268.284131
## iter 150 value 215.593012
## iter 160 value 191.903468
## iter 170 value 182.588694
## iter 180 value 173.217912
## iter 190 value 164.288716
## iter 200 value 158.613855
## iter 210 value 144.179876
## iter 220 value 135.705918
## iter 230 value 133.802741
## iter 240 value 133.307617
## iter 250 value 132.571068
## iter 260 value 132.181950
## iter 270 value 132.002135
## iter 280 value 131.841580
## iter 290 value 131.807841
## final value 131.805923
## converged
## INFO [10:30:56.069] [mlr3] Finished benchmark
## INFO [10:30:56.082] [bbotk] Result of batch 12:
## INFO [10:30:56.082] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.082] [bbotk] 8 403 1.021026e-06 17.84537 0 0 0.024
## INFO [10:30:56.082] [bbotk] uhash
## INFO [10:30:56.082] [bbotk] 43ba7995-3c44-420c-ad89-7c7467614d2a
## INFO [10:30:56.084] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.091] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.094] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 84077.942005
## iter 10 value 3845.445212
## iter 20 value 2437.868174
## iter 30 value 1698.401581
## iter 40 value 1242.614089
## iter 50 value 1204.550724
## iter 60 value 1194.822034
## iter 70 value 1187.133546
## iter 80 value 1185.506673
## iter 90 value 1185.362901
## iter 100 value 1185.271550
## final value 1185.270287
## converged
## INFO [10:30:56.101] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 88111.932243
## iter 10 value 1744.353178
## iter 20 value 1211.948171
## iter 30 value 861.313151
## iter 40 value 808.698515
## iter 50 value 765.606314
## iter 60 value 762.063352
## iter 70 value 762.018856
## iter 80 value 762.015084
## final value 762.014459
## converged
## INFO [10:30:56.108] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 87841.142086
## iter 10 value 2956.774289
## iter 20 value 1818.124163
## iter 30 value 1178.505611
## iter 40 value 1060.095022
## iter 50 value 1014.640986
## iter 60 value 981.858796
## iter 70 value 954.140626
## iter 80 value 917.109739
## iter 90 value 884.741314
## iter 100 value 884.688035
## final value 884.687705
## converged
## INFO [10:30:56.115] [mlr3] Finished benchmark
## INFO [10:30:56.126] [bbotk] Result of batch 13:
## INFO [10:30:56.126] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.126] [bbotk] 2 483 8.50991e-05 9.794818 0 0 0.008
## INFO [10:30:56.126] [bbotk] uhash
## INFO [10:30:56.126] [bbotk] 68c28add-8103-4d9c-86ee-5cb9f260e3c7
## INFO [10:30:56.128] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.135] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.137] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 87162.426575
## iter 10 value 2377.071641
## iter 20 value 980.907128
## iter 30 value 721.260788
## iter 40 value 645.235901
## iter 50 value 430.113100
## iter 60 value 357.775996
## iter 70 value 347.482470
## iter 80 value 345.950740
## iter 90 value 341.967558
## iter 100 value 336.864030
## iter 110 value 335.289609
## iter 120 value 334.105779
## iter 130 value 306.877477
## iter 140 value 288.940671
## iter 150 value 285.724460
## iter 160 value 284.895082
## iter 170 value 267.422336
## iter 180 value 234.730542
## iter 190 value 187.144876
## final value 177.000164
## stopped after 194 iterations
## INFO [10:30:56.147] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 88172.888836
## iter 10 value 3159.252094
## iter 20 value 1071.796801
## iter 30 value 811.271742
## iter 40 value 802.766147
## iter 50 value 754.703911
## iter 60 value 728.602587
## iter 70 value 717.601441
## iter 80 value 711.936325
## iter 90 value 708.670533
## iter 100 value 703.338212
## iter 110 value 701.387853
## iter 120 value 684.812569
## iter 130 value 673.447904
## iter 140 value 673.134642
## iter 150 value 670.579081
## iter 160 value 669.267631
## iter 170 value 668.680330
## iter 180 value 668.447896
## iter 190 value 668.145986
## final value 668.133724
## stopped after 194 iterations
## INFO [10:30:56.156] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 95138.019218
## iter 10 value 1619.864366
## iter 20 value 878.249929
## iter 30 value 484.260931
## iter 40 value 294.874323
## iter 50 value 217.693672
## iter 60 value 181.423336
## iter 70 value 158.248208
## iter 80 value 147.442481
## iter 90 value 143.518970
## iter 100 value 141.704965
## iter 110 value 140.307293
## iter 120 value 136.974559
## iter 130 value 135.490841
## iter 140 value 130.685641
## iter 150 value 128.297720
## iter 160 value 126.562645
## iter 170 value 124.917565
## iter 180 value 124.663281
## iter 190 value 124.372429
## final value 124.366160
## stopped after 194 iterations
## INFO [10:30:56.164] [mlr3] Finished benchmark
## INFO [10:30:56.180] [bbotk] Result of batch 14:
## INFO [10:30:56.181] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.181] [bbotk] 7 194 6.593456e-05 13.6557 0 0 0.015
## INFO [10:30:56.181] [bbotk] uhash
## INFO [10:30:56.181] [bbotk] 332b9a35-d7e7-418d-8205-1afca521b266
## INFO [10:30:56.184] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.191] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.194] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 84697.731691
## iter 10 value 3579.448325
## iter 20 value 2369.708961
## iter 30 value 1321.375471
## iter 40 value 1224.568986
## iter 50 value 1193.634338
## iter 60 value 1186.383648
## iter 70 value 1184.099732
## iter 80 value 1183.757790
## iter 90 value 1183.460164
## iter 100 value 1183.448329
## final value 1183.448086
## converged
## INFO [10:30:56.202] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 81530.898176
## iter 10 value 1230.858608
## iter 20 value 580.681580
## iter 30 value 416.820989
## iter 40 value 293.256248
## iter 50 value 267.985530
## iter 60 value 194.581637
## iter 70 value 133.959919
## iter 80 value 80.833775
## iter 90 value 70.673748
## iter 100 value 68.923227
## iter 110 value 68.047833
## iter 120 value 67.314430
## iter 130 value 66.396410
## iter 140 value 66.205324
## iter 150 value 66.012070
## iter 160 value 65.666804
## iter 170 value 65.493849
## iter 180 value 65.420726
## iter 190 value 65.345576
## iter 200 value 65.230019
## iter 210 value 65.169999
## iter 220 value 65.137588
## iter 230 value 65.052987
## iter 240 value 64.148998
## iter 250 value 63.236800
## iter 260 value 63.077664
## iter 270 value 63.064244
## iter 280 value 63.050664
## iter 290 value 63.018397
## iter 300 value 63.002494
## iter 310 value 62.993871
## iter 320 value 62.964029
## iter 330 value 62.942500
## iter 340 value 62.922638
## iter 350 value 62.914749
## iter 360 value 62.898286
## iter 370 value 62.813845
## iter 380 value 62.781764
## iter 390 value 62.779996
## final value 62.779996
## stopped after 390 iterations
## INFO [10:30:56.215] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 91421.158701
## iter 10 value 2684.797689
## iter 20 value 757.381195
## iter 30 value 459.118703
## iter 40 value 300.781913
## iter 50 value 219.283562
## iter 60 value 159.884308
## iter 70 value 105.754465
## iter 80 value 83.808435
## iter 90 value 71.018299
## iter 100 value 63.744331
## iter 110 value 59.455341
## iter 120 value 57.863005
## iter 130 value 57.280380
## iter 140 value 57.058112
## iter 150 value 56.910705
## iter 160 value 56.467756
## iter 170 value 56.238162
## iter 180 value 55.982278
## iter 190 value 55.827156
## iter 200 value 55.701116
## iter 210 value 55.614960
## iter 220 value 55.531287
## iter 230 value 55.492084
## iter 240 value 55.483383
## iter 250 value 55.480047
## iter 260 value 55.387637
## iter 270 value 55.360322
## iter 280 value 55.357530
## iter 290 value 55.349566
## iter 300 value 55.340385
## iter 310 value 55.249966
## iter 320 value 52.959751
## iter 330 value 51.496880
## iter 340 value 50.841862
## iter 350 value 50.513582
## iter 360 value 50.364527
## iter 370 value 50.282368
## iter 380 value 50.229931
## iter 390 value 50.154623
## final value 50.154623
## stopped after 390 iterations
## INFO [10:30:56.228] [mlr3] Finished benchmark
## INFO [10:30:56.239] [bbotk] Result of batch 15:
## INFO [10:30:56.240] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.240] [bbotk] 9 390 5.820521e-06 13.60529 0 0 0.022
## INFO [10:30:56.240] [bbotk] uhash
## INFO [10:30:56.240] [bbotk] 069c6992-1e29-4770-a797-63bb4f186a4d
## INFO [10:30:56.242] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.249] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.251] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 91015.992398
## iter 10 value 1394.273918
## iter 20 value 650.373881
## iter 30 value 440.375458
## iter 40 value 375.478283
## iter 50 value 364.563569
## iter 60 value 361.638534
## iter 70 value 360.748758
## iter 80 value 358.170800
## iter 90 value 296.490081
## iter 100 value 243.623869
## iter 110 value 227.618333
## iter 120 value 210.885920
## iter 130 value 204.536337
## iter 140 value 195.557309
## iter 150 value 190.642783
## iter 160 value 189.922508
## iter 170 value 177.317662
## iter 180 value 141.253383
## iter 190 value 120.993212
## iter 200 value 110.792576
## iter 210 value 106.481475
## iter 220 value 104.246171
## iter 230 value 87.786773
## final value 81.356356
## stopped after 237 iterations
## INFO [10:30:56.263] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 81666.704348
## iter 10 value 9442.310751
## iter 20 value 9441.707284
## iter 30 value 9151.101359
## iter 40 value 2420.995025
## iter 50 value 1950.639882
## iter 60 value 1190.245674
## iter 70 value 1036.572645
## iter 80 value 1024.488106
## iter 90 value 1023.354487
## iter 100 value 1022.709167
## iter 110 value 1022.641456
## iter 120 value 1022.587416
## iter 120 value 1022.587410
## final value 1022.587297
## converged
## INFO [10:30:56.271] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 88048.519848
## iter 10 value 2477.980011
## iter 20 value 1614.664382
## iter 30 value 1482.488763
## iter 40 value 1450.640021
## iter 50 value 1408.088989
## iter 60 value 1396.842134
## iter 70 value 1389.155874
## iter 80 value 1386.603715
## iter 90 value 1381.410161
## iter 100 value 1040.027675
## iter 110 value 1013.602628
## iter 120 value 992.512440
## iter 130 value 969.643686
## iter 140 value 955.746974
## iter 150 value 951.492488
## iter 160 value 951.452215
## iter 170 value 950.673951
## iter 180 value 948.617552
## iter 190 value 943.718067
## iter 200 value 793.840985
## iter 210 value 658.722963
## iter 220 value 656.580111
## iter 230 value 646.288090
## final value 619.190555
## stopped after 237 iterations
## INFO [10:30:56.281] [mlr3] Finished benchmark
## INFO [10:30:56.299] [bbotk] Result of batch 16:
## INFO [10:30:56.300] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.300] [bbotk] 9 237 5.115715e-05 9.87273 0 0 0.015
## INFO [10:30:56.300] [bbotk] uhash
## INFO [10:30:56.300] [bbotk] be2a1114-51c8-4d15-8d5b-4fc8d235b082
## INFO [10:30:56.301] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.308] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.311] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 82748.706392
## iter 10 value 1463.319886
## iter 20 value 971.135138
## iter 30 value 783.877926
## iter 40 value 462.531135
## iter 50 value 409.307213
## iter 60 value 333.122841
## iter 70 value 304.074298
## iter 80 value 302.353382
## iter 90 value 301.987801
## iter 100 value 300.922928
## iter 110 value 297.240104
## iter 120 value 246.706395
## iter 130 value 209.780383
## iter 140 value 194.665437
## iter 150 value 190.076948
## iter 160 value 188.186901
## iter 170 value 185.442940
## iter 180 value 184.578891
## iter 190 value 183.811369
## iter 200 value 183.738695
## iter 210 value 183.736848
## iter 220 value 183.384391
## iter 230 value 183.074498
## iter 240 value 183.026614
## iter 250 value 183.017731
## iter 260 value 182.955467
## iter 270 value 182.853665
## iter 280 value 152.042431
## iter 290 value 131.555733
## iter 300 value 128.813124
## iter 310 value 112.524755
## final value 108.290313
## stopped after 312 iterations
## INFO [10:30:56.322] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 86499.127219
## iter 10 value 908.936394
## iter 20 value 487.762832
## iter 30 value 441.936893
## iter 40 value 437.074174
## iter 50 value 431.708465
## iter 60 value 421.036031
## iter 70 value 419.606864
## iter 80 value 415.616203
## iter 90 value 413.260139
## iter 100 value 412.883112
## iter 110 value 412.787066
## iter 120 value 412.736460
## iter 130 value 374.475883
## iter 140 value 361.094925
## iter 150 value 359.101070
## iter 160 value 358.973737
## iter 170 value 358.863568
## iter 180 value 358.518042
## iter 190 value 358.189685
## iter 200 value 357.533599
## iter 210 value 357.180449
## iter 220 value 356.590841
## iter 230 value 356.366480
## iter 240 value 356.325096
## iter 250 value 356.319968
## iter 260 value 356.291856
## iter 270 value 356.231079
## iter 280 value 356.186065
## iter 290 value 356.153712
## iter 300 value 356.127408
## iter 310 value 355.830257
## final value 349.096642
## stopped after 312 iterations
## INFO [10:30:56.333] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 91044.365476
## iter 10 value 1759.810114
## iter 20 value 1021.386982
## iter 30 value 834.490486
## iter 40 value 589.028168
## iter 50 value 541.198201
## iter 60 value 373.943552
## iter 70 value 324.817355
## iter 80 value 311.376493
## iter 90 value 305.518962
## iter 100 value 300.638412
## iter 110 value 289.773252
## iter 120 value 245.839075
## iter 130 value 193.852126
## iter 140 value 165.546052
## iter 150 value 158.944706
## iter 160 value 144.523245
## iter 170 value 141.207521
## iter 180 value 140.834267
## iter 190 value 137.488453
## iter 200 value 123.363648
## iter 210 value 113.789882
## iter 220 value 107.712001
## iter 230 value 97.621645
## iter 240 value 89.010397
## iter 250 value 84.061811
## iter 260 value 67.689206
## iter 270 value 29.683933
## iter 280 value 22.849307
## iter 290 value 19.727830
## iter 300 value 18.997941
## iter 310 value 18.502761
## final value 18.322847
## stopped after 312 iterations
## INFO [10:30:56.344] [mlr3] Finished benchmark
## INFO [10:30:56.355] [bbotk] Result of batch 17:
## INFO [10:30:56.356] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.356] [bbotk] 7 312 5.673564e-05 8.9031 0 0 0.017
## INFO [10:30:56.356] [bbotk] uhash
## INFO [10:30:56.356] [bbotk] ca3b388c-c918-4cb1-9968-07e23dea38c6
## INFO [10:30:56.358] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.364] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.367] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 81615.563729
## iter 10 value 1586.014283
## iter 20 value 630.938426
## iter 30 value 427.723570
## iter 40 value 326.615933
## iter 50 value 256.678596
## iter 60 value 230.667546
## iter 70 value 220.296991
## iter 80 value 209.549140
## iter 90 value 194.915374
## iter 100 value 186.910812
## iter 110 value 185.326143
## iter 120 value 184.474281
## iter 130 value 183.670046
## iter 140 value 183.528406
## iter 150 value 182.961217
## iter 160 value 182.315284
## iter 170 value 166.050988
## iter 180 value 164.559129
## iter 190 value 164.304337
## iter 200 value 163.715661
## iter 210 value 162.842310
## iter 220 value 162.276786
## iter 230 value 161.866069
## iter 240 value 161.224932
## iter 250 value 159.438956
## iter 260 value 151.828311
## iter 270 value 120.623311
## iter 280 value 111.583138
## iter 290 value 106.137815
## iter 300 value 67.981742
## iter 310 value 47.851839
## iter 320 value 44.450953
## iter 330 value 43.766556
## iter 340 value 42.751421
## iter 350 value 39.970358
## iter 360 value 35.340119
## iter 370 value 31.658120
## iter 380 value 30.193958
## iter 390 value 29.169287
## iter 400 value 27.673965
## iter 410 value 26.422979
## iter 420 value 24.989694
## iter 430 value 24.231056
## iter 440 value 24.121790
## iter 450 value 22.961773
## iter 460 value 21.441640
## iter 470 value 18.505795
## iter 480 value 17.415460
## final value 17.297984
## stopped after 487 iterations
## INFO [10:30:56.383] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 84050.108128
## iter 10 value 1281.765369
## iter 20 value 584.806656
## iter 30 value 455.163081
## iter 40 value 371.826665
## iter 50 value 309.155638
## iter 60 value 295.043921
## iter 70 value 256.176818
## iter 80 value 227.913127
## iter 90 value 189.359955
## iter 100 value 171.133761
## iter 110 value 152.482814
## iter 120 value 147.275099
## iter 130 value 144.233526
## iter 140 value 140.709850
## iter 150 value 139.089554
## iter 160 value 137.929772
## iter 170 value 135.614387
## iter 180 value 133.946622
## iter 190 value 133.590354
## iter 200 value 133.017790
## iter 210 value 131.062490
## iter 220 value 126.175014
## iter 230 value 119.594482
## iter 240 value 110.207224
## iter 250 value 96.764718
## iter 260 value 88.217936
## iter 270 value 75.003632
## iter 280 value 67.845458
## iter 290 value 63.039772
## iter 300 value 59.014175
## iter 310 value 49.830589
## iter 320 value 47.790908
## iter 330 value 40.638762
## iter 340 value 32.458845
## iter 350 value 26.616737
## iter 360 value 22.533851
## iter 370 value 18.815962
## iter 380 value 17.493569
## iter 390 value 16.920194
## iter 400 value 16.623461
## iter 410 value 16.117077
## iter 420 value 15.924157
## iter 430 value 15.645302
## iter 440 value 15.473523
## iter 450 value 15.457735
## iter 460 value 15.391320
## iter 470 value 15.245788
## iter 480 value 15.180627
## final value 15.059240
## stopped after 487 iterations
## INFO [10:30:56.399] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 86742.864504
## iter 10 value 2711.781381
## iter 20 value 1609.288984
## iter 30 value 1432.599497
## iter 40 value 1399.070908
## iter 50 value 1391.306777
## iter 60 value 1388.426983
## iter 70 value 1387.987629
## iter 80 value 1387.885418
## iter 90 value 1387.452985
## iter 100 value 1383.404754
## iter 110 value 1037.630731
## iter 120 value 857.758444
## iter 130 value 818.603647
## iter 140 value 774.444100
## iter 150 value 656.002086
## iter 160 value 651.772728
## iter 170 value 648.723872
## iter 180 value 648.046655
## iter 190 value 647.578914
## iter 200 value 645.839064
## iter 210 value 644.287180
## iter 220 value 639.806975
## iter 230 value 591.043876
## iter 240 value 526.865326
## iter 250 value 516.431986
## iter 260 value 514.158710
## iter 270 value 512.747224
## iter 280 value 510.346268
## iter 290 value 508.171259
## iter 300 value 507.869734
## iter 310 value 484.275971
## iter 320 value 444.403039
## iter 330 value 430.103498
## iter 340 value 427.846048
## iter 350 value 422.451855
## iter 360 value 403.139966
## iter 370 value 348.729274
## iter 380 value 330.663234
## iter 390 value 318.050623
## iter 400 value 311.320279
## iter 410 value 256.004279
## iter 420 value 190.222435
## iter 430 value 160.164540
## iter 440 value 132.051606
## iter 450 value 110.115879
## iter 460 value 96.631296
## iter 470 value 86.731530
## iter 480 value 78.809957
## final value 76.086355
## stopped after 487 iterations
## INFO [10:30:56.419] [mlr3] Finished benchmark
## INFO [10:30:56.432] [bbotk] Result of batch 18:
## INFO [10:30:56.432] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.432] [bbotk] 9 487 8.087822e-05 12.60908 0 0 0.037
## INFO [10:30:56.432] [bbotk] uhash
## INFO [10:30:56.432] [bbotk] 6b8bb98b-8aa0-458a-8aff-974d9aad77a8
## INFO [10:30:56.434] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.441] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.444] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 71
## initial value 80557.228713
## iter 10 value 1092.227214
## iter 20 value 345.693935
## iter 30 value 195.710240
## iter 40 value 109.368279
## iter 50 value 77.606452
## iter 60 value 69.326299
## iter 70 value 62.065716
## iter 80 value 56.663887
## iter 90 value 53.766806
## final value 53.391007
## stopped after 93 iterations
## INFO [10:30:56.452] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 71
## initial value 83812.084563
## iter 10 value 1472.857581
## iter 20 value 550.117786
## iter 30 value 478.929096
## iter 40 value 463.227244
## iter 50 value 456.967801
## iter 60 value 453.883945
## iter 70 value 453.660164
## iter 80 value 453.108838
## iter 90 value 452.487512
## final value 449.716934
## stopped after 93 iterations
## INFO [10:30:56.461] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 71
## initial value 88147.243705
## iter 10 value 1453.806720
## iter 20 value 788.497191
## iter 30 value 437.380657
## iter 40 value 273.053168
## iter 50 value 234.643497
## iter 60 value 227.443645
## iter 70 value 203.069393
## iter 80 value 163.169283
## iter 90 value 143.505957
## final value 140.325530
## stopped after 93 iterations
## INFO [10:30:56.469] [mlr3] Finished benchmark
## INFO [10:30:56.480] [bbotk] Result of batch 19:
## INFO [10:30:56.481] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.481] [bbotk] 10 93 1.12927e-05 9.909154 0 0 0.01
## INFO [10:30:56.481] [bbotk] uhash
## INFO [10:30:56.481] [bbotk] ff4f34e8-c46b-4c1b-b914-29e08255b063
## INFO [10:30:56.482] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.489] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.492] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 82789.620096
## iter 10 value 2166.684411
## iter 20 value 589.110696
## iter 30 value 453.223170
## iter 40 value 392.399255
## iter 50 value 356.654809
## iter 60 value 330.590932
## iter 70 value 328.890907
## iter 80 value 328.216377
## iter 90 value 322.835631
## iter 100 value 294.209146
## iter 110 value 268.580595
## iter 120 value 245.475505
## iter 130 value 217.881693
## iter 140 value 185.639703
## iter 150 value 161.459330
## iter 160 value 148.255504
## iter 170 value 136.164745
## iter 180 value 125.426893
## iter 190 value 124.807684
## iter 200 value 123.809520
## iter 210 value 122.539084
## final value 122.405672
## stopped after 214 iterations
## INFO [10:30:56.502] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 85090.820195
## iter 10 value 1501.989863
## iter 20 value 530.680643
## iter 30 value 493.761539
## iter 40 value 478.590801
## iter 50 value 468.987990
## iter 60 value 456.977457
## iter 70 value 450.905526
## iter 80 value 444.416701
## iter 90 value 437.537940
## iter 100 value 416.594903
## iter 110 value 392.906953
## iter 120 value 391.719073
## iter 130 value 389.210992
## iter 140 value 386.873925
## iter 150 value 384.963435
## iter 160 value 384.944707
## iter 170 value 383.436000
## iter 180 value 369.282991
## iter 190 value 367.273775
## iter 200 value 365.088837
## iter 210 value 355.418402
## final value 353.322155
## stopped after 214 iterations
## INFO [10:30:56.511] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 86419.965148
## iter 10 value 5150.208419
## iter 20 value 2044.182546
## iter 30 value 1127.184016
## iter 40 value 795.806979
## iter 50 value 635.086700
## iter 60 value 617.855840
## iter 70 value 610.469872
## iter 80 value 547.538051
## iter 90 value 504.223300
## iter 100 value 499.216106
## iter 110 value 498.860872
## iter 120 value 497.871274
## iter 130 value 488.880092
## iter 140 value 479.713408
## iter 150 value 456.410809
## iter 160 value 445.849998
## iter 170 value 441.508435
## iter 180 value 441.098621
## iter 190 value 440.613527
## iter 200 value 440.546266
## iter 210 value 440.536852
## final value 440.535680
## stopped after 214 iterations
## INFO [10:30:56.525] [mlr3] Finished benchmark
## INFO [10:30:56.538] [bbotk] Result of batch 20:
## INFO [10:30:56.538] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.538] [bbotk] 7 214 1.443899e-05 17.89432 0 0 0.018
## INFO [10:30:56.538] [bbotk] uhash
## INFO [10:30:56.538] [bbotk] 0396f66a-3035-4a55-979f-d066efb1a295
## INFO [10:30:56.542] [bbotk] Finished optimizing after 20 evaluation(s)
## INFO [10:30:56.542] [bbotk] Result:
## INFO [10:30:56.543] [bbotk] size maxit decay learner_param_vals x_domain regr.rmse
## INFO [10:30:56.543] [bbotk] 3 300 4.119386e-05 <list[3]> <list[3]> 8.295178
## # weights: 22
## initial value 124405.536119
## iter 10 value 4600.319175
## iter 20 value 2299.074947
## iter 30 value 1395.662317
## iter 40 value 1273.750702
## iter 50 value 1220.555003
## iter 60 value 1157.057558
## iter 70 value 1034.437637
## iter 80 value 873.342870
## iter 90 value 856.901333
## iter 100 value 852.691694
## iter 110 value 843.597680
## iter 120 value 834.186698
## iter 130 value 815.041928
## iter 140 value 796.957173
## iter 150 value 781.315577
## iter 160 value 767.392819
## iter 170 value 758.761952
## iter 180 value 752.388758
## iter 190 value 748.509619
## iter 200 value 748.231456
## iter 210 value 748.222359
## iter 220 value 748.221454
## final value 748.220955
## converged
## INFO [10:30:56.559] [mlr3] Applying learner 'regr.nnet.tuned' on task 'cereal' (iter 4/5)
## INFO [10:30:56.576] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorEvals> [n_evals=20, k=0]'
## INFO [10:30:56.583] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.589] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.592] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 79647.254062
## iter 10 value 3176.958033
## iter 20 value 1048.558408
## iter 30 value 584.441049
## iter 40 value 402.625187
## iter 50 value 341.081196
## iter 60 value 323.011179
## iter 70 value 286.649678
## iter 80 value 285.011894
## iter 90 value 281.869347
## iter 100 value 273.398054
## iter 110 value 257.353058
## iter 120 value 209.324308
## iter 130 value 186.710094
## iter 140 value 168.651558
## iter 150 value 160.475256
## final value 159.437466
## stopped after 153 iterations
## INFO [10:30:56.601] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 82204.018941
## iter 10 value 3380.829024
## iter 20 value 563.035256
## iter 30 value 241.549882
## iter 40 value 168.618749
## iter 50 value 141.161048
## iter 60 value 118.637384
## iter 70 value 90.264205
## iter 80 value 73.195012
## iter 90 value 65.876122
## iter 100 value 55.003018
## iter 110 value 50.438739
## iter 120 value 47.191321
## iter 130 value 44.814307
## iter 140 value 40.941683
## iter 150 value 37.966639
## final value 36.796008
## stopped after 153 iterations
## INFO [10:30:56.611] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 79457.353119
## iter 10 value 3813.749316
## iter 20 value 1510.837336
## iter 30 value 1197.827746
## iter 40 value 1163.755407
## iter 50 value 1155.497990
## iter 60 value 1153.913263
## iter 70 value 1153.460138
## iter 80 value 1149.168944
## iter 90 value 1128.666227
## iter 100 value 1089.480514
## iter 110 value 930.497428
## iter 120 value 878.233082
## iter 130 value 875.074351
## iter 140 value 831.113275
## iter 150 value 775.932277
## final value 770.901212
## stopped after 153 iterations
## INFO [10:30:56.618] [mlr3] Finished benchmark
## INFO [10:30:56.632] [bbotk] Result of batch 1:
## INFO [10:30:56.633] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.633] [bbotk] 8 153 6.8896e-05 7.921639 0 0 0.013
## INFO [10:30:56.633] [bbotk] uhash
## INFO [10:30:56.633] [bbotk] 8f9700b5-1669-4fab-af99-4bd6be6db175
## INFO [10:30:56.636] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.644] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.647] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 75423.455705
## iter 10 value 3609.744468
## iter 20 value 1125.495576
## iter 30 value 557.269057
## iter 40 value 500.301154
## iter 50 value 492.344312
## iter 60 value 478.791637
## iter 70 value 475.641714
## iter 80 value 473.962086
## iter 90 value 471.599538
## iter 100 value 471.236833
## iter 110 value 470.574362
## iter 120 value 463.228298
## iter 130 value 462.564441
## iter 140 value 462.433206
## iter 150 value 462.427565
## final value 462.419085
## converged
## INFO [10:30:56.655] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 79782.565546
## iter 10 value 4240.427810
## iter 20 value 1691.096459
## iter 30 value 1541.963172
## iter 40 value 998.724110
## iter 50 value 894.094151
## iter 60 value 890.263131
## final value 890.195994
## converged
## INFO [10:30:56.662] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 80357.411796
## iter 10 value 1283.814648
## iter 20 value 646.563374
## iter 30 value 554.136683
## iter 40 value 534.805539
## iter 50 value 446.098113
## iter 60 value 439.970101
## iter 70 value 439.834534
## iter 80 value 439.773264
## iter 90 value 439.596905
## final value 439.596872
## converged
## INFO [10:30:56.668] [mlr3] Finished benchmark
## INFO [10:30:56.679] [bbotk] Result of batch 2:
## INFO [10:30:56.680] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.680] [bbotk] 2 232 2.719739e-05 8.026327 0 0 0.008
## INFO [10:30:56.680] [bbotk] uhash
## INFO [10:30:56.680] [bbotk] 5f60275d-e96c-4123-aae3-85d60f41424f
## INFO [10:30:56.681] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.688] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.691] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 76199.040094
## final value 7197.689906
## converged
## INFO [10:30:56.697] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 80166.491193
## iter 10 value 2503.436104
## iter 20 value 889.387327
## iter 30 value 693.816452
## iter 40 value 676.820298
## iter 50 value 663.176913
## iter 60 value 663.162014
## iter 70 value 663.136937
## iter 80 value 663.128060
## iter 90 value 663.078959
## iter 100 value 662.791313
## iter 110 value 655.817119
## iter 120 value 552.867817
## iter 130 value 357.939693
## iter 140 value 351.129617
## iter 150 value 350.189370
## iter 160 value 343.982981
## iter 170 value 342.842663
## iter 180 value 342.834193
## iter 190 value 342.784414
## iter 200 value 342.771123
## final value 342.771048
## converged
## INFO [10:30:56.705] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 76372.109352
## iter 10 value 1621.118079
## iter 20 value 614.771690
## iter 30 value 528.668945
## iter 40 value 523.614788
## iter 50 value 519.600355
## iter 60 value 516.648794
## iter 70 value 515.736098
## final value 515.735607
## converged
## INFO [10:30:56.711] [mlr3] Finished benchmark
## INFO [10:30:56.722] [bbotk] Result of batch 3:
## INFO [10:30:56.723] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.723] [bbotk] 2 309 1.647272e-05 8.727068 0 0 0.007
## INFO [10:30:56.723] [bbotk] uhash
## INFO [10:30:56.723] [bbotk] 7430ad38-31c6-491c-9dde-45cd82b4171d
## INFO [10:30:56.725] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.735] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.739] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 76855.092576
## final value 7198.572531
## converged
## INFO [10:30:56.747] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 80656.252225
## final value 6909.932794
## converged
## INFO [10:30:56.754] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 77132.476584
## iter 10 value 2398.787981
## iter 20 value 1564.551299
## iter 30 value 1396.520263
## iter 40 value 1251.814593
## iter 50 value 1198.903169
## iter 60 value 1160.278349
## iter 70 value 1153.118299
## iter 80 value 1151.441811
## iter 90 value 1149.985188
## iter 100 value 1149.603113
## iter 110 value 1149.151479
## iter 120 value 1149.115997
## iter 130 value 1148.837663
## iter 140 value 1148.779520
## iter 150 value 1148.687028
## iter 150 value 1148.687025
## iter 160 value 1148.679987
## iter 170 value 1148.560579
## iter 180 value 1148.548724
## final value 1148.546143
## converged
## INFO [10:30:56.760] [mlr3] Finished benchmark
## INFO [10:30:56.772] [bbotk] Result of batch 4:
## INFO [10:30:56.772] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.772] [bbotk] 1 191 3.267971e-05 9.486437 0 0 0.006
## INFO [10:30:56.772] [bbotk] uhash
## INFO [10:30:56.772] [bbotk] 894ca7c8-8b11-4fd8-8900-be79cf5c8fd9
## INFO [10:30:56.774] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.781] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.784] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 75252.884324
## final value 7197.663487
## converged
## INFO [10:30:56.790] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 76367.270209
## iter 10 value 1891.443883
## iter 20 value 1626.893404
## iter 30 value 1075.065815
## iter 40 value 941.386488
## iter 50 value 890.309672
## iter 60 value 890.095470
## final value 890.077131
## converged
## INFO [10:30:56.797] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 80627.011843
## iter 10 value 1607.163041
## iter 20 value 1239.194889
## iter 30 value 1179.044078
## iter 40 value 1162.354865
## iter 50 value 1152.988223
## iter 60 value 1151.512971
## iter 70 value 1149.497540
## iter 80 value 1149.300170
## iter 90 value 1148.628502
## iter 100 value 1148.372802
## iter 110 value 1147.905496
## iter 120 value 1147.790811
## iter 130 value 1147.717151
## iter 140 value 1147.652780
## iter 150 value 1147.583386
## iter 160 value 1147.527923
## iter 170 value 1147.488296
## iter 180 value 1147.421076
## iter 190 value 1147.370082
## iter 200 value 1147.359912
## iter 210 value 1147.336746
## final value 1147.336343
## converged
## INFO [10:30:56.804] [mlr3] Finished benchmark
## INFO [10:30:56.815] [bbotk] Result of batch 5:
## INFO [10:30:56.816] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.816] [bbotk] 1 333 2.346569e-07 8.343919 0 0 0.008
## INFO [10:30:56.816] [bbotk] uhash
## INFO [10:30:56.816] [bbotk] 87a2fb1f-1421-4097-9333-74a80385ae44
## INFO [10:30:56.817] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.829] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.833] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 77069.460205
## iter 10 value 2455.232148
## iter 20 value 680.381243
## iter 30 value 578.090731
## iter 40 value 457.812132
## iter 50 value 402.385659
## iter 60 value 386.484144
## iter 70 value 377.320415
## iter 80 value 374.902590
## iter 90 value 373.018521
## iter 100 value 371.604819
## iter 110 value 371.348887
## iter 120 value 371.278745
## iter 130 value 371.190671
## iter 140 value 371.167837
## iter 150 value 371.115576
## iter 160 value 371.085691
## iter 170 value 370.996560
## iter 180 value 370.849945
## iter 190 value 370.845271
## iter 200 value 370.817937
## iter 210 value 370.802559
## iter 220 value 370.790851
## iter 230 value 370.756758
## iter 240 value 370.734851
## final value 370.733973
## converged
## INFO [10:30:56.842] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 81593.932751
## iter 10 value 3134.709264
## iter 20 value 1207.588282
## iter 30 value 478.194977
## iter 40 value 273.740695
## iter 50 value 252.167878
## iter 60 value 221.848147
## iter 70 value 213.219806
## iter 80 value 197.490344
## iter 90 value 189.395490
## iter 100 value 178.081936
## iter 110 value 163.781769
## iter 120 value 160.673603
## iter 130 value 160.506649
## iter 140 value 160.389347
## iter 150 value 158.742674
## iter 160 value 157.407859
## iter 170 value 156.216868
## iter 180 value 155.459973
## iter 190 value 151.831473
## iter 200 value 146.826389
## iter 210 value 142.499817
## iter 220 value 141.965548
## iter 230 value 133.127152
## iter 240 value 126.695877
## iter 250 value 125.387751
## iter 260 value 124.975156
## iter 270 value 124.489509
## iter 280 value 124.463988
## iter 290 value 124.233785
## iter 300 value 123.822068
## iter 310 value 123.277206
## final value 123.120496
## stopped after 311 iterations
## INFO [10:30:56.852] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 78143.464103
## iter 10 value 2337.063718
## iter 20 value 1406.900034
## iter 30 value 1256.225100
## iter 40 value 1065.805792
## iter 50 value 934.753268
## iter 60 value 904.366128
## iter 70 value 895.288091
## iter 80 value 888.508217
## iter 90 value 883.857014
## iter 100 value 881.557389
## iter 110 value 880.658984
## iter 120 value 879.823208
## iter 130 value 879.777655
## iter 140 value 879.764947
## iter 150 value 879.703956
## iter 160 value 878.264250
## iter 170 value 812.597278
## iter 180 value 731.102024
## iter 190 value 723.653304
## iter 200 value 722.747110
## iter 210 value 719.351643
## iter 220 value 718.295362
## iter 230 value 717.563249
## iter 240 value 717.243807
## iter 250 value 717.153455
## final value 717.148612
## converged
## INFO [10:30:56.860] [mlr3] Finished benchmark
## INFO [10:30:56.871] [bbotk] Result of batch 6:
## INFO [10:30:56.872] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.872] [bbotk] 4 311 4.140793e-05 9.620708 0 0 0.015
## INFO [10:30:56.872] [bbotk] uhash
## INFO [10:30:56.872] [bbotk] cbe00273-d229-44e7-a8a6-abb725900b3f
## INFO [10:30:56.874] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.881] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.883] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 71
## initial value 79449.886459
## iter 10 value 1505.139574
## iter 20 value 607.561898
## iter 30 value 415.807293
## iter 40 value 231.695951
## iter 50 value 165.425041
## iter 60 value 132.149346
## iter 70 value 100.182917
## iter 80 value 69.184741
## iter 90 value 66.033949
## iter 100 value 64.547980
## iter 110 value 63.494519
## iter 120 value 62.427119
## iter 130 value 59.412391
## iter 140 value 57.816658
## iter 150 value 57.450302
## iter 160 value 57.250532
## iter 170 value 57.116352
## iter 180 value 56.607204
## iter 190 value 56.072754
## iter 200 value 55.560652
## iter 210 value 55.186871
## iter 220 value 54.924882
## iter 230 value 54.809461
## iter 240 value 53.331141
## iter 250 value 49.587622
## iter 260 value 45.414992
## iter 270 value 44.264443
## iter 280 value 43.809920
## iter 290 value 43.306942
## iter 300 value 42.837798
## final value 42.783392
## stopped after 305 iterations
## INFO [10:30:56.896] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 71
## initial value 82628.386945
## final value 6912.706775
## converged
## INFO [10:30:56.903] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 71
## initial value 75566.294762
## iter 10 value 1696.222234
## iter 20 value 649.682842
## iter 30 value 374.118727
## iter 40 value 303.466463
## iter 50 value 209.813542
## iter 60 value 164.431165
## iter 70 value 124.646397
## iter 80 value 120.503620
## iter 90 value 117.923666
## iter 100 value 114.048619
## iter 110 value 111.813568
## iter 120 value 111.176810
## iter 130 value 110.818890
## iter 140 value 110.704049
## iter 150 value 110.375700
## iter 160 value 109.153927
## iter 170 value 105.267373
## iter 180 value 104.777869
## iter 190 value 103.886184
## iter 200 value 103.848001
## iter 210 value 103.733524
## iter 220 value 103.722735
## iter 230 value 103.714613
## iter 240 value 102.527431
## iter 250 value 83.780022
## iter 260 value 74.023533
## iter 270 value 69.291464
## iter 280 value 67.137376
## iter 290 value 61.724856
## iter 300 value 49.810903
## final value 46.415671
## stopped after 305 iterations
## INFO [10:30:56.920] [mlr3] Finished benchmark
## INFO [10:30:56.933] [bbotk] Result of batch 7:
## INFO [10:30:56.934] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.934] [bbotk] 10 305 3.250192e-05 9.6612 0 0 0.022
## INFO [10:30:56.934] [bbotk] uhash
## INFO [10:30:56.934] [bbotk] 70230894-2bd1-4d25-b1c1-30b7f0cf3624
## INFO [10:30:56.935] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.942] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.945] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 22
## initial value 76525.994555
## iter 10 value 1281.486813
## iter 20 value 668.859459
## iter 30 value 455.292121
## iter 40 value 312.372550
## iter 50 value 279.265483
## iter 60 value 251.282983
## iter 70 value 199.273038
## iter 80 value 179.777838
## iter 90 value 177.473066
## iter 100 value 177.253041
## iter 110 value 176.819459
## iter 120 value 176.457814
## iter 130 value 175.748603
## iter 140 value 175.678870
## iter 150 value 175.671270
## iter 160 value 175.625425
## iter 170 value 175.575711
## iter 180 value 175.479796
## final value 175.478986
## converged
## INFO [10:30:56.953] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 22
## initial value 82048.516100
## iter 10 value 1746.879397
## iter 20 value 390.574608
## iter 30 value 297.352238
## iter 40 value 290.880346
## iter 50 value 287.154860
## iter 60 value 283.724212
## iter 70 value 272.230989
## iter 80 value 250.513277
## iter 90 value 241.061723
## iter 100 value 240.578010
## iter 110 value 238.002888
## iter 120 value 235.111743
## iter 130 value 234.120016
## iter 140 value 234.063421
## iter 150 value 234.052435
## iter 160 value 234.041656
## final value 234.041543
## converged
## INFO [10:30:56.961] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 22
## initial value 80699.219347
## iter 10 value 2163.611324
## iter 20 value 1473.516625
## iter 30 value 1296.013521
## iter 40 value 1019.878388
## iter 50 value 855.173084
## iter 60 value 754.281105
## iter 70 value 600.345310
## iter 80 value 539.717388
## iter 90 value 463.509126
## iter 100 value 454.190556
## iter 110 value 446.566723
## iter 120 value 442.379622
## iter 130 value 442.155079
## iter 140 value 442.011601
## iter 150 value 442.000465
## iter 160 value 441.975885
## iter 170 value 441.944445
## iter 180 value 441.942030
## iter 190 value 429.223995
## iter 200 value 417.628198
## iter 210 value 387.032021
## iter 220 value 366.802835
## iter 230 value 348.782893
## final value 348.782893
## stopped after 230 iterations
## INFO [10:30:56.969] [mlr3] Finished benchmark
## INFO [10:30:56.980] [bbotk] Result of batch 8:
## INFO [10:30:56.981] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:56.981] [bbotk] 3 230 9.676331e-05 7.856719 0 0 0.011
## INFO [10:30:56.981] [bbotk] uhash
## INFO [10:30:56.981] [bbotk] 9ff014f9-021d-4a93-90c7-7a4fec73bc04
## INFO [10:30:56.983] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:56.989] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:56.992] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 22
## initial value 76815.108770
## iter 10 value 1300.958126
## iter 20 value 896.927352
## iter 30 value 852.160215
## iter 40 value 816.867436
## iter 50 value 797.024075
## final value 748.613405
## stopped after 58 iterations
## INFO [10:30:56.999] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 22
## initial value 76218.489354
## iter 10 value 1901.812554
## iter 20 value 1095.229101
## iter 30 value 893.540219
## iter 40 value 626.958487
## iter 50 value 602.465209
## final value 586.538831
## stopped after 58 iterations
## INFO [10:30:57.011] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 22
## initial value 77594.614122
## iter 10 value 3795.186841
## iter 20 value 1427.501395
## iter 30 value 1320.133040
## iter 40 value 1189.101469
## iter 50 value 1166.563830
## final value 1157.603031
## stopped after 58 iterations
## INFO [10:30:57.019] [mlr3] Finished benchmark
## INFO [10:30:57.030] [bbotk] Result of batch 9:
## INFO [10:30:57.031] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.031] [bbotk] 3 58 3.272069e-05 7.604849 0 0 0.01
## INFO [10:30:57.031] [bbotk] uhash
## INFO [10:30:57.031] [bbotk] 9af71789-794f-415d-8157-8491ccece63c
## INFO [10:30:57.033] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.040] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.042] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 75954.206031
## iter 10 value 1814.542902
## iter 20 value 1180.212522
## iter 30 value 1089.925467
## iter 40 value 1059.314220
## iter 50 value 871.151533
## iter 60 value 766.078413
## iter 70 value 696.474973
## final value 696.253011
## stopped after 75 iterations
## INFO [10:30:57.050] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 76488.986376
## iter 10 value 2282.087244
## iter 20 value 436.739833
## iter 30 value 294.132084
## iter 40 value 280.247950
## iter 50 value 265.616341
## iter 60 value 262.300862
## iter 70 value 262.251672
## final value 262.212099
## stopped after 75 iterations
## INFO [10:30:57.057] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 75717.303277
## iter 10 value 3062.179126
## iter 20 value 1504.875542
## iter 30 value 1224.745800
## iter 40 value 1184.971453
## iter 50 value 1156.337802
## iter 60 value 1152.927936
## iter 70 value 1151.459890
## final value 1150.281577
## stopped after 75 iterations
## INFO [10:30:57.063] [mlr3] Finished benchmark
## INFO [10:30:57.074] [bbotk] Result of batch 10:
## INFO [10:30:57.075] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.075] [bbotk] 2 75 5.25751e-05 6.850185 0 0 0.007
## INFO [10:30:57.075] [bbotk] uhash
## INFO [10:30:57.075] [bbotk] 4038ff88-a516-48d7-95ea-7bec8ed4e3ac
## INFO [10:30:57.076] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.083] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.086] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 76681.006143
## iter 10 value 3454.807150
## iter 20 value 1912.303275
## iter 30 value 1450.216497
## iter 40 value 1311.040897
## iter 50 value 713.760981
## iter 60 value 646.757303
## iter 70 value 643.741276
## final value 629.317793
## stopped after 73 iterations
## INFO [10:30:57.098] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 78314.663298
## final value 6909.861105
## converged
## INFO [10:30:57.106] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 80992.157229
## iter 10 value 2006.415446
## iter 20 value 1544.975532
## iter 30 value 1086.241659
## iter 40 value 560.160036
## iter 50 value 527.325838
## iter 60 value 524.810826
## iter 70 value 517.541847
## final value 516.010519
## stopped after 73 iterations
## INFO [10:30:57.112] [mlr3] Finished benchmark
## INFO [10:30:57.124] [bbotk] Result of batch 11:
## INFO [10:30:57.124] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.124] [bbotk] 2 73 1.755493e-05 7.46907 0 0 0.008
## INFO [10:30:57.124] [bbotk] uhash
## INFO [10:30:57.124] [bbotk] 758b9aa4-88a0-4709-8d37-7b91fe770822
## INFO [10:30:57.126] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.133] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.136] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 76181.407416
## iter 10 value 3061.825826
## iter 20 value 1715.384821
## iter 30 value 1114.018069
## iter 40 value 668.328205
## iter 50 value 504.378241
## iter 60 value 481.842008
## iter 70 value 479.058838
## iter 80 value 476.869461
## iter 90 value 474.360695
## iter 100 value 472.713353
## iter 110 value 471.563377
## iter 120 value 470.670103
## iter 130 value 469.763414
## iter 140 value 463.864383
## iter 150 value 463.863079
## iter 160 value 463.862603
## final value 463.862562
## converged
## INFO [10:30:57.144] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 78106.445576
## iter 10 value 2216.573892
## iter 20 value 2164.831478
## iter 30 value 2115.532897
## iter 40 value 1803.170617
## iter 50 value 1721.373778
## iter 60 value 1281.537366
## iter 70 value 915.068757
## iter 80 value 891.568349
## iter 90 value 890.885303
## iter 100 value 890.430433
## iter 110 value 887.514003
## iter 120 value 817.300287
## iter 130 value 417.123912
## iter 140 value 403.456312
## iter 150 value 403.243025
## iter 160 value 402.777741
## iter 170 value 402.775067
## final value 402.775054
## converged
## INFO [10:30:57.151] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 78181.370602
## iter 10 value 3835.860568
## iter 20 value 3531.360503
## iter 30 value 3527.072002
## iter 40 value 3526.448710
## iter 50 value 3524.629620
## iter 60 value 3519.246904
## iter 70 value 3515.337232
## iter 80 value 3514.138540
## iter 90 value 3513.631176
## iter 100 value 3513.576926
## iter 110 value 3513.438623
## iter 120 value 3513.205778
## iter 130 value 3374.675574
## iter 140 value 1929.025091
## iter 150 value 1413.086533
## iter 160 value 1311.622602
## iter 170 value 1224.497700
## iter 180 value 1169.672248
## iter 190 value 1156.710769
## iter 200 value 1152.793635
## iter 210 value 1150.778215
## iter 220 value 1150.190844
## iter 230 value 1149.972331
## iter 240 value 1149.681927
## iter 250 value 1149.251705
## iter 260 value 1149.155963
## final value 1149.154444
## converged
## INFO [10:30:57.159] [mlr3] Finished benchmark
## INFO [10:30:57.175] [bbotk] Result of batch 12:
## INFO [10:30:57.177] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.177] [bbotk] 2 373 4.830053e-05 6.57438 0 0 0.01
## INFO [10:30:57.177] [bbotk] uhash
## INFO [10:30:57.177] [bbotk] 57d09bbd-0144-4b1c-9611-9e0b7389729d
## INFO [10:30:57.178] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.185] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.188] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 73946.447979
## final value 7198.159640
## converged
## INFO [10:30:57.195] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 79753.811654
## iter 10 value 1961.484452
## iter 20 value 1103.387780
## iter 30 value 555.478938
## iter 40 value 296.350116
## iter 50 value 277.791819
## iter 60 value 268.097745
## iter 70 value 262.716066
## iter 80 value 262.333241
## final value 262.332247
## converged
## INFO [10:30:57.202] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 79026.855614
## iter 10 value 3009.419402
## iter 20 value 1830.248987
## iter 30 value 1706.407034
## iter 40 value 1692.216608
## iter 50 value 1657.083961
## iter 60 value 1471.665073
## iter 70 value 1307.057490
## iter 80 value 1206.123715
## iter 90 value 1170.785253
## iter 100 value 1154.254885
## iter 110 value 1152.552340
## iter 120 value 1150.623596
## iter 130 value 1149.066197
## iter 140 value 1141.215483
## iter 150 value 965.876943
## iter 160 value 886.496294
## iter 170 value 858.310358
## iter 180 value 853.614743
## iter 190 value 822.855607
## iter 200 value 695.957519
## iter 210 value 659.613923
## iter 220 value 599.277310
## iter 230 value 589.624298
## iter 240 value 584.275221
## iter 250 value 579.632639
## iter 260 value 579.367326
## iter 270 value 574.599549
## iter 280 value 548.739395
## iter 290 value 533.050945
## iter 300 value 518.087038
## iter 310 value 516.471400
## iter 320 value 516.416814
## iter 330 value 516.413609
## final value 516.407983
## converged
## INFO [10:30:57.210] [mlr3] Finished benchmark
## INFO [10:30:57.222] [bbotk] Result of batch 13:
## INFO [10:30:57.222] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.222] [bbotk] 2 387 8.499084e-05 7.948422 0 0 0.01
## INFO [10:30:57.222] [bbotk] uhash
## INFO [10:30:57.222] [bbotk] 4577d0ab-194f-49b2-814f-3aa50d13ed78
## INFO [10:30:57.224] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.231] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.233] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 73756.826064
## iter 10 value 1128.796588
## iter 20 value 668.837620
## iter 30 value 465.563256
## iter 40 value 312.380702
## iter 50 value 229.700324
## iter 60 value 185.942719
## iter 70 value 167.143538
## iter 80 value 136.789925
## iter 90 value 130.022036
## iter 100 value 128.820840
## iter 110 value 128.224898
## iter 120 value 126.413093
## iter 130 value 118.919361
## iter 140 value 107.925878
## iter 150 value 46.101327
## iter 160 value 29.885333
## iter 170 value 27.311340
## iter 180 value 25.398635
## iter 190 value 24.519677
## iter 200 value 23.697849
## iter 210 value 22.698301
## iter 220 value 22.271388
## iter 230 value 22.179689
## iter 240 value 22.025944
## iter 250 value 21.970148
## iter 260 value 21.854230
## iter 270 value 21.849316
## iter 280 value 21.841584
## iter 290 value 21.822434
## iter 300 value 21.787792
## iter 310 value 21.697114
## final value 21.666715
## stopped after 312 iterations
## INFO [10:30:57.246] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 78582.471990
## iter 10 value 6787.216186
## iter 20 value 2599.802734
## iter 30 value 827.205205
## iter 40 value 273.248095
## iter 50 value 202.683014
## iter 60 value 194.653781
## iter 70 value 192.777577
## iter 80 value 191.828193
## iter 90 value 188.941946
## iter 100 value 187.795547
## iter 110 value 187.261196
## iter 120 value 185.221575
## iter 130 value 182.210251
## iter 140 value 181.419899
## iter 150 value 180.565018
## iter 160 value 178.527120
## iter 170 value 162.480812
## iter 180 value 155.255468
## iter 190 value 153.133168
## iter 200 value 152.487901
## iter 210 value 151.915390
## iter 220 value 150.431841
## iter 230 value 150.286870
## iter 240 value 149.899259
## iter 250 value 149.404162
## iter 260 value 145.209609
## iter 270 value 138.414347
## iter 280 value 137.023290
## iter 290 value 131.200588
## iter 300 value 127.221467
## iter 310 value 120.309742
## final value 118.758162
## stopped after 312 iterations
## INFO [10:30:57.265] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 79629.209958
## iter 10 value 1818.054307
## iter 20 value 1459.569049
## iter 30 value 1074.943187
## iter 40 value 565.461564
## iter 50 value 473.581126
## iter 60 value 465.229609
## iter 70 value 465.049884
## iter 80 value 464.696736
## iter 90 value 437.820714
## iter 100 value 436.072927
## iter 110 value 425.781018
## iter 120 value 390.556786
## iter 130 value 369.310835
## iter 140 value 328.382249
## iter 150 value 317.028856
## iter 160 value 315.703700
## iter 170 value 311.505922
## iter 180 value 293.678660
## iter 190 value 280.133271
## iter 200 value 274.730961
## iter 210 value 273.791717
## iter 220 value 272.788810
## iter 230 value 272.341337
## iter 240 value 271.560763
## iter 250 value 271.279818
## iter 260 value 271.252791
## iter 270 value 271.092725
## iter 280 value 270.070712
## iter 290 value 258.615530
## iter 300 value 216.424798
## iter 310 value 215.676486
## final value 215.667562
## stopped after 312 iterations
## INFO [10:30:57.277] [mlr3] Finished benchmark
## INFO [10:30:57.288] [bbotk] Result of batch 14:
## INFO [10:30:57.289] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.289] [bbotk] 9 312 3.121987e-05 9.493398 0 0 0.026
## INFO [10:30:57.289] [bbotk] uhash
## INFO [10:30:57.289] [bbotk] f9c14aad-49a3-418e-9144-f1baeaaa5683
## INFO [10:30:57.291] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.298] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.300] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 71
## initial value 75699.117815
## iter 10 value 3870.210487
## iter 20 value 2881.064814
## iter 30 value 2633.437962
## iter 40 value 1911.677334
## iter 50 value 1337.846243
## iter 60 value 905.776926
## iter 70 value 744.273884
## iter 80 value 660.316469
## iter 90 value 624.398340
## iter 100 value 618.249606
## iter 110 value 606.490607
## iter 120 value 589.986292
## iter 130 value 583.789823
## iter 140 value 575.812650
## iter 150 value 570.414513
## iter 160 value 562.798522
## iter 170 value 562.656833
## iter 180 value 562.192391
## iter 190 value 555.389729
## iter 200 value 522.967078
## iter 210 value 472.954723
## iter 220 value 432.471463
## iter 230 value 412.156284
## iter 240 value 407.169668
## iter 250 value 405.099827
## iter 260 value 403.944590
## iter 270 value 394.840800
## iter 280 value 393.720188
## iter 290 value 393.464480
## iter 300 value 392.861651
## iter 310 value 389.984135
## iter 320 value 385.941442
## iter 330 value 382.951415
## iter 340 value 382.118837
## iter 350 value 381.935076
## iter 360 value 378.082553
## iter 370 value 336.368868
## iter 380 value 248.900856
## iter 390 value 181.424594
## final value 167.995812
## stopped after 398 iterations
## INFO [10:30:57.316] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 71
## initial value 79692.818924
## iter 10 value 1672.410155
## iter 20 value 686.666675
## iter 30 value 511.244757
## iter 40 value 391.613209
## iter 50 value 272.761107
## iter 60 value 179.925472
## iter 70 value 125.858289
## iter 80 value 100.990610
## iter 90 value 90.628818
## iter 100 value 80.578075
## iter 110 value 55.699585
## iter 120 value 46.451654
## iter 130 value 38.765973
## iter 140 value 33.235737
## iter 150 value 29.994578
## iter 160 value 27.810849
## iter 170 value 25.695031
## iter 180 value 24.671171
## iter 190 value 23.952349
## iter 200 value 23.347505
## iter 210 value 21.812759
## iter 220 value 20.988355
## iter 230 value 20.240658
## iter 240 value 17.579602
## iter 250 value 13.239962
## iter 260 value 10.240711
## iter 270 value 9.260486
## iter 280 value 8.831439
## iter 290 value 8.070845
## iter 300 value 7.882097
## iter 310 value 7.229528
## iter 320 value 6.472812
## iter 330 value 5.310892
## iter 340 value 4.270179
## iter 350 value 3.787786
## iter 360 value 3.579389
## iter 370 value 3.268852
## iter 380 value 3.114250
## iter 390 value 2.862031
## final value 2.686088
## stopped after 398 iterations
## INFO [10:30:57.336] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 71
## initial value 82423.814559
## iter 10 value 1553.694541
## iter 20 value 1252.436680
## iter 30 value 865.402474
## iter 40 value 535.124332
## iter 50 value 330.627018
## iter 60 value 279.909505
## iter 70 value 269.395122
## iter 80 value 265.845929
## iter 90 value 256.943671
## iter 100 value 253.336241
## iter 110 value 247.917167
## iter 120 value 246.990003
## iter 130 value 245.666267
## iter 140 value 241.965930
## iter 150 value 238.403730
## iter 160 value 234.290994
## iter 170 value 231.717509
## iter 180 value 229.976839
## iter 190 value 224.949980
## iter 200 value 218.436556
## iter 210 value 215.315513
## iter 220 value 182.176979
## iter 230 value 128.988478
## iter 240 value 113.762475
## iter 250 value 109.203478
## iter 260 value 105.387234
## iter 270 value 104.469057
## iter 280 value 103.358602
## iter 290 value 97.918333
## iter 300 value 89.575296
## iter 310 value 88.872089
## iter 320 value 86.705815
## iter 330 value 85.456180
## iter 340 value 85.045419
## iter 350 value 83.961213
## iter 360 value 83.375980
## iter 370 value 83.088606
## iter 380 value 82.402144
## iter 390 value 82.035743
## final value 81.802906
## stopped after 398 iterations
## INFO [10:30:57.351] [mlr3] Finished benchmark
## INFO [10:30:57.363] [bbotk] Result of batch 15:
## INFO [10:30:57.363] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.363] [bbotk] 10 398 6.479318e-05 9.702574 0 0 0.035
## INFO [10:30:57.363] [bbotk] uhash
## INFO [10:30:57.363] [bbotk] f2f11ad6-6d8d-4218-aea8-08f7c4c653d4
## INFO [10:30:57.365] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.372] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.375] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 73570.810409
## final value 7197.712373
## converged
## INFO [10:30:57.382] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 78900.544140
## final value 6909.938251
## converged
## INFO [10:30:57.388] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 78067.849624
## iter 10 value 4980.681789
## iter 20 value 1511.327361
## iter 30 value 1303.750128
## iter 40 value 1208.332171
## iter 50 value 1172.497683
## iter 60 value 1154.669466
## iter 70 value 1152.715539
## iter 80 value 1150.336715
## iter 90 value 1150.131578
## iter 100 value 1149.588766
## iter 110 value 1149.409768
## iter 120 value 1149.327178
## iter 130 value 1149.235059
## iter 140 value 1149.188736
## iter 150 value 1149.094360
## final value 1149.093168
## stopped after 154 iterations
## INFO [10:30:57.395] [mlr3] Finished benchmark
## INFO [10:30:57.406] [bbotk] Result of batch 16:
## INFO [10:30:57.407] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.407] [bbotk] 1 154 4.650919e-05 9.486234 0 0 0.007
## INFO [10:30:57.407] [bbotk] uhash
## INFO [10:30:57.407] [bbotk] 0f15f5e7-3fa5-4e60-8fdd-3bbffefe4456
## INFO [10:30:57.408] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.418] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.422] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 43
## initial value 73387.402662
## iter 10 value 1048.867719
## iter 20 value 575.452365
## iter 30 value 331.703500
## iter 40 value 195.069454
## iter 50 value 123.966759
## iter 60 value 87.267600
## iter 70 value 73.279012
## iter 80 value 71.108013
## iter 90 value 70.318840
## iter 100 value 69.686243
## iter 110 value 68.662379
## iter 120 value 66.515661
## iter 130 value 58.023832
## iter 140 value 53.440810
## iter 150 value 45.740036
## iter 160 value 38.682778
## iter 170 value 35.770153
## iter 180 value 34.663220
## final value 34.618217
## stopped after 182 iterations
## INFO [10:30:57.433] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 43
## initial value 77969.155266
## iter 10 value 1565.996194
## iter 20 value 918.226744
## iter 30 value 700.714093
## iter 40 value 646.662129
## iter 50 value 553.588542
## iter 60 value 358.090280
## iter 70 value 353.845503
## iter 80 value 346.359660
## iter 90 value 344.549573
## iter 100 value 344.311569
## iter 110 value 344.257939
## iter 120 value 344.000255
## iter 130 value 343.394936
## iter 140 value 340.928373
## iter 150 value 329.138710
## iter 160 value 303.190271
## iter 170 value 243.916635
## iter 180 value 175.361090
## final value 163.105567
## stopped after 182 iterations
## INFO [10:30:57.442] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 43
## initial value 77608.354310
## iter 10 value 2471.223257
## iter 20 value 928.897923
## iter 30 value 650.199822
## iter 40 value 572.640623
## iter 50 value 537.507206
## iter 60 value 419.467479
## iter 70 value 346.642934
## iter 80 value 330.956087
## iter 90 value 323.361536
## iter 100 value 313.742073
## iter 110 value 310.796327
## iter 120 value 308.861552
## iter 130 value 307.818515
## iter 140 value 298.034181
## iter 150 value 229.448375
## iter 160 value 201.003467
## iter 170 value 186.703081
## iter 180 value 183.029127
## final value 181.941272
## stopped after 182 iterations
## INFO [10:30:57.451] [mlr3] Finished benchmark
## INFO [10:30:57.462] [bbotk] Result of batch 17:
## INFO [10:30:57.463] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.463] [bbotk] 6 182 9.137956e-05 9.626471 0 0 0.013
## INFO [10:30:57.463] [bbotk] uhash
## INFO [10:30:57.463] [bbotk] f0671efa-16a4-4f80-a7d0-7ce5c0fe11ee
## INFO [10:30:57.465] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.471] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.474] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 76671.719223
## iter 10 value 1117.599522
## iter 20 value 628.417805
## iter 30 value 310.914677
## iter 40 value 167.717744
## iter 50 value 131.775626
## iter 60 value 114.908168
## iter 70 value 85.981185
## iter 80 value 68.698864
## iter 90 value 56.997935
## iter 100 value 39.972120
## iter 110 value 33.805849
## iter 120 value 31.892576
## iter 130 value 31.265795
## iter 140 value 29.169146
## iter 150 value 27.815320
## iter 160 value 26.937108
## iter 170 value 26.634376
## iter 180 value 26.505239
## iter 190 value 26.452871
## iter 200 value 26.442106
## iter 210 value 26.397309
## final value 26.391601
## stopped after 214 iterations
## INFO [10:30:57.589] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 80815.035685
## iter 10 value 2946.912171
## iter 20 value 995.709936
## iter 30 value 684.277525
## iter 40 value 354.409819
## iter 50 value 263.131573
## iter 60 value 164.059133
## iter 70 value 133.157154
## iter 80 value 112.268338
## iter 90 value 104.102458
## iter 100 value 99.417940
## iter 110 value 95.430541
## iter 120 value 93.373129
## iter 130 value 90.536574
## iter 140 value 78.752017
## iter 150 value 60.889484
## iter 160 value 55.264074
## iter 170 value 53.530242
## iter 180 value 52.030134
## iter 190 value 50.965025
## iter 200 value 50.149327
## iter 210 value 49.759779
## final value 49.703695
## stopped after 214 iterations
## INFO [10:30:57.599] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 78869.604771
## iter 10 value 4167.445153
## iter 20 value 2280.242178
## iter 30 value 1228.881501
## iter 40 value 986.569187
## iter 50 value 919.926563
## iter 60 value 801.483312
## iter 70 value 775.176342
## iter 80 value 774.460446
## iter 90 value 768.314458
## iter 100 value 759.175289
## iter 110 value 719.586830
## iter 120 value 690.490501
## iter 130 value 689.355992
## iter 140 value 678.237200
## iter 150 value 674.026863
## iter 160 value 670.671052
## iter 170 value 601.291906
## iter 180 value 552.354706
## iter 190 value 501.311309
## iter 200 value 442.632746
## iter 210 value 431.902336
## final value 428.657622
## stopped after 214 iterations
## INFO [10:30:57.608] [mlr3] Finished benchmark
## INFO [10:30:57.619] [bbotk] Result of batch 18:
## INFO [10:30:57.620] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.620] [bbotk] 8 214 1.671782e-05 9.221697 0 0 0.118
## INFO [10:30:57.620] [bbotk] uhash
## INFO [10:30:57.620] [bbotk] 5e8f7687-9e40-46df-86f3-214e1c8b9812
## INFO [10:30:57.622] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.628] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.631] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 76760.594099
## iter 10 value 2811.570072
## iter 20 value 1627.767614
## iter 30 value 946.162184
## iter 40 value 562.962210
## iter 50 value 483.694937
## iter 60 value 477.893554
## iter 70 value 477.111964
## iter 80 value 472.743552
## iter 90 value 472.104773
## iter 100 value 467.486539
## iter 110 value 466.359741
## iter 120 value 465.861321
## iter 130 value 463.340029
## iter 140 value 463.174134
## iter 150 value 463.169126
## final value 463.168501
## converged
## INFO [10:30:57.639] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 79435.001724
## iter 10 value 5311.306560
## iter 20 value 1656.687779
## iter 30 value 1081.478689
## iter 40 value 916.870576
## iter 50 value 892.846149
## iter 60 value 890.275660
## iter 70 value 890.240482
## iter 80 value 890.226755
## iter 90 value 888.953011
## iter 100 value 882.989992
## iter 110 value 665.184068
## iter 120 value 422.856789
## iter 130 value 392.880687
## iter 140 value 372.311256
## iter 150 value 345.825932
## iter 160 value 343.441071
## iter 170 value 343.425550
## iter 180 value 343.024272
## iter 190 value 342.992980
## final value 342.992925
## converged
## INFO [10:30:57.647] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 79077.414540
## iter 10 value 3002.127587
## iter 20 value 1553.569881
## iter 30 value 1315.798083
## iter 40 value 1214.946682
## iter 50 value 1162.460249
## iter 60 value 1152.658982
## iter 70 value 1151.584338
## iter 80 value 1150.093858
## iter 90 value 1141.454776
## iter 100 value 1114.650318
## iter 110 value 957.367635
## iter 120 value 768.116781
## iter 130 value 726.635979
## iter 140 value 692.693313
## iter 150 value 665.783011
## iter 160 value 645.407659
## iter 170 value 590.268386
## iter 180 value 582.854858
## iter 190 value 582.502485
## iter 200 value 582.301130
## iter 210 value 575.403695
## iter 220 value 563.598443
## iter 230 value 547.644641
## iter 240 value 524.464217
## iter 250 value 518.695660
## iter 260 value 517.064326
## iter 270 value 515.990403
## final value 515.988431
## converged
## INFO [10:30:57.655] [mlr3] Finished benchmark
## INFO [10:30:57.665] [bbotk] Result of batch 19:
## INFO [10:30:57.666] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.666] [bbotk] 2 401 3.894598e-05 7.049084 0 0 0.011
## INFO [10:30:57.666] [bbotk] uhash
## INFO [10:30:57.666] [bbotk] 543a8bce-8b50-43ca-a0f5-76a1e2748dcf
## INFO [10:30:57.668] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.674] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.677] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 74769.584354
## iter 10 value 7154.737969
## iter 20 value 2445.579532
## iter 30 value 1441.542005
## iter 40 value 1435.951390
## iter 50 value 1272.916537
## iter 60 value 1222.598912
## iter 70 value 1220.050064
## iter 80 value 1219.757425
## iter 90 value 1218.668535
## iter 100 value 1137.154432
## iter 110 value 740.694393
## iter 120 value 528.788857
## iter 130 value 453.938759
## iter 140 value 434.137767
## iter 150 value 426.038263
## iter 160 value 423.063365
## iter 170 value 420.386689
## iter 180 value 415.636237
## iter 190 value 414.827198
## iter 200 value 414.230744
## iter 210 value 413.737175
## iter 220 value 411.153248
## iter 230 value 367.414900
## iter 240 value 316.481534
## iter 250 value 226.632420
## iter 260 value 189.995516
## iter 270 value 174.990846
## iter 280 value 172.010777
## iter 290 value 168.905560
## iter 300 value 167.922783
## iter 310 value 167.246190
## iter 320 value 159.758933
## iter 330 value 151.127157
## iter 340 value 147.864561
## iter 350 value 138.340373
## final value 133.829139
## stopped after 356 iterations
## INFO [10:30:57.689] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 77992.048004
## iter 10 value 1403.110419
## iter 20 value 709.121812
## iter 30 value 613.659677
## iter 40 value 603.682959
## iter 50 value 521.217446
## iter 60 value 496.184751
## iter 70 value 489.997162
## iter 80 value 489.566321
## iter 90 value 488.820943
## iter 100 value 488.431693
## iter 110 value 487.924915
## iter 120 value 487.754773
## iter 130 value 487.088657
## iter 140 value 482.716324
## iter 150 value 342.378491
## iter 160 value 290.143233
## iter 170 value 285.597604
## iter 180 value 279.460906
## iter 190 value 277.400238
## iter 200 value 264.017996
## iter 210 value 242.613851
## iter 220 value 217.864870
## iter 230 value 130.914514
## iter 240 value 124.622395
## iter 250 value 121.386902
## iter 260 value 118.022398
## iter 270 value 113.625880
## iter 280 value 110.389145
## iter 290 value 105.543532
## iter 300 value 99.260523
## iter 310 value 97.550996
## iter 320 value 96.417480
## iter 330 value 95.304381
## iter 340 value 90.545931
## iter 350 value 83.232409
## final value 82.391317
## stopped after 356 iterations
## INFO [10:30:57.701] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 80229.167053
## iter 10 value 4309.665790
## iter 20 value 1836.406407
## iter 30 value 1391.051901
## iter 40 value 1283.924151
## iter 50 value 1042.680109
## iter 60 value 884.427880
## iter 70 value 772.176947
## iter 80 value 499.724404
## iter 90 value 407.801002
## iter 100 value 352.676051
## iter 110 value 323.472276
## iter 120 value 320.703117
## iter 130 value 313.530453
## iter 140 value 291.502663
## iter 150 value 275.180731
## iter 160 value 272.664380
## iter 170 value 272.012693
## iter 180 value 271.510720
## iter 190 value 264.511666
## iter 200 value 264.316092
## iter 210 value 263.962265
## iter 220 value 263.618421
## iter 230 value 263.577957
## iter 240 value 263.251268
## iter 250 value 260.956740
## iter 260 value 258.890783
## iter 270 value 256.128674
## iter 280 value 255.576960
## iter 290 value 255.382028
## iter 300 value 255.233217
## iter 310 value 255.132508
## iter 320 value 255.053454
## iter 330 value 255.049940
## iter 340 value 255.013235
## iter 350 value 254.984665
## final value 254.973058
## stopped after 356 iterations
## INFO [10:30:57.712] [mlr3] Finished benchmark
## INFO [10:30:57.727] [bbotk] Result of batch 20:
## INFO [10:30:57.728] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.728] [bbotk] 7 356 6.275318e-05 8.013516 0 0 0.024
## INFO [10:30:57.728] [bbotk] uhash
## INFO [10:30:57.728] [bbotk] b7f2f68f-6f90-499d-ba0c-8d6e4745af21
## INFO [10:30:57.731] [bbotk] Finished optimizing after 20 evaluation(s)
## INFO [10:30:57.731] [bbotk] Result:
## INFO [10:30:57.732] [bbotk] size maxit decay learner_param_vals x_domain regr.rmse
## INFO [10:30:57.732] [bbotk] 2 373 4.830053e-05 <list[3]> <list[3]> 6.57438
## # weights: 15
## initial value 116212.339840
## iter 10 value 4902.785291
## iter 20 value 3711.445889
## iter 30 value 3380.499091
## iter 40 value 3212.678720
## iter 50 value 2264.001327
## iter 60 value 1934.313451
## iter 70 value 1856.448221
## iter 80 value 1839.780642
## iter 90 value 1838.441911
## iter 100 value 1838.402974
## iter 110 value 1838.382460
## final value 1838.372844
## converged
## INFO [10:30:57.746] [mlr3] Applying learner 'regr.nnet.tuned' on task 'cereal' (iter 5/5)
## INFO [10:30:57.763] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorEvals> [n_evals=20, k=0]'
## INFO [10:30:57.769] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.776] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.778] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 83085.077476
## iter 10 value 3031.788380
## iter 20 value 2754.876216
## iter 30 value 2728.488398
## iter 40 value 2183.840115
## iter 50 value 1468.348063
## iter 60 value 1149.507298
## final value 1134.357170
## stopped after 62 iterations
## INFO [10:30:57.785] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 80481.959420
## iter 10 value 2677.918486
## iter 20 value 1058.904624
## iter 30 value 1029.627808
## iter 40 value 1024.827850
## iter 50 value 1014.751736
## iter 60 value 1012.260708
## final value 1011.967571
## stopped after 62 iterations
## INFO [10:30:57.792] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 93064.683669
## iter 10 value 2521.613905
## iter 20 value 1495.920745
## iter 30 value 1462.361865
## iter 40 value 1450.389402
## iter 50 value 1449.889206
## final value 1449.887339
## converged
## INFO [10:30:57.798] [mlr3] Finished benchmark
## INFO [10:30:57.808] [bbotk] Result of batch 1:
## INFO [10:30:57.809] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.809] [bbotk] 2 62 1.299817e-05 6.434725 0 0 0.007
## INFO [10:30:57.809] [bbotk] uhash
## INFO [10:30:57.809] [bbotk] cd51d347-7d3e-436e-8874-650c37742cac
## INFO [10:30:57.811] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.817] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.820] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 79176.876437
## iter 10 value 2135.519636
## iter 20 value 905.222686
## iter 30 value 442.649698
## iter 40 value 369.555536
## iter 50 value 344.782822
## iter 60 value 327.173642
## iter 70 value 315.108758
## iter 80 value 300.862345
## iter 90 value 298.575786
## iter 100 value 291.802470
## iter 110 value 281.105673
## iter 120 value 279.740018
## final value 279.447658
## stopped after 126 iterations
## INFO [10:30:57.839] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 85255.612804
## iter 10 value 1231.550151
## iter 20 value 665.056132
## iter 30 value 534.628944
## iter 40 value 422.756256
## iter 50 value 315.647364
## iter 60 value 257.818073
## iter 70 value 160.710945
## iter 80 value 100.811839
## iter 90 value 69.255248
## iter 100 value 55.559496
## iter 110 value 45.256582
## iter 120 value 33.642594
## final value 28.076886
## stopped after 126 iterations
## INFO [10:30:57.848] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 89052.384262
## iter 10 value 1475.873324
## iter 20 value 813.410887
## iter 30 value 621.978469
## iter 40 value 560.694703
## iter 50 value 552.971654
## iter 60 value 551.752624
## iter 70 value 551.033427
## iter 80 value 550.784969
## iter 90 value 523.295033
## iter 100 value 512.103230
## iter 110 value 510.653664
## iter 120 value 510.271012
## final value 509.760509
## stopped after 126 iterations
## INFO [10:30:57.857] [mlr3] Finished benchmark
## INFO [10:30:57.867] [bbotk] Result of batch 2:
## INFO [10:30:57.868] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.868] [bbotk] 9 126 5.910645e-05 9.295543 0 0 0.011
## INFO [10:30:57.868] [bbotk] uhash
## INFO [10:30:57.868] [bbotk] c46a7f63-551b-437d-9a91-409504058bd7
## INFO [10:30:57.870] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.876] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.879] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 82851.815776
## iter 10 value 2427.008893
## iter 20 value 1941.800317
## iter 30 value 1371.860984
## iter 40 value 999.803708
## iter 50 value 664.484474
## iter 60 value 529.288577
## iter 70 value 519.736066
## iter 80 value 514.066099
## iter 90 value 509.919764
## iter 100 value 508.131588
## iter 110 value 507.739739
## iter 120 value 507.076019
## iter 130 value 506.734015
## iter 140 value 506.719786
## iter 150 value 506.469881
## iter 160 value 506.327595
## iter 170 value 497.276104
## iter 180 value 426.107668
## iter 190 value 378.378649
## iter 200 value 342.743280
## iter 210 value 274.390960
## iter 220 value 264.611281
## iter 230 value 261.666456
## iter 240 value 261.296563
## iter 250 value 259.419720
## iter 260 value 256.419176
## iter 270 value 255.678283
## iter 280 value 253.858208
## iter 290 value 234.217247
## iter 300 value 224.781510
## iter 310 value 206.544177
## iter 320 value 179.966789
## iter 330 value 168.241333
## iter 340 value 167.419135
## iter 350 value 166.558991
## iter 360 value 164.576753
## iter 370 value 158.051002
## iter 380 value 155.811985
## final value 154.787705
## stopped after 385 iterations
## INFO [10:30:57.891] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 83914.132562
## iter 10 value 2501.634782
## iter 20 value 1029.441274
## iter 30 value 1018.512320
## iter 40 value 1014.078751
## iter 50 value 1013.134887
## iter 60 value 1012.874428
## iter 70 value 1012.488386
## iter 80 value 998.485956
## iter 90 value 846.915181
## iter 100 value 720.715089
## iter 110 value 601.186668
## iter 120 value 541.722892
## iter 130 value 521.816921
## iter 140 value 518.980504
## iter 150 value 518.091241
## iter 160 value 517.175711
## iter 170 value 516.604823
## iter 180 value 515.918929
## iter 190 value 515.691914
## iter 200 value 509.505593
## iter 210 value 486.283631
## iter 220 value 360.054477
## iter 230 value 295.523147
## iter 240 value 278.790138
## iter 250 value 262.120887
## iter 260 value 249.087525
## iter 270 value 242.162386
## iter 280 value 239.425798
## iter 290 value 238.198187
## iter 300 value 237.841253
## iter 310 value 237.097991
## iter 320 value 237.042165
## iter 330 value 236.889576
## iter 340 value 236.562134
## iter 350 value 236.064088
## iter 360 value 236.027216
## iter 370 value 234.749049
## iter 380 value 229.791031
## final value 228.103805
## stopped after 385 iterations
## INFO [10:30:57.904] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 92870.571610
## iter 10 value 3513.952667
## iter 20 value 1873.011065
## iter 30 value 1709.531614
## iter 40 value 1288.922475
## iter 50 value 928.410459
## iter 60 value 898.135573
## iter 70 value 885.585187
## iter 80 value 875.687035
## iter 90 value 833.572634
## iter 100 value 589.244041
## iter 110 value 557.892832
## iter 120 value 529.384023
## iter 130 value 522.879371
## iter 140 value 515.277426
## iter 150 value 512.842698
## iter 160 value 511.691843
## iter 170 value 511.569958
## iter 180 value 511.023592
## iter 190 value 510.996830
## iter 200 value 510.476516
## iter 210 value 508.212566
## iter 220 value 494.238120
## iter 230 value 477.721250
## iter 240 value 471.808881
## iter 250 value 443.494951
## iter 260 value 433.018420
## iter 270 value 432.614599
## iter 280 value 428.763486
## iter 290 value 422.040828
## iter 300 value 315.266751
## iter 310 value 268.217008
## iter 320 value 254.831666
## iter 330 value 206.450435
## iter 340 value 175.521008
## iter 350 value 168.054449
## iter 360 value 166.860215
## iter 370 value 164.313878
## iter 380 value 162.497127
## final value 162.403116
## stopped after 385 iterations
## INFO [10:30:57.916] [mlr3] Finished benchmark
## INFO [10:30:57.927] [bbotk] Result of batch 3:
## INFO [10:30:57.928] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.928] [bbotk] 7 385 9.508889e-05 13.53424 0 0 0.025
## INFO [10:30:57.928] [bbotk] uhash
## INFO [10:30:57.928] [bbotk] 2515842e-da8d-4267-b343-f0eab52bdddf
## INFO [10:30:57.929] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.936] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.938] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 80935.954379
## final value 9170.979203
## converged
## INFO [10:30:57.945] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 82630.578648
## final value 6343.932271
## converged
## INFO [10:30:57.952] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 94443.643625
## iter 10 value 5906.722812
## iter 20 value 2942.516253
## iter 30 value 2834.641018
## iter 40 value 2592.532102
## iter 50 value 1976.317428
## iter 60 value 1670.269108
## iter 70 value 1460.766664
## iter 80 value 1453.229093
## iter 90 value 1449.800759
## final value 1449.799161
## converged
## INFO [10:30:57.958] [mlr3] Finished benchmark
## INFO [10:30:57.970] [bbotk] Result of batch 4:
## INFO [10:30:57.970] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:57.970] [bbotk] 1 418 6.998396e-06 11.53957 0 0 0.007
## INFO [10:30:57.970] [bbotk] uhash
## INFO [10:30:57.970] [bbotk] 63623ab0-49a7-416c-8ebe-2e29af36f3f4
## INFO [10:30:57.976] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:57.982] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:57.985] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 81152.990761
## iter 10 value 2233.970107
## iter 20 value 1865.508424
## iter 30 value 1863.347020
## iter 40 value 1581.579065
## iter 50 value 1272.688235
## iter 60 value 1240.974399
## iter 70 value 1204.681029
## iter 80 value 1158.034227
## iter 90 value 1144.389230
## iter 100 value 1079.234370
## iter 110 value 706.173037
## iter 120 value 634.020444
## iter 130 value 612.293115
## iter 140 value 577.082736
## iter 150 value 572.467892
## iter 160 value 570.943534
## iter 170 value 569.703753
## iter 180 value 565.178858
## iter 190 value 564.590557
## iter 200 value 564.517777
## iter 210 value 564.514014
## iter 220 value 564.455144
## iter 230 value 564.330105
## iter 240 value 563.796044
## iter 250 value 563.665865
## iter 260 value 562.265473
## iter 270 value 537.898467
## iter 280 value 506.807507
## iter 290 value 505.496923
## iter 300 value 503.842627
## iter 310 value 500.832411
## iter 320 value 500.375541
## final value 500.311543
## stopped after 328 iterations
## INFO [10:30:57.994] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 82729.255932
## iter 10 value 6341.759758
## iter 20 value 1198.840519
## iter 30 value 1035.797671
## iter 40 value 1017.996309
## iter 50 value 975.355250
## iter 60 value 788.617333
## iter 70 value 719.811212
## iter 80 value 657.224883
## iter 90 value 637.068567
## iter 100 value 626.080260
## iter 110 value 601.611604
## iter 120 value 559.536263
## iter 130 value 558.979584
## iter 140 value 558.953196
## iter 150 value 558.828092
## iter 160 value 558.821671
## iter 170 value 558.777501
## final value 558.774641
## converged
## INFO [10:30:58.002] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 91914.228109
## iter 10 value 9265.354834
## iter 20 value 5973.638988
## iter 30 value 2167.638240
## iter 40 value 1753.275049
## iter 50 value 1500.986400
## iter 60 value 1402.456312
## iter 70 value 984.539008
## iter 80 value 964.292779
## iter 90 value 962.698413
## iter 100 value 925.055995
## iter 110 value 924.350479
## iter 120 value 924.339903
## iter 130 value 924.337337
## final value 924.337273
## converged
## INFO [10:30:58.009] [mlr3] Finished benchmark
## INFO [10:30:58.019] [bbotk] Result of batch 5:
## INFO [10:30:58.020] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.020] [bbotk] 2 328 4.676914e-05 8.162926 0 0 0.01
## INFO [10:30:58.020] [bbotk] uhash
## INFO [10:30:58.020] [bbotk] 59f05a5b-9eec-428f-b14e-507954ab1a27
## INFO [10:30:58.022] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.028] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.031] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 84888.770675
## final value 9171.964530
## converged
## INFO [10:30:58.037] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 77103.688980
## iter 10 value 1249.573193
## iter 20 value 554.281542
## iter 30 value 380.962827
## iter 40 value 257.979286
## iter 50 value 150.860021
## iter 60 value 98.978247
## iter 70 value 72.234499
## iter 80 value 56.619634
## iter 90 value 48.597895
## iter 100 value 32.391883
## iter 110 value 24.448233
## iter 120 value 17.571349
## iter 130 value 13.699653
## iter 140 value 13.275343
## iter 150 value 12.525723
## iter 160 value 10.733161
## iter 170 value 7.296750
## iter 180 value 5.443207
## iter 190 value 4.680034
## iter 200 value 4.111229
## iter 210 value 3.697935
## iter 220 value 3.562641
## iter 230 value 3.435893
## iter 240 value 3.188930
## iter 250 value 2.745083
## iter 260 value 2.473560
## iter 270 value 2.434816
## iter 280 value 2.390375
## iter 290 value 2.344311
## iter 300 value 2.293808
## iter 310 value 2.243316
## final value 2.106220
## stopped after 319 iterations
## INFO [10:30:58.051] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 94200.697069
## iter 10 value 1269.671750
## iter 20 value 672.175816
## iter 30 value 556.162088
## iter 40 value 517.007382
## iter 50 value 481.351525
## iter 60 value 433.263375
## iter 70 value 398.815602
## iter 80 value 390.044579
## iter 90 value 365.026276
## iter 100 value 331.786420
## iter 110 value 321.726957
## iter 120 value 320.188740
## iter 130 value 316.725824
## iter 140 value 314.916136
## iter 150 value 296.847433
## iter 160 value 284.472630
## iter 170 value 276.211758
## iter 180 value 274.460865
## iter 190 value 269.613519
## iter 200 value 261.442394
## iter 210 value 193.580230
## iter 220 value 184.443284
## iter 230 value 182.909336
## iter 240 value 179.433158
## iter 250 value 177.730787
## iter 260 value 176.595522
## iter 270 value 176.481095
## iter 280 value 176.395300
## iter 290 value 176.378570
## iter 300 value 176.287339
## iter 310 value 176.135778
## final value 176.014552
## stopped after 319 iterations
## INFO [10:30:58.062] [mlr3] Finished benchmark
## INFO [10:30:58.073] [bbotk] Result of batch 6:
## INFO [10:30:58.074] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.074] [bbotk] 9 319 3.739961e-05 13.10578 0 0 0.017
## INFO [10:30:58.074] [bbotk] uhash
## INFO [10:30:58.074] [bbotk] 02c6053c-554a-48ca-838a-de77071e939c
## INFO [10:30:58.076] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.083] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.085] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 43
## initial value 80058.733362
## iter 10 value 7265.869028
## iter 20 value 1065.148336
## iter 30 value 723.647600
## iter 40 value 548.307665
## iter 50 value 420.977436
## iter 60 value 382.425648
## iter 70 value 378.413316
## iter 80 value 378.016100
## iter 90 value 377.937898
## iter 100 value 377.606890
## iter 110 value 376.533087
## final value 376.515622
## stopped after 113 iterations
## INFO [10:30:58.093] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 43
## initial value 83225.910073
## iter 10 value 2958.401836
## iter 20 value 1129.685175
## iter 30 value 839.179196
## iter 40 value 648.140216
## iter 50 value 589.595917
## iter 60 value 572.373824
## iter 70 value 513.232618
## iter 80 value 448.013850
## iter 90 value 421.126301
## iter 100 value 391.872262
## iter 110 value 355.061726
## final value 350.080451
## stopped after 113 iterations
## INFO [10:30:58.105] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 43
## initial value 88621.145725
## iter 10 value 5371.005162
## iter 20 value 1828.253879
## iter 30 value 1498.765544
## iter 40 value 1454.194465
## iter 50 value 1451.033467
## iter 60 value 1450.975576
## iter 70 value 1450.199830
## iter 80 value 1443.295451
## iter 90 value 1407.845675
## iter 100 value 1276.570586
## iter 110 value 1069.506948
## final value 1025.744681
## stopped after 113 iterations
## INFO [10:30:58.113] [mlr3] Finished benchmark
## INFO [10:30:58.123] [bbotk] Result of batch 7:
## INFO [10:30:58.124] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.124] [bbotk] 6 113 4.914075e-05 7.095884 0 0 0.009
## INFO [10:30:58.124] [bbotk] uhash
## INFO [10:30:58.124] [bbotk] 55254817-f5b5-45e4-aa4d-cef3e1e43340
## INFO [10:30:58.126] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.132] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.135] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 85583.578147
## iter 10 value 9439.287480
## iter 20 value 1978.870291
## iter 30 value 534.037484
## iter 40 value 337.458587
## iter 50 value 264.177388
## iter 60 value 234.586996
## iter 70 value 210.871278
## iter 80 value 190.602324
## iter 90 value 174.050711
## iter 100 value 167.459687
## iter 110 value 152.612594
## iter 120 value 135.574010
## iter 130 value 130.116122
## iter 140 value 128.126803
## iter 150 value 105.304816
## iter 160 value 88.461834
## final value 88.461834
## stopped after 160 iterations
## INFO [10:30:58.145] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 79865.628382
## iter 10 value 2650.254907
## iter 20 value 1360.112036
## iter 30 value 927.536563
## iter 40 value 619.441049
## iter 50 value 415.982188
## iter 60 value 372.364828
## iter 70 value 361.336730
## iter 80 value 351.635448
## iter 90 value 309.886998
## iter 100 value 289.908508
## iter 110 value 286.474517
## iter 120 value 282.744503
## iter 130 value 274.291746
## iter 140 value 266.603869
## iter 150 value 251.040251
## iter 160 value 244.412871
## final value 244.412871
## stopped after 160 iterations
## INFO [10:30:58.154] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 96313.217607
## iter 10 value 4093.661756
## iter 20 value 2055.304473
## iter 30 value 1362.087226
## iter 40 value 1244.428279
## iter 50 value 913.901405
## iter 60 value 777.751831
## iter 70 value 707.153368
## iter 80 value 702.462881
## iter 90 value 697.906649
## iter 100 value 695.422729
## iter 110 value 695.411706
## iter 120 value 695.215349
## iter 130 value 695.144798
## iter 140 value 695.133249
## iter 150 value 694.552419
## iter 160 value 687.962670
## final value 687.962670
## stopped after 160 iterations
## INFO [10:30:58.163] [mlr3] Finished benchmark
## INFO [10:30:58.174] [bbotk] Result of batch 8:
## INFO [10:30:58.175] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.175] [bbotk] 9 160 1.586458e-05 10.05934 0 0 0.016
## INFO [10:30:58.175] [bbotk] uhash
## INFO [10:30:58.175] [bbotk] 840133b2-f0a4-4df3-8595-9cc71dd6a9a1
## INFO [10:30:58.177] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.184] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.186] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 50
## initial value 81854.956286
## iter 10 value 3441.243815
## iter 20 value 2025.853360
## iter 30 value 1705.623000
## iter 40 value 1210.412448
## iter 50 value 1119.506058
## iter 60 value 1104.357786
## iter 70 value 1102.267749
## iter 80 value 1102.073905
## iter 90 value 1101.490671
## iter 100 value 1101.484255
## iter 100 value 1101.484248
## final value 1101.484173
## converged
## INFO [10:30:58.195] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 50
## initial value 77519.552539
## iter 10 value 971.398890
## iter 20 value 461.730613
## iter 30 value 340.650305
## iter 40 value 285.975664
## iter 50 value 275.258106
## iter 60 value 272.733784
## iter 70 value 268.035696
## iter 80 value 266.097605
## iter 90 value 264.566735
## iter 100 value 262.936745
## iter 110 value 262.587945
## iter 120 value 261.718314
## iter 130 value 255.516875
## iter 140 value 228.215447
## iter 150 value 214.975204
## iter 160 value 205.089303
## iter 170 value 187.127273
## iter 180 value 169.341094
## iter 190 value 163.139088
## iter 200 value 159.431693
## iter 210 value 158.941087
## iter 220 value 158.898480
## iter 230 value 158.613962
## iter 240 value 158.406905
## iter 250 value 158.209253
## iter 260 value 157.946905
## iter 270 value 157.696131
## iter 280 value 157.515381
## iter 290 value 157.332942
## iter 300 value 156.909241
## iter 310 value 156.594101
## iter 320 value 156.493194
## iter 330 value 156.407409
## iter 340 value 156.214013
## iter 350 value 156.083265
## iter 360 value 155.993967
## iter 370 value 155.931973
## iter 380 value 155.888490
## iter 390 value 155.821365
## iter 400 value 155.695080
## iter 410 value 155.646839
## iter 420 value 155.591171
## final value 155.478711
## stopped after 427 iterations
## INFO [10:30:58.208] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 50
## initial value 92835.487492
## iter 10 value 3102.546495
## iter 20 value 1728.849476
## iter 30 value 1353.935328
## iter 40 value 1348.900604
## iter 50 value 1348.398573
## iter 60 value 1340.923903
## iter 70 value 1026.905918
## iter 80 value 947.128681
## iter 90 value 935.515009
## iter 100 value 935.013703
## iter 110 value 934.929120
## iter 120 value 933.700294
## iter 130 value 933.402257
## iter 140 value 933.271175
## iter 150 value 932.457190
## iter 160 value 926.326999
## iter 170 value 856.051193
## iter 180 value 585.539203
## iter 190 value 521.637444
## iter 200 value 479.554137
## iter 210 value 434.483563
## iter 220 value 298.477965
## iter 230 value 261.381535
## iter 240 value 253.986047
## iter 250 value 251.746004
## iter 260 value 247.584228
## iter 270 value 247.096862
## iter 280 value 246.993978
## iter 290 value 246.977807
## iter 300 value 246.960663
## iter 310 value 246.951936
## iter 320 value 246.904904
## iter 330 value 246.849720
## iter 340 value 246.566759
## iter 350 value 236.836075
## iter 360 value 190.160990
## iter 370 value 158.983178
## iter 380 value 152.940942
## iter 390 value 152.239588
## iter 400 value 151.619692
## iter 410 value 148.090319
## iter 420 value 129.703199
## final value 119.342220
## stopped after 427 iterations
## INFO [10:30:58.220] [mlr3] Finished benchmark
## INFO [10:30:58.232] [bbotk] Result of batch 9:
## INFO [10:30:58.232] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.232] [bbotk] 7 427 5.397219e-05 10.64276 0 0 0.02
## INFO [10:30:58.232] [bbotk] uhash
## INFO [10:30:58.232] [bbotk] 7c0251d7-0278-439a-8e3b-3ba938dfd0f9
## INFO [10:30:58.234] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.244] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.247] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 80523.975956
## iter 10 value 8195.900253
## iter 20 value 3016.372736
## iter 30 value 2952.111091
## iter 40 value 1903.832271
## iter 50 value 1585.206982
## iter 60 value 1158.670405
## iter 70 value 1117.990378
## iter 80 value 1102.379160
## iter 90 value 1100.531944
## iter 100 value 1099.239275
## final value 1099.238328
## converged
## INFO [10:30:58.254] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 85311.370974
## iter 10 value 1311.623641
## iter 20 value 1035.353478
## iter 30 value 1026.890523
## iter 40 value 1016.231998
## iter 50 value 1013.829450
## iter 60 value 1012.025514
## iter 70 value 1011.503788
## iter 80 value 1011.380420
## iter 90 value 1011.263341
## iter 100 value 1011.257609
## iter 110 value 1011.238671
## iter 110 value 1011.238664
## final value 1011.238579
## converged
## INFO [10:30:58.262] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 93799.518279
## iter 10 value 3931.336598
## iter 20 value 2734.198309
## iter 30 value 2236.442508
## iter 40 value 1721.961296
## iter 50 value 1506.192813
## iter 60 value 1455.441861
## iter 70 value 1450.572033
## iter 80 value 1449.914891
## final value 1449.914810
## converged
## INFO [10:30:58.268] [mlr3] Finished benchmark
## INFO [10:30:58.278] [bbotk] Result of batch 10:
## INFO [10:30:58.279] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.279] [bbotk] 1 195 1.102321e-05 6.280607 0 0 0.007
## INFO [10:30:58.279] [bbotk] uhash
## INFO [10:30:58.279] [bbotk] 1a86fb22-4d81-4d7e-8886-afa57224cf92
## INFO [10:30:58.281] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.287] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.290] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 64
## initial value 85332.036819
## iter 10 value 2334.132930
## iter 20 value 1055.548207
## iter 30 value 438.727058
## iter 40 value 350.173378
## iter 50 value 291.161020
## iter 60 value 231.477422
## iter 70 value 197.721515
## iter 80 value 163.476828
## iter 90 value 140.730047
## iter 100 value 134.031285
## iter 110 value 132.138111
## iter 120 value 127.877250
## iter 130 value 127.265938
## iter 140 value 127.097511
## iter 150 value 126.951634
## iter 160 value 126.391436
## iter 170 value 124.821098
## iter 180 value 124.699614
## iter 190 value 123.083551
## iter 200 value 121.604725
## iter 210 value 121.196543
## iter 220 value 117.478654
## iter 230 value 103.919237
## iter 240 value 96.746100
## iter 250 value 91.146696
## iter 260 value 83.420168
## iter 270 value 80.767534
## iter 280 value 79.733568
## iter 290 value 78.014247
## iter 300 value 77.011303
## iter 310 value 74.985613
## final value 74.985613
## stopped after 310 iterations
## INFO [10:30:58.303] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 64
## initial value 81766.020614
## iter 10 value 1245.149170
## iter 20 value 638.115800
## iter 30 value 450.280931
## iter 40 value 382.967441
## iter 50 value 352.129176
## iter 60 value 314.503051
## iter 70 value 297.777646
## iter 80 value 281.194267
## iter 90 value 265.828422
## iter 100 value 252.843166
## iter 110 value 248.691966
## iter 120 value 246.990972
## iter 130 value 242.629926
## iter 140 value 231.656793
## iter 150 value 223.651919
## iter 160 value 222.694916
## iter 170 value 219.303117
## iter 180 value 214.659502
## iter 190 value 211.055023
## iter 200 value 205.863707
## iter 210 value 203.853056
## iter 220 value 202.631211
## iter 230 value 202.170843
## iter 240 value 192.347706
## iter 250 value 157.077336
## iter 260 value 133.905950
## iter 270 value 124.461519
## iter 280 value 120.079376
## iter 290 value 114.446664
## iter 300 value 110.940467
## iter 310 value 107.267513
## final value 107.267513
## stopped after 310 iterations
## INFO [10:30:58.316] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 64
## initial value 91622.769164
## iter 10 value 2281.520721
## iter 20 value 1457.817911
## iter 30 value 577.446499
## iter 40 value 458.863228
## iter 50 value 351.388959
## iter 60 value 291.698326
## iter 70 value 264.971327
## iter 80 value 221.089821
## iter 90 value 175.156723
## iter 100 value 154.564350
## iter 110 value 119.359468
## iter 120 value 98.164849
## iter 130 value 91.452436
## iter 140 value 89.835977
## iter 150 value 86.075935
## iter 160 value 83.458377
## iter 170 value 80.855372
## iter 180 value 80.052169
## iter 190 value 78.554231
## iter 200 value 76.534890
## iter 210 value 70.159532
## iter 220 value 67.032355
## iter 230 value 62.813156
## iter 240 value 58.094364
## iter 250 value 51.315428
## iter 260 value 45.914997
## iter 270 value 44.360041
## iter 280 value 41.427623
## iter 290 value 37.450721
## iter 300 value 35.611997
## iter 310 value 34.281796
## final value 34.281796
## stopped after 310 iterations
## INFO [10:30:58.329] [mlr3] Finished benchmark
## INFO [10:30:58.340] [bbotk] Result of batch 11:
## INFO [10:30:58.341] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.341] [bbotk] 9 310 8.434946e-05 13.14123 0 0 0.025
## INFO [10:30:58.341] [bbotk] uhash
## INFO [10:30:58.341] [bbotk] 85ce3009-4f90-4b69-b18f-0776c56575db
## INFO [10:30:58.343] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.349] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.352] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 57
## initial value 83240.260064
## iter 10 value 2078.637880
## iter 20 value 1022.905366
## iter 30 value 852.600687
## iter 40 value 634.801885
## iter 50 value 510.802464
## iter 60 value 469.524967
## iter 70 value 450.663127
## iter 80 value 442.494646
## iter 90 value 441.411817
## iter 100 value 439.041030
## iter 110 value 411.705029
## iter 120 value 289.079975
## iter 130 value 276.198592
## iter 140 value 236.004309
## iter 150 value 203.686520
## iter 160 value 203.348779
## iter 170 value 203.114501
## iter 180 value 202.436849
## iter 190 value 200.789028
## iter 200 value 169.787992
## iter 210 value 142.991466
## iter 220 value 135.097581
## iter 230 value 133.131910
## iter 240 value 133.047362
## iter 250 value 132.857610
## iter 260 value 132.693907
## iter 270 value 132.239296
## iter 280 value 131.918564
## iter 290 value 130.850596
## iter 300 value 130.748542
## iter 310 value 130.548969
## iter 320 value 130.401157
## iter 330 value 130.018122
## iter 340 value 129.604816
## iter 350 value 129.422430
## iter 360 value 129.373565
## iter 370 value 129.315370
## iter 380 value 129.295179
## iter 390 value 129.217735
## iter 400 value 129.213500
## iter 410 value 129.208857
## final value 129.207880
## stopped after 412 iterations
## INFO [10:30:58.366] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 57
## initial value 86093.605977
## iter 10 value 1094.905272
## iter 20 value 939.482471
## iter 30 value 656.714996
## iter 40 value 440.545439
## iter 50 value 414.915857
## iter 60 value 392.018788
## iter 70 value 385.630925
## iter 80 value 379.680882
## iter 90 value 376.020597
## iter 100 value 374.725014
## iter 110 value 373.890888
## iter 120 value 373.740727
## iter 130 value 373.729263
## iter 140 value 373.646281
## iter 150 value 364.517238
## iter 160 value 355.976536
## iter 170 value 268.068183
## iter 180 value 218.616150
## iter 190 value 193.852924
## iter 200 value 158.745967
## iter 210 value 154.088903
## iter 220 value 152.200804
## iter 230 value 151.919182
## iter 240 value 149.609429
## iter 250 value 147.557461
## iter 260 value 147.299959
## iter 270 value 147.035002
## iter 280 value 146.963956
## iter 290 value 146.945415
## iter 300 value 146.916062
## iter 310 value 146.865813
## iter 320 value 146.785462
## iter 330 value 146.762452
## iter 340 value 146.549176
## iter 350 value 146.515684
## iter 360 value 146.384052
## iter 370 value 145.712601
## iter 380 value 129.706170
## iter 390 value 112.996059
## iter 400 value 99.611489
## iter 410 value 88.649410
## final value 88.134575
## stopped after 412 iterations
## INFO [10:30:58.384] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 57
## initial value 94337.243042
## iter 10 value 6100.727353
## iter 20 value 2066.671722
## iter 30 value 1805.608649
## iter 40 value 1498.660731
## iter 50 value 1434.213295
## iter 60 value 1015.198559
## iter 70 value 961.758697
## iter 80 value 957.272315
## iter 90 value 955.018533
## iter 100 value 953.104049
## iter 110 value 940.379810
## iter 120 value 933.871151
## iter 130 value 931.114412
## iter 140 value 923.161491
## iter 150 value 912.208995
## iter 160 value 894.421787
## iter 170 value 731.490901
## iter 180 value 696.056374
## iter 190 value 692.877096
## iter 200 value 692.602552
## iter 210 value 692.494021
## iter 220 value 692.366559
## iter 230 value 692.328027
## final value 692.326855
## converged
## INFO [10:30:58.394] [mlr3] Finished benchmark
## INFO [10:30:58.405] [bbotk] Result of batch 12:
## INFO [10:30:58.406] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.406] [bbotk] 8 412 2.129418e-05 7.393695 0 0 0.028
## INFO [10:30:58.406] [bbotk] uhash
## INFO [10:30:58.406] [bbotk] 1756d543-fb24-47de-9124-3725633a933e
## INFO [10:30:58.408] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.414] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.417] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 36
## initial value 82605.883146
## iter 10 value 2299.028853
## iter 20 value 1101.393004
## iter 30 value 730.243474
## iter 40 value 475.813127
## iter 50 value 420.811676
## iter 60 value 395.401851
## iter 70 value 392.041325
## iter 80 value 386.012698
## iter 90 value 383.664077
## iter 100 value 383.048071
## iter 110 value 382.614491
## iter 120 value 381.818880
## iter 130 value 374.519694
## iter 140 value 349.868095
## iter 150 value 211.948605
## iter 160 value 180.030642
## iter 170 value 158.296315
## iter 180 value 152.538215
## iter 190 value 146.689974
## iter 200 value 144.378473
## iter 210 value 143.333414
## iter 220 value 142.847998
## iter 230 value 142.434505
## iter 240 value 142.147856
## iter 250 value 142.147077
## iter 260 value 142.141008
## iter 270 value 141.804441
## iter 280 value 141.605330
## iter 290 value 140.889719
## iter 300 value 140.743397
## iter 310 value 140.705409
## iter 320 value 140.695195
## iter 330 value 140.693695
## iter 340 value 140.688448
## iter 350 value 140.671610
## iter 360 value 140.663856
## iter 370 value 140.651987
## iter 380 value 140.649542
## final value 140.649251
## converged
## INFO [10:30:58.429] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 36
## initial value 80345.766132
## iter 10 value 7437.720019
## iter 20 value 4795.784160
## iter 30 value 1204.909165
## iter 40 value 1047.178191
## iter 50 value 1023.793989
## iter 60 value 1015.549449
## iter 70 value 1012.623544
## iter 80 value 974.138312
## iter 90 value 728.260671
## iter 100 value 673.237442
## iter 110 value 626.077590
## iter 120 value 598.433499
## iter 130 value 582.965530
## iter 140 value 524.317443
## iter 150 value 517.467504
## iter 160 value 515.972262
## iter 170 value 510.046862
## iter 180 value 506.131322
## iter 190 value 503.866340
## iter 200 value 503.714249
## iter 210 value 503.101551
## iter 220 value 501.464223
## iter 230 value 494.170284
## iter 240 value 461.535807
## iter 250 value 406.152091
## iter 260 value 340.945556
## iter 270 value 312.507098
## iter 280 value 301.061305
## iter 290 value 299.038548
## iter 300 value 296.668821
## iter 310 value 294.392560
## iter 320 value 292.509533
## iter 330 value 290.639724
## iter 340 value 290.009358
## iter 350 value 289.733088
## iter 360 value 289.631855
## iter 370 value 289.172893
## iter 380 value 288.837362
## iter 390 value 288.807075
## iter 400 value 288.529515
## iter 410 value 285.084383
## iter 420 value 279.991393
## iter 430 value 272.641893
## iter 440 value 263.693311
## final value 256.983821
## stopped after 447 iterations
## INFO [10:30:58.442] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 36
## initial value 95275.353135
## iter 10 value 7011.147997
## iter 20 value 2702.778583
## iter 30 value 2024.347109
## iter 40 value 1630.061157
## iter 50 value 1461.063865
## iter 60 value 1452.330361
## iter 70 value 1451.871688
## iter 80 value 1451.526547
## final value 1451.524176
## converged
## INFO [10:30:58.449] [mlr3] Finished benchmark
## INFO [10:30:58.459] [bbotk] Result of batch 13:
## INFO [10:30:58.460] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.460] [bbotk] 5 447 7.190734e-05 6.817563 0 0 0.017
## INFO [10:30:58.460] [bbotk] uhash
## INFO [10:30:58.460] [bbotk] 1e813db5-f7e4-4bff-a1c4-261d1a532970
## INFO [10:30:58.462] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.469] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.471] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 29
## initial value 84000.213615
## iter 10 value 4028.994496
## iter 20 value 1207.218749
## iter 30 value 812.670363
## iter 40 value 501.856911
## iter 50 value 344.672119
## iter 60 value 262.810058
## iter 70 value 237.884571
## iter 80 value 202.058418
## iter 90 value 189.981175
## iter 100 value 189.178933
## iter 110 value 186.892972
## iter 120 value 186.365177
## iter 130 value 186.326613
## iter 140 value 186.079310
## iter 150 value 185.831712
## iter 160 value 185.280828
## iter 170 value 185.143727
## final value 185.124979
## converged
## INFO [10:30:58.480] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 29
## initial value 80431.931558
## iter 10 value 2688.947115
## iter 20 value 1273.068906
## iter 30 value 927.507909
## iter 40 value 864.068747
## iter 50 value 854.554936
## iter 60 value 841.278264
## iter 70 value 838.272630
## iter 80 value 831.936713
## iter 90 value 827.472737
## iter 100 value 825.675864
## iter 110 value 825.625663
## iter 120 value 825.613105
## iter 130 value 789.787765
## iter 140 value 587.425193
## iter 150 value 480.868719
## iter 160 value 477.143965
## iter 170 value 474.255684
## iter 180 value 473.002058
## iter 190 value 472.959607
## iter 200 value 472.938235
## iter 210 value 472.340447
## iter 220 value 471.629304
## iter 230 value 469.523682
## iter 240 value 464.835500
## iter 250 value 461.578540
## iter 260 value 457.372024
## iter 270 value 456.859438
## iter 280 value 453.403201
## iter 290 value 419.142278
## iter 300 value 373.349491
## iter 310 value 333.712419
## iter 320 value 329.838445
## iter 330 value 328.531323
## iter 340 value 328.450329
## iter 350 value 328.117431
## iter 360 value 326.490444
## final value 323.340707
## stopped after 367 iterations
## INFO [10:30:58.490] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 29
## initial value 93794.914276
## final value 9265.109242
## converged
## INFO [10:30:58.496] [mlr3] Finished benchmark
## INFO [10:30:58.511] [bbotk] Result of batch 14:
## INFO [10:30:58.512] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.512] [bbotk] 4 367 4.274419e-05 15.83837 0 0 0.012
## INFO [10:30:58.512] [bbotk] uhash
## INFO [10:30:58.512] [bbotk] 28cefccf-3554-4a89-98a4-f755474e4d0f
## INFO [10:30:58.513] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.520] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.523] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 81146.802604
## final value 9171.030918
## converged
## INFO [10:30:58.529] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 82889.077222
## iter 10 value 2399.341829
## iter 20 value 1685.065398
## iter 30 value 1637.984272
## iter 40 value 1625.138129
## iter 50 value 1625.097457
## iter 60 value 1624.867240
## iter 70 value 1624.692636
## iter 80 value 1624.629374
## iter 90 value 1624.493266
## iter 100 value 1624.266264
## iter 110 value 1501.878702
## iter 120 value 1473.203350
## iter 130 value 1384.251920
## iter 140 value 1058.950509
## iter 150 value 1030.190859
## iter 160 value 1020.573619
## iter 170 value 1015.796796
## iter 180 value 1012.933915
## final value 1012.649440
## stopped after 186 iterations
## INFO [10:30:58.537] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 92643.485747
## iter 10 value 3603.608415
## iter 20 value 1990.192396
## iter 30 value 1529.808400
## iter 40 value 1465.460874
## iter 50 value 1454.454954
## iter 60 value 1452.259338
## final value 1452.198089
## converged
## INFO [10:30:58.543] [mlr3] Finished benchmark
## INFO [10:30:58.554] [bbotk] Result of batch 15:
## INFO [10:30:58.554] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.554] [bbotk] 1 186 7.421892e-05 8.333121 0 0 0.008
## INFO [10:30:58.554] [bbotk] uhash
## INFO [10:30:58.554] [bbotk] 518dd4e5-f86a-4c39-ba6b-251178d740ff
## INFO [10:30:58.556] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.563] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.566] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 71
## initial value 81235.270927
## iter 10 value 912.814422
## iter 20 value 456.934938
## iter 30 value 278.613482
## iter 40 value 139.151583
## iter 50 value 109.558774
## iter 60 value 78.757892
## iter 70 value 50.823138
## iter 80 value 47.069767
## iter 90 value 45.897250
## iter 100 value 43.150300
## iter 110 value 41.644004
## iter 120 value 41.272292
## iter 130 value 40.988001
## iter 140 value 40.820413
## iter 150 value 40.642881
## iter 160 value 40.577751
## iter 170 value 40.339228
## iter 180 value 40.039156
## iter 190 value 39.300604
## iter 200 value 28.068058
## iter 210 value 23.227708
## iter 220 value 20.063933
## iter 230 value 18.298598
## iter 240 value 17.881870
## iter 250 value 17.572338
## iter 260 value 17.061925
## iter 270 value 16.659186
## iter 280 value 15.985624
## iter 290 value 15.422290
## iter 300 value 15.163701
## iter 310 value 13.733838
## iter 320 value 11.928510
## iter 330 value 11.438988
## iter 340 value 11.063337
## iter 350 value 10.901452
## iter 360 value 10.742113
## iter 370 value 10.493990
## iter 380 value 10.209970
## iter 390 value 10.019498
## iter 400 value 9.630087
## iter 410 value 9.023178
## iter 420 value 7.850952
## iter 430 value 6.628482
## iter 440 value 6.575020
## final value 6.560884
## stopped after 442 iterations
## INFO [10:30:58.582] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 71
## initial value 82910.052895
## iter 10 value 2574.002124
## iter 20 value 1051.666101
## iter 30 value 1025.498089
## iter 40 value 1017.851997
## iter 50 value 1012.740382
## iter 60 value 1012.037099
## iter 70 value 1011.886403
## iter 80 value 1004.434851
## iter 90 value 900.296177
## iter 100 value 803.748927
## iter 110 value 734.193413
## iter 120 value 666.896669
## iter 130 value 655.941088
## iter 140 value 654.660223
## iter 150 value 535.711408
## iter 160 value 464.109495
## iter 170 value 393.666708
## iter 180 value 358.912274
## iter 190 value 351.032484
## iter 200 value 347.898773
## iter 210 value 346.916326
## iter 220 value 346.812071
## iter 230 value 346.743680
## iter 240 value 342.979135
## iter 250 value 291.291314
## iter 260 value 269.659161
## iter 270 value 267.315706
## iter 280 value 262.998536
## iter 290 value 261.266320
## iter 300 value 259.278605
## iter 310 value 258.024106
## iter 320 value 256.999232
## iter 330 value 255.697475
## iter 340 value 252.353080
## iter 350 value 216.131906
## iter 360 value 201.893775
## iter 370 value 199.298361
## iter 380 value 194.542438
## iter 390 value 183.171829
## iter 400 value 164.870569
## iter 410 value 143.140414
## iter 420 value 129.211321
## iter 430 value 119.232424
## iter 440 value 108.477007
## final value 108.055647
## stopped after 442 iterations
## INFO [10:30:58.599] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 71
## initial value 94774.750764
## iter 10 value 1285.002738
## iter 20 value 708.817398
## iter 30 value 357.305533
## iter 40 value 154.475227
## iter 50 value 94.921131
## iter 60 value 81.259026
## iter 70 value 79.709264
## iter 80 value 73.046123
## iter 90 value 58.157763
## iter 100 value 39.231891
## iter 110 value 28.029038
## iter 120 value 24.548787
## iter 130 value 21.652630
## iter 140 value 19.994324
## iter 150 value 19.723187
## iter 160 value 19.529059
## iter 170 value 19.065189
## iter 180 value 18.632029
## iter 190 value 18.145765
## iter 200 value 17.804955
## iter 210 value 17.560369
## iter 220 value 17.279343
## iter 230 value 16.953143
## iter 240 value 16.741426
## iter 250 value 16.529141
## iter 260 value 16.130509
## iter 270 value 15.630801
## iter 280 value 15.359086
## iter 290 value 15.106300
## iter 300 value 15.070718
## iter 310 value 14.992705
## iter 320 value 14.863684
## iter 330 value 14.762216
## iter 340 value 14.403929
## iter 350 value 14.146112
## iter 360 value 13.964799
## iter 370 value 13.784822
## iter 380 value 13.672426
## iter 390 value 13.574701
## iter 400 value 13.472264
## iter 410 value 13.391614
## iter 420 value 13.320149
## iter 430 value 13.289155
## iter 440 value 13.288388
## final value 13.288274
## stopped after 442 iterations
## INFO [10:30:58.615] [mlr3] Finished benchmark
## INFO [10:30:58.626] [bbotk] Result of batch 16:
## INFO [10:30:58.627] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.627] [bbotk] 10 442 8.188255e-05 9.570173 0 0 0.034
## INFO [10:30:58.627] [bbotk] uhash
## INFO [10:30:58.627] [bbotk] 12a4b18c-f0f2-4632-8f3a-d80a11aede0d
## INFO [10:30:58.628] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.639] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.641] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 80789.984492
## final value 9171.086456
## converged
## INFO [10:30:58.648] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 80503.490483
## final value 6343.969083
## converged
## INFO [10:30:58.654] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 94892.677785
## final value 9265.558866
## converged
## INFO [10:30:58.660] [mlr3] Finished benchmark
## INFO [10:30:58.671] [bbotk] Result of batch 17:
## INFO [10:30:58.671] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.671] [bbotk] 1 411 3.094475e-05 14.19413 0 0 0.005
## INFO [10:30:58.671] [bbotk] uhash
## INFO [10:30:58.671] [bbotk] 98db7291-5aca-4577-ba20-ad6e483545a3
## INFO [10:30:58.673] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.680] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.682] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 8
## initial value 81927.423305
## iter 10 value 5118.967572
## iter 20 value 2717.304490
## iter 30 value 2151.487097
## iter 40 value 1701.048557
## iter 50 value 1344.032850
## iter 60 value 1136.203756
## iter 70 value 1112.008925
## iter 80 value 1103.550291
## iter 90 value 1100.891302
## iter 100 value 1100.278063
## iter 110 value 1099.899566
## iter 120 value 1099.866862
## iter 130 value 1099.840229
## final value 1099.839883
## converged
## INFO [10:30:58.690] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 8
## initial value 82372.656337
## iter 10 value 1788.183691
## iter 20 value 1752.651269
## iter 30 value 1719.484297
## iter 40 value 1679.523400
## iter 50 value 1677.106696
## iter 60 value 1632.931869
## iter 70 value 1183.738290
## iter 80 value 1034.846786
## iter 90 value 1024.569277
## iter 100 value 1018.288812
## iter 110 value 1013.542301
## iter 120 value 1012.538578
## iter 130 value 1011.699411
## iter 140 value 1011.675617
## iter 150 value 1011.598221
## final value 1011.597813
## converged
## INFO [10:30:58.697] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 8
## initial value 93793.915215
## iter 10 value 3260.984504
## iter 20 value 2832.247664
## iter 30 value 2534.623048
## iter 40 value 2060.551669
## iter 50 value 1816.586804
## iter 60 value 1490.528663
## iter 70 value 1459.789424
## iter 80 value 1452.332027
## iter 90 value 1450.938555
## final value 1450.779757
## converged
## INFO [10:30:58.704] [mlr3] Finished benchmark
## INFO [10:30:58.715] [bbotk] Result of batch 18:
## INFO [10:30:58.716] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.716] [bbotk] 1 466 6.912196e-05 6.28995 0 0 0.007
## INFO [10:30:58.716] [bbotk] uhash
## INFO [10:30:58.716] [bbotk] 9a93bd87-f7c6-44c2-abed-bd9922f73bfb
## INFO [10:30:58.717] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.724] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.727] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 83414.098976
## iter 10 value 3238.673066
## iter 20 value 1586.091787
## iter 30 value 1096.990595
## iter 40 value 732.009044
## iter 50 value 594.740559
## iter 60 value 565.479831
## iter 70 value 561.223873
## iter 80 value 560.938215
## iter 90 value 560.470688
## iter 100 value 560.461268
## iter 110 value 560.460995
## iter 120 value 560.455688
## final value 560.455331
## converged
## INFO [10:30:58.735] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 81736.947154
## iter 10 value 1451.338346
## iter 20 value 904.985199
## iter 30 value 790.083187
## iter 40 value 730.524303
## iter 50 value 706.344254
## iter 60 value 690.439276
## iter 70 value 680.850956
## iter 80 value 654.298027
## iter 90 value 580.240873
## iter 100 value 561.466043
## iter 110 value 561.035061
## iter 120 value 560.746410
## iter 130 value 559.696223
## iter 140 value 559.059608
## iter 150 value 559.038769
## iter 160 value 558.881792
## iter 170 value 558.772213
## iter 180 value 558.770273
## iter 190 value 558.689658
## iter 200 value 558.663485
## iter 210 value 558.636769
## iter 220 value 558.631858
## iter 230 value 558.625716
## final value 558.624003
## converged
## INFO [10:30:58.743] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 90683.277863
## iter 10 value 3730.546781
## iter 20 value 2980.146498
## iter 30 value 2897.937852
## iter 40 value 2809.721779
## iter 50 value 2463.125052
## iter 60 value 2168.660029
## iter 70 value 1617.899095
## iter 80 value 1466.281802
## iter 90 value 1454.809457
## iter 100 value 1450.563972
## iter 110 value 1450.465070
## iter 120 value 1450.455775
## iter 120 value 1450.455765
## final value 1450.455696
## converged
## INFO [10:30:58.750] [mlr3] Finished benchmark
## INFO [10:30:58.764] [bbotk] Result of batch 19:
## INFO [10:30:58.765] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.765] [bbotk] 2 392 4.004162e-05 6.199296 0 0 0.01
## INFO [10:30:58.765] [bbotk] uhash
## INFO [10:30:58.765] [bbotk] 7dfcd219-2cd2-477b-a4cd-5dd41c2f2b2a
## INFO [10:30:58.767] [bbotk] Evaluating 1 configuration(s)
## INFO [10:30:58.774] [mlr3] Running benchmark with 3 resampling iterations
## INFO [10:30:58.776] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 1/3)
## # weights: 15
## initial value 81138.677642
## iter 10 value 3466.368660
## iter 20 value 2298.655441
## iter 30 value 2045.962058
## iter 40 value 1351.203437
## iter 50 value 1146.843858
## iter 60 value 1104.556522
## iter 70 value 1100.480968
## iter 80 value 1099.466484
## iter 90 value 1099.417540
## iter 100 value 1099.273440
## iter 110 value 1099.260242
## final value 1099.257148
## converged
## INFO [10:30:58.784] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 2/3)
## # weights: 15
## initial value 81362.578157
## iter 10 value 2358.628498
## iter 20 value 1524.616772
## iter 30 value 1126.956176
## iter 40 value 946.541185
## iter 50 value 876.873100
## iter 60 value 831.855761
## iter 70 value 686.442082
## iter 80 value 590.918466
## iter 90 value 566.369560
## iter 100 value 537.737598
## iter 110 value 527.871585
## final value 526.354608
## stopped after 119 iterations
## INFO [10:30:58.792] [mlr3] Applying learner 'regr.nnet' on task 'cereal' (iter 3/3)
## # weights: 15
## initial value 93108.428130
## iter 10 value 5065.343080
## iter 20 value 3076.461628
## iter 30 value 2390.909365
## iter 40 value 1880.901296
## iter 50 value 1544.591746
## iter 60 value 1464.356775
## iter 70 value 1451.233243
## iter 80 value 1450.415528
## final value 1450.399494
## converged
## INFO [10:30:58.798] [mlr3] Finished benchmark
## INFO [10:30:58.809] [bbotk] Result of batch 20:
## INFO [10:30:58.809] [bbotk] size maxit decay regr.rmse warnings errors runtime_learners
## INFO [10:30:58.809] [bbotk] 2 119 4.546635e-05 5.732408 0 0 0.008
## INFO [10:30:58.809] [bbotk] uhash
## INFO [10:30:58.809] [bbotk] 62662a5a-d625-4270-86eb-6b253d062c66
## INFO [10:30:58.813] [bbotk] Finished optimizing after 20 evaluation(s)
## INFO [10:30:58.813] [bbotk] Result:
## INFO [10:30:58.813] [bbotk] size maxit decay learner_param_vals x_domain regr.rmse
## INFO [10:30:58.813] [bbotk] 2 119 4.546635e-05 <list[3]> <list[3]> 5.732408
## # weights: 15
## initial value 127815.151906
## final value 12456.841180
## convergedWe can extract the results of the tuning process (the inner cross validation) as follows:
## Extract tuning results
extract_inner_tuning_results(cereal_nn)[ , list(maxit, decay, size, regr.rmse)]## maxit decay size regr.rmse
## 1: 257 8.446055e-05 5 7.535631
## 2: 457 3.549095e-05 4 7.445906
## 3: 300 4.119386e-05 3 8.295178
## 4: 373 4.830053e-05 2 6.574380
## 5: 119 4.546635e-05 2 5.732408From these results, it would appear that the last set of parameters gives the best result (lowest RMSE). However, when we extract the RMSE for the test set as follows, this has the highest test RMSE, suggesting that these parameters overfit the model.
In other words, the model fits the training data well, but it does not generalize/predict well.
## Test Data RMSE
cereal_nn$score(msr_rmse)[ , list(regr.rmse)]## regr.rmse
## 1: 8.753778
## 2: 5.793959
## 3: 8.691641
## 4: 8.885114
## 5: 13.075462In this case, the results of the 2nd outer fold (lowest RMSE score) have the lowest error. We will build our model using this.
## Extract the maxit, decay, and size from model 1 to build our full model
lrn_nn <- lrn("regr.nnet",
size = extract_inner_tuning_results(cereal_nn)[2]$size,
maxit = extract_inner_tuning_results(cereal_nn)[2]$maxit,
decay = extract_inner_tuning_results(cereal_nn)[2]$decay)## Full Model Build
cereal_nn.full = lrn_nn$train(cereal_task)## # weights: 29
## initial value 153249.633453
## iter 10 value 3722.204564
## iter 20 value 2178.182772
## iter 30 value 1875.558405
## iter 40 value 1733.728010
## iter 50 value 1616.705206
## iter 60 value 1602.685360
## iter 70 value 1595.256919
## iter 80 value 1476.425707
## iter 90 value 1338.751958
## iter 100 value 1224.078138
## iter 110 value 1194.835285
## iter 120 value 1184.841338
## iter 130 value 1181.809025
## iter 140 value 1161.018764
## iter 150 value 1148.752936
## iter 160 value 1131.352144
## iter 170 value 1123.524452
## iter 180 value 1121.432264
## final value 1121.431939
## converged[Optional section] The final model we obtained is in a format that is quite hard to visualize. You can show the network by first downloading the following function:
## Download the nnet visualization package/tool from github
## Requires devtools package
library(devtools)## Loading required package: usethisdevtools::source_url('https://gist.githubusercontent.com/Peque/41a9e20d6687f2f3108d/raw/85e14f3a292e126f1454864427e3a189c2fe33f3/nnet_plot_update.r')## ℹ SHA-1 hash of file is "bf3c7b8ac910823b729e3ce73bb6ab5e6955ad3d"## Load the required package
library(nnet)
## Rebuild the model
cereal_nn2 = nnet(rating ~ .,
scaled_data,
size = extract_inner_tuning_results(cereal_nn)[2]$size,
maxit = extract_inner_tuning_results(cereal_nn)[2]$maxit,
decay = extract_inner_tuning_results(cereal_nn)[2]$decay)## # weights: 29
## initial value 151658.678214
## iter 10 value 148676.785788
## iter 20 value 148668.864492
## final value 148668.775844
## converged##Neural Network Plot
plot(cereal_nn2)## Loading required package: scales## Loading required package: reshape##
## Attaching package: 'reshape'## The following object is masked from 'package:dplyr':
##
## rename
Neural Network Classification
Next, we’ll build a neural network for a classification task. We’ll use a new dataset, containing credit rankings for over 4000 people (see appendix for a description of the fields). The goal will be to predict Status, a binary outcome with two levels: good and bad. We’ll start again by reading the data:
## Read in the data
credit_data = read.csv("../datafiles/credit_data.csv")
## Check
str(credit_data)## 'data.frame': 4454 obs. of 14 variables:
## $ Status : chr "good" "good" "bad" "good" ...
## $ Seniority: int 9 17 10 0 0 1 29 9 0 0 ...
## $ Home : chr "rent" "rent" "owner" "rent" ...
## $ Time : int 60 60 36 60 36 60 60 12 60 48 ...
## $ Age : int 30 58 46 24 26 36 44 27 32 41 ...
## $ Marital : chr "married" "widow" "married" "single" ...
## $ Records : chr "no" "no" "yes" "no" ...
## $ Job : chr "freelance" "fixed" "freelance" "fixed" ...
## $ Expenses : int 73 48 90 63 46 75 75 35 90 90 ...
## $ Income : int 129 131 200 182 107 214 125 80 107 80 ...
## $ Assets : int 0 0 3000 2500 0 3500 10000 0 15000 0 ...
## $ Debt : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Amount : int 800 1000 2000 900 310 650 1600 200 1200 1200 ...
## $ Price : int 846 1658 2985 1325 910 1645 1800 1093 1957 1468 ...As we have several categorical variables, we need to make sure that R recognizes these as factors. The following line of code checks each column in the credit_data data frame, and if it contains character data, it then converts it to a factor. Note this is similar to the approach in the previous lab, where we convert individual variables to factors:
## Loop through the data frame and change character variables to factors
credit_data = credit_data %>%
mutate_if(is.character, as.factor) %>%
mutate_if(is.integer, as.numeric)
## Check
str(credit_data)## 'data.frame': 4454 obs. of 14 variables:
## $ Status : Factor w/ 2 levels "bad","good": 2 2 1 2 2 2 2 2 2 1 ...
## $ Seniority: num 9 17 10 0 0 1 29 9 0 0 ...
## $ Home : Factor w/ 6 levels "ignore","other",..: 6 6 3 6 6 3 3 4 3 4 ...
## $ Time : num 60 60 36 60 36 60 60 12 60 48 ...
## $ Age : num 30 58 46 24 26 36 44 27 32 41 ...
## $ Marital : Factor w/ 5 levels "divorced","married",..: 2 5 2 4 4 2 2 4 2 2 ...
## $ Records : Factor w/ 2 levels "no","yes": 1 1 2 1 1 1 1 1 1 1 ...
## $ Job : Factor w/ 4 levels "fixed","freelance",..: 2 1 2 1 1 1 1 1 2 4 ...
## $ Expenses : num 73 48 90 63 46 75 75 35 90 90 ...
## $ Income : num 129 131 200 182 107 214 125 80 107 80 ...
## $ Assets : num 0 0 3000 2500 0 3500 10000 0 15000 0 ...
## $ Debt : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Amount : num 800 1000 2000 900 310 650 1600 200 1200 1200 ...
## $ Price : num 846 1658 2985 1325 910 ...## Check the credit data for NAs
summary(credit_data)## Status Seniority Home Time Age
## bad :1254 Min. : 0.000 ignore : 20 Min. : 6.00 Min. :18.00
## good:3200 1st Qu.: 2.000 other : 319 1st Qu.:36.00 1st Qu.:28.00
## Median : 5.000 owner :2107 Median :48.00 Median :36.00
## Mean : 7.987 parents: 783 Mean :46.44 Mean :37.08
## 3rd Qu.:12.000 priv : 246 3rd Qu.:60.00 3rd Qu.:45.00
## Max. :48.000 rent : 973 Max. :72.00 Max. :68.00
## NA's : 6
## Marital Records Job Expenses Income
## divorced : 38 no :3681 fixed :2805 Min. : 35.00 Min. : 6.0
## married :3241 yes: 773 freelance:1024 1st Qu.: 35.00 1st Qu.: 90.0
## separated: 130 others : 171 Median : 51.00 Median :125.0
## single : 977 partime : 452 Mean : 55.57 Mean :141.7
## widow : 67 NA's : 2 3rd Qu.: 72.00 3rd Qu.:170.0
## NA's : 1 Max. :180.00 Max. :959.0
## NA's :381
## Assets Debt Amount Price
## Min. : 0 Min. : 0 Min. : 100 Min. : 105
## 1st Qu.: 0 1st Qu.: 0 1st Qu.: 700 1st Qu.: 1117
## Median : 3000 Median : 0 Median :1000 Median : 1400
## Mean : 5404 Mean : 343 Mean :1039 Mean : 1463
## 3rd Qu.: 6000 3rd Qu.: 0 3rd Qu.:1300 3rd Qu.: 1692
## Max. :300000 Max. :30000 Max. :5000 Max. :11140
## NA's :47 NA's :18## Home - 6
## Marital - 1
## Job - 2
## Income - 381
## Assets - 47
## Debt - 18As machine learning algorithms can’t use missing data to train, we need to decide what to do with these. For this lab, we’ll just exclude them, which results in the loss of about 400 observations, but in the next lab, we’ll explore methods to impute values and use these.
## Exclude the NAs
credit_data = credit_data %>%
na.omit()
## Check
sum(is.na(credit_data))## [1] 0Now set up the machine learning model.
## Set up the task
credit_task = TaskClassif$new(id = "credit",
backend = credit_data,
target = "Status")## Set up the learner
## size = 10 nodes
## trace?
credit_learn_nn = lrn("classif.nnet",
size = 10,
decay = 1e-5,
maxit = 500,
trace = FALSE)## Set up the resampling
credit_rsmp_outer = rsmp("cv",
folds = 5)## Set up the measure
credit_msr_auc = msr("classif.auc")## Set up the model
credit_nn = resample(task = credit_task,
learner = credit_learn_nn,
resampling = credit_rsmp_outer)## INFO [10:31:00.001] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/5)
## INFO [10:31:00.796] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 2/5)
## INFO [10:31:02.188] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 3/5)
## INFO [10:31:04.002] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 4/5)
## INFO [10:31:06.403] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 5/5)## Model performance
credit_nn$aggregate(credit_msr_auc)## classif.auc
## 0.7466198And let’s try with a higher number of nodes and a greater number of iterations:
## Reset the learner to include more iterations (1000)
## Add more nodes (25)
credit_learn_nn = lrn("classif.nnet",
size = 25,
decay = 1e-5,
maxit = 1000,
trace = FALSE)
## Rerun model
credit_nn_v2 = resample(task = credit_task,
learner = credit_learn_nn,
resampling = credit_rsmp_outer)## INFO [10:31:08.031] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/5)
## INFO [10:31:22.719] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 2/5)
## INFO [10:31:30.726] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 3/5)
## INFO [10:31:43.066] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 4/5)
## INFO [10:31:49.715] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 5/5)## Assess the second model
credit_nn_v2$aggregate(credit_msr_auc)## classif.auc
## 0.7423865Interpretation Note: Not much improvement
Appendix
Cereal data set From https://www.kaggle.com/crawford/80-cereals
Credit data set From https://github.com/gastonstat/CreditScoring
Exercise
Credit Neural Network Model Tune
## Tune the following parameters credit score neural network
## Size of the hidden layer (size)
## Number of iterations (maxit)
## Decay Function (decay) (balancing between over/underfitting)
## Later runs - decay set to 1e-6
tune_credit_ps = ParamSet$new(list(
ParamInt$new("size", lower = 1, upper = 25),
ParamInt$new("maxit", lower = 50, upper = 1000),
ParamDbl$new("decay", lower = 0, upper = 1e-6)
))
## Check
tune_credit_ps## <ParamSet>
## id class lower upper nlevels default value
## 1: size ParamInt 1 2.5e+01 25 <NoDefault[3]>
## 2: maxit ParamInt 50 1.0e+03 951 <NoDefault[3]>
## 3: decay ParamDbl 0 1.0e-06 Inf <NoDefault[3]>## Tuner setup
## Grid Search (grid_search)
## From the mlr3 book -
## Discretizes the range of each configuration and exhaustively evaluates each combination.
tuner_credit = tnr("grid_search")
## Bayesian Optimzation
## Creating this tuner to try
## From the mlr3 book -
## Iterative algorithms that make use of a continuously updated surrogate model built for the objective function. By optimizing a (comparably cheap to evaluate) acquisition function defined on the surrogate prediction, the next candidate is chosen for evaluation, resulting in good sample efficiency.
library(mlr3mbo)## Loading required package: mlr3tuningtuner_credit_mbo = tnr("mbo")
## Tuner setup - random_search
## Note: Samples configurations from a uniform distribution randomly
tuner_credit_random = tnr("random_search")## Set this for 30 iterations
## Later set and run with 25 and 20 evaluations
evals_credit = trm("evals",
n_evals = 20)
## Set a run time terminator to experiment with
time_credit = trm("run_time",
secs = 90)## Cross Validation
## folds
rsmp_inner_credit = rsmp("cv",
folds = 3)
## Holdout strategy for testing
rsmp_inner_credit_holdout = rsmp("holdout",
ratio = 0.8)Build the autotuner!
## AutoTuner
credit_at_nn = AutoTuner$new(tuner = tuner_credit_random,
learner = credit_learn_nn,
resampling = rsmp_inner_credit_holdout,
measure = credit_msr_auc,
search_space = tune_credit_ps,
terminator = time_credit)## Reproducability?
set.seed(2)
## Time Start
start = Sys.time()
## Resample Re-run
credit_nn_v3 = resample(task = credit_task,
learner = credit_at_nn,
resampling = credit_rsmp_outer,
store_models = TRUE)## INFO [10:32:04.169] [mlr3] Applying learner 'classif.nnet.tuned' on task 'credit' (iter 1/5)
## INFO [10:32:04.219] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorRunTime> [secs=90]'
## INFO [10:32:04.226] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:04.233] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:04.235] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:10.114] [mlr3] Finished benchmark
## INFO [10:32:10.123] [bbotk] Result of batch 1:
## INFO [10:32:10.124] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:10.124] [bbotk] 25 454 1.123396e-07 0.7649401 0 0 5.875
## INFO [10:32:10.124] [bbotk] uhash
## INFO [10:32:10.124] [bbotk] b857cde5-42de-46c0-a03e-90189ca0b108
## INFO [10:32:10.126] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:10.133] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:10.135] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:12.381] [mlr3] Finished benchmark
## INFO [10:32:12.392] [bbotk] Result of batch 2:
## INFO [10:32:12.393] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:12.393] [bbotk] 11 646 4.072748e-07 0.7542556 0 0 2.242
## INFO [10:32:12.393] [bbotk] uhash
## INFO [10:32:12.393] [bbotk] 99d5fc9b-4e45-4d06-ac21-bc41ccae13aa
## INFO [10:32:12.394] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:12.401] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:12.404] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:12.613] [mlr3] Finished benchmark
## INFO [10:32:12.623] [bbotk] Result of batch 3:
## INFO [10:32:12.624] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:12.624] [bbotk] 9 477 4.934742e-07 0.6265038 0 0 0.2
## INFO [10:32:12.624] [bbotk] uhash
## INFO [10:32:12.624] [bbotk] 21b9c788-77c9-4ef0-ace7-e374bab622f4
## INFO [10:32:12.626] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:12.632] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:12.635] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:12.662] [mlr3] Finished benchmark
## INFO [10:32:12.672] [bbotk] Result of batch 4:
## INFO [10:32:12.673] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:12.673] [bbotk] 2 431 7.577693e-07 0.6019567 0 0 0.024
## INFO [10:32:12.673] [bbotk] uhash
## INFO [10:32:12.673] [bbotk] 1138b565-13f4-4488-8fc1-020d1e3d00d5
## INFO [10:32:12.675] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:12.682] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:12.684] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:13.053] [mlr3] Finished benchmark
## INFO [10:32:13.064] [bbotk] Result of batch 5:
## INFO [10:32:13.065] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:13.065] [bbotk] 12 408 3.925037e-07 0.6324579 0 0 0.365
## INFO [10:32:13.065] [bbotk] uhash
## INFO [10:32:13.065] [bbotk] b063042a-b058-4551-887e-a10ab475c600
## INFO [10:32:13.066] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:13.073] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:13.076] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:18.727] [mlr3] Finished benchmark
## INFO [10:32:18.738] [bbotk] Result of batch 6:
## INFO [10:32:18.739] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:18.739] [bbotk] 22 524 9.115486e-07 0.7170149 0 0 5.648
## INFO [10:32:18.739] [bbotk] uhash
## INFO [10:32:18.739] [bbotk] dba96095-9ef6-4b61-911b-405ca382fd3c
## INFO [10:32:18.741] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:18.747] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:18.750] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:18.770] [mlr3] Finished benchmark
## INFO [10:32:18.780] [bbotk] Result of batch 7:
## INFO [10:32:18.781] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:18.781] [bbotk] 2 781 7.851298e-07 0.5 0 0 0.016
## INFO [10:32:18.781] [bbotk] uhash
## INFO [10:32:18.781] [bbotk] 73890ed9-c07e-42ad-87dd-6ff07c4e9f92
## INFO [10:32:18.783] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:18.789] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:18.792] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:19.532] [mlr3] Finished benchmark
## INFO [10:32:19.542] [bbotk] Result of batch 8:
## INFO [10:32:19.543] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:19.543] [bbotk] 14 459 6.694759e-07 0.6481468 0 0 0.736
## INFO [10:32:19.543] [bbotk] uhash
## INFO [10:32:19.543] [bbotk] b6685d89-aa5b-42f0-8fef-4e3909db954b
## INFO [10:32:19.544] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:19.551] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:19.554] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:23.528] [mlr3] Finished benchmark
## INFO [10:32:23.539] [bbotk] Result of batch 9:
## INFO [10:32:23.540] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:23.540] [bbotk] 24 422 6.918985e-07 0.8224722 0 0 3.969
## INFO [10:32:23.540] [bbotk] uhash
## INFO [10:32:23.540] [bbotk] 42eff6be-d633-4d35-8aaf-492b1f870a74
## INFO [10:32:23.541] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:23.548] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:23.551] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:25.536] [mlr3] Finished benchmark
## INFO [10:32:25.549] [bbotk] Result of batch 10:
## INFO [10:32:25.549] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:25.549] [bbotk] 21 477 1.994285e-07 0.6174021 0 0 1.983
## INFO [10:32:25.549] [bbotk] uhash
## INFO [10:32:25.549] [bbotk] 76b05587-716c-406a-8ed7-6ae1e75d8cdd
## INFO [10:32:25.551] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:25.558] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:25.561] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:31.634] [mlr3] Finished benchmark
## INFO [10:32:31.645] [bbotk] Result of batch 11:
## INFO [10:32:31.645] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:31.645] [bbotk] 19 682 5.976915e-07 0.6244399 0 0 6.07
## INFO [10:32:31.645] [bbotk] uhash
## INFO [10:32:31.645] [bbotk] b9199268-ae3d-4380-8d37-1bcf8856bf82
## INFO [10:32:31.647] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:31.654] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:31.656] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:31.684] [mlr3] Finished benchmark
## INFO [10:32:31.694] [bbotk] Result of batch 12:
## INFO [10:32:31.695] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:31.695] [bbotk] 5 714 3.358172e-07 0.5013637 0 0 0.023
## INFO [10:32:31.695] [bbotk] uhash
## INFO [10:32:31.695] [bbotk] e8783f46-a344-4cd6-bf0a-4a730d04db6f
## INFO [10:32:31.697] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:31.704] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:31.706] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:32.025] [mlr3] Finished benchmark
## INFO [10:32:32.050] [bbotk] Result of batch 13:
## INFO [10:32:32.051] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:32.051] [bbotk] 7 534 3.532281e-08 0.6794029 0 0 0.315
## INFO [10:32:32.051] [bbotk] uhash
## INFO [10:32:32.051] [bbotk] b4cfe7d8-a9c2-4192-88b1-4625b9897ee3
## INFO [10:32:32.053] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:32.060] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:32.063] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:34.483] [mlr3] Finished benchmark
## INFO [10:32:34.494] [bbotk] Result of batch 14:
## INFO [10:32:34.494] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:34.494] [bbotk] 13 504 7.923116e-07 0.6629773 0 0 2.416
## INFO [10:32:34.494] [bbotk] uhash
## INFO [10:32:34.494] [bbotk] aeb19b8a-eafa-4165-8084-f18ffc923e38
## INFO [10:32:34.496] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:34.503] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:34.505] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:35.787] [mlr3] Finished benchmark
## INFO [10:32:35.804] [bbotk] Result of batch 15:
## INFO [10:32:35.806] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:35.806] [bbotk] 18 469 1.345405e-07 0.7312427 0 0 1.278
## INFO [10:32:35.806] [bbotk] uhash
## INFO [10:32:35.806] [bbotk] 775e2221-abda-4182-a489-f1582e7745c2
## INFO [10:32:35.808] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:35.816] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:35.818] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:42.397] [mlr3] Finished benchmark
## INFO [10:32:42.408] [bbotk] Result of batch 16:
## INFO [10:32:42.409] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:42.409] [bbotk] 24 744 9.700011e-07 0.7733781 0 0 6.576
## INFO [10:32:42.409] [bbotk] uhash
## INFO [10:32:42.409] [bbotk] 456e3e83-0275-45c4-b655-5948ce4e4cfd
## INFO [10:32:42.410] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:42.417] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:42.420] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:44.260] [mlr3] Finished benchmark
## INFO [10:32:44.279] [bbotk] Result of batch 17:
## INFO [10:32:44.279] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:44.279] [bbotk] 16 326 3.324379e-07 0.6344608 0 0 1.837
## INFO [10:32:44.279] [bbotk] uhash
## INFO [10:32:44.279] [bbotk] cc079773-d378-42f3-99d2-b2c1454cc7de
## INFO [10:32:44.281] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:44.288] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:44.290] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:45.785] [mlr3] Finished benchmark
## INFO [10:32:45.796] [bbotk] Result of batch 18:
## INFO [10:32:45.796] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:45.796] [bbotk] 10 524 8.752843e-07 0.837461 0 0 1.491
## INFO [10:32:45.796] [bbotk] uhash
## INFO [10:32:45.796] [bbotk] ceb03f5f-ae75-42d9-a236-0f4ccba05f65
## INFO [10:32:45.798] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:45.805] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:45.807] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:45.961] [mlr3] Finished benchmark
## INFO [10:32:45.976] [bbotk] Result of batch 19:
## INFO [10:32:45.977] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:45.977] [bbotk] 3 870 6.285876e-07 0.6621615 0 0 0.15
## INFO [10:32:45.977] [bbotk] uhash
## INFO [10:32:45.977] [bbotk] d12057d0-24c9-4213-8754-425913cd6270
## INFO [10:32:45.980] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:45.989] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:45.991] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:48.142] [mlr3] Finished benchmark
## INFO [10:32:48.153] [bbotk] Result of batch 20:
## INFO [10:32:48.154] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:48.154] [bbotk] 21 198 6.344985e-07 0.604879 0 0 2.148
## INFO [10:32:48.154] [bbotk] uhash
## INFO [10:32:48.154] [bbotk] bdd15550-5941-498f-92ac-5153e9167e85
## INFO [10:32:48.155] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:48.162] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:48.165] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:51.927] [mlr3] Finished benchmark
## INFO [10:32:51.940] [bbotk] Result of batch 21:
## INFO [10:32:51.941] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:51.941] [bbotk] 20 418 5.725342e-08 0.7030428 0 0 3.758
## INFO [10:32:51.941] [bbotk] uhash
## INFO [10:32:51.941] [bbotk] c66f2306-c36c-4f36-9aa8-a929ea9b55fe
## INFO [10:32:51.943] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:51.949] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:51.952] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:53.665] [mlr3] Finished benchmark
## INFO [10:32:53.676] [bbotk] Result of batch 22:
## INFO [10:32:53.677] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:53.677] [bbotk] 22 145 4.778899e-07 0.6682861 0 0 1.71
## INFO [10:32:53.677] [bbotk] uhash
## INFO [10:32:53.677] [bbotk] 2d82bc0a-3409-4f59-bdde-07c96bd5de98
## INFO [10:32:53.678] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:53.685] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:53.688] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:54.058] [mlr3] Finished benchmark
## INFO [10:32:54.071] [bbotk] Result of batch 23:
## INFO [10:32:54.072] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:54.072] [bbotk] 13 60 4.776232e-07 0.7121201 0 0 0.365
## INFO [10:32:54.072] [bbotk] uhash
## INFO [10:32:54.072] [bbotk] 54223bb2-63f9-4e13-a9c7-0e881ffc1cc2
## INFO [10:32:54.073] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:54.080] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:54.083] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:54.225] [mlr3] Finished benchmark
## INFO [10:32:54.236] [bbotk] Result of batch 24:
## INFO [10:32:54.237] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:54.237] [bbotk] 5 346 8.891335e-07 0.6779417 0 0 0.138
## INFO [10:32:54.237] [bbotk] uhash
## INFO [10:32:54.237] [bbotk] abef4589-763e-4430-b7f2-a10d92265582
## INFO [10:32:54.239] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:54.246] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:54.248] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:32:57.882] [mlr3] Finished benchmark
## INFO [10:32:57.895] [bbotk] Result of batch 25:
## INFO [10:32:57.895] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:32:57.895] [bbotk] 21 391 3.940897e-07 0.6648402 0 0 3.628
## INFO [10:32:57.895] [bbotk] uhash
## INFO [10:32:57.895] [bbotk] d2fe4946-6431-4eca-9222-6aba4e183b80
## INFO [10:32:57.897] [bbotk] Evaluating 1 configuration(s)
## INFO [10:32:57.904] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:32:57.907] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:00.407] [mlr3] Finished benchmark
## INFO [10:33:00.424] [bbotk] Result of batch 26:
## INFO [10:33:00.425] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:00.425] [bbotk] 25 201 7.464722e-07 0.6783009 0 0 2.497
## INFO [10:33:00.425] [bbotk] uhash
## INFO [10:33:00.425] [bbotk] 25d01d86-a416-4557-aa5d-924281bd7dc0
## INFO [10:33:00.427] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:00.435] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:00.438] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:01.021] [mlr3] Finished benchmark
## INFO [10:33:01.032] [bbotk] Result of batch 27:
## INFO [10:33:01.033] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:01.033] [bbotk] 13 132 8.965753e-07 0.666344 0 0 0.58
## INFO [10:33:01.033] [bbotk] uhash
## INFO [10:33:01.033] [bbotk] cf6e9218-a9b8-47f4-b20c-35fce7ee05e8
## INFO [10:33:01.035] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:01.042] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:01.045] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:02.578] [mlr3] Finished benchmark
## INFO [10:33:02.590] [bbotk] Result of batch 28:
## INFO [10:33:02.591] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:02.591] [bbotk] 10 770 4.922726e-07 0.6645054 0 0 1.529
## INFO [10:33:02.591] [bbotk] uhash
## INFO [10:33:02.591] [bbotk] eeb8ba8c-2b9f-4c0f-873c-3cc300ba02ec
## INFO [10:33:02.593] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:02.600] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:02.602] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:05.268] [mlr3] Finished benchmark
## INFO [10:33:05.288] [bbotk] Result of batch 29:
## INFO [10:33:05.289] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:05.289] [bbotk] 11 532 3.387596e-07 0.6340529 0 0 2.662
## INFO [10:33:05.289] [bbotk] uhash
## INFO [10:33:05.289] [bbotk] 51d4289c-f1dd-4eca-bc1c-f5c029fa8aa1
## INFO [10:33:05.292] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:05.302] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:05.305] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:06.518] [mlr3] Finished benchmark
## INFO [10:33:06.529] [bbotk] Result of batch 30:
## INFO [10:33:06.530] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:06.530] [bbotk] 14 864 9.696513e-07 0.6531268 0 0 1.209
## INFO [10:33:06.530] [bbotk] uhash
## INFO [10:33:06.530] [bbotk] 85139130-3d8e-453c-ad2c-90595d4839e1
## INFO [10:33:06.531] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:06.538] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:06.541] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:09.349] [mlr3] Finished benchmark
## INFO [10:33:09.365] [bbotk] Result of batch 31:
## INFO [10:33:09.365] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:09.365] [bbotk] 25 257 1.312043e-07 0.6720363 0 0 2.803
## INFO [10:33:09.365] [bbotk] uhash
## INFO [10:33:09.365] [bbotk] f38b5bcc-5433-48e5-a551-47294481b8a0
## INFO [10:33:09.367] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:09.374] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:09.376] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:09.452] [mlr3] Finished benchmark
## INFO [10:33:09.463] [bbotk] Result of batch 32:
## INFO [10:33:09.464] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:09.464] [bbotk] 2 790 6.673123e-07 0.6257975 0 0 0.072
## INFO [10:33:09.464] [bbotk] uhash
## INFO [10:33:09.464] [bbotk] a54d8bf1-d7e5-4959-b14f-e29f85a6d60d
## INFO [10:33:09.466] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:09.472] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:09.475] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:12.189] [mlr3] Finished benchmark
## INFO [10:33:12.204] [bbotk] Result of batch 33:
## INFO [10:33:12.205] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:12.205] [bbotk] 24 200 6.699734e-07 0.6594341 0 0 2.71
## INFO [10:33:12.205] [bbotk] uhash
## INFO [10:33:12.205] [bbotk] d7dac8ae-df44-41f9-b194-64caa91869e9
## INFO [10:33:12.207] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:12.214] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:12.217] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:13.511] [mlr3] Finished benchmark
## INFO [10:33:13.522] [bbotk] Result of batch 34:
## INFO [10:33:13.522] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:13.522] [bbotk] 16 224 9.341452e-08 0.638065 0 0 1.291
## INFO [10:33:13.522] [bbotk] uhash
## INFO [10:33:13.522] [bbotk] bd4828bd-5ea0-46d7-919b-f3a7188609a2
## INFO [10:33:13.524] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:13.531] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:13.534] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:15.271] [mlr3] Finished benchmark
## INFO [10:33:15.286] [bbotk] Result of batch 35:
## INFO [10:33:15.287] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:15.287] [bbotk] 23 148 1.259278e-07 0.6513613 0 0 1.733
## INFO [10:33:15.287] [bbotk] uhash
## INFO [10:33:15.287] [bbotk] 143de62b-487b-46d4-af71-4522deebaaf9
## INFO [10:33:15.288] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:15.295] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:15.298] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:22.589] [mlr3] Finished benchmark
## INFO [10:33:22.607] [bbotk] Result of batch 36:
## INFO [10:33:22.608] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:22.608] [bbotk] 20 908 2.488918e-07 0.6516718 0 0 7.287
## INFO [10:33:22.608] [bbotk] uhash
## INFO [10:33:22.608] [bbotk] fbc6ec29-d1c7-4df8-b3e6-ba977377f685
## INFO [10:33:22.610] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:22.620] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:22.623] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:26.767] [mlr3] Finished benchmark
## INFO [10:33:26.778] [bbotk] Result of batch 37:
## INFO [10:33:26.779] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:26.779] [bbotk] 15 768 8.54268e-08 0.698495 0 0 4.141
## INFO [10:33:26.779] [bbotk] uhash
## INFO [10:33:26.779] [bbotk] 9dd56343-7d70-452f-b91c-bfd429f425c7
## INFO [10:33:26.781] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:26.787] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:26.790] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:30.900] [mlr3] Finished benchmark
## INFO [10:33:30.915] [bbotk] Result of batch 38:
## INFO [10:33:30.916] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:30.916] [bbotk] 22 568 6.677052e-07 0.7149815 0 0 4.106
## INFO [10:33:30.916] [bbotk] uhash
## INFO [10:33:30.916] [bbotk] 6922a4f1-0ba4-4b23-91af-8cfad490edd1
## INFO [10:33:30.917] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:30.924] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:30.927] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:31.965] [mlr3] Finished benchmark
## INFO [10:33:31.976] [bbotk] Result of batch 39:
## INFO [10:33:31.977] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:31.977] [bbotk] 14 129 3.448113e-07 0.6955667 0 0 1.036
## INFO [10:33:31.977] [bbotk] uhash
## INFO [10:33:31.977] [bbotk] 906afcac-5b3f-4638-a3b9-dc3240b4bb9a
## INFO [10:33:31.987] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:31.999] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:32.003] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:35.873] [mlr3] Finished benchmark
## INFO [10:33:35.884] [bbotk] Result of batch 40:
## INFO [10:33:35.885] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:35.885] [bbotk] 11 921 8.092531e-08 0.6210245 0 0 3.867
## INFO [10:33:35.885] [bbotk] uhash
## INFO [10:33:35.885] [bbotk] 60842ea1-5fab-40f6-80b3-816b8efaaf1d
## INFO [10:33:35.888] [bbotk] Finished optimizing after 40 evaluation(s)
## INFO [10:33:35.888] [bbotk] Result:
## INFO [10:33:35.889] [bbotk] size maxit decay learner_param_vals x_domain classif.auc
## INFO [10:33:35.889] [bbotk] 10 524 8.752843e-07 <list[4]> <list[3]> 0.837461
## INFO [10:33:38.801] [mlr3] Applying learner 'classif.nnet.tuned' on task 'credit' (iter 2/5)
## INFO [10:33:38.825] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorRunTime> [secs=90]'
## INFO [10:33:38.831] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:38.838] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:38.841] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:43.425] [mlr3] Finished benchmark
## INFO [10:33:43.435] [bbotk] Result of batch 1:
## INFO [10:33:43.436] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:43.436] [bbotk] 25 927 4.968778e-07 0.633816 0 0 4.581
## INFO [10:33:43.436] [bbotk] uhash
## INFO [10:33:43.436] [bbotk] 1fb9e815-14ea-4918-9be4-334c251e9e61
## INFO [10:33:43.438] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:43.445] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:43.448] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:43.624] [mlr3] Finished benchmark
## INFO [10:33:43.635] [bbotk] Result of batch 2:
## INFO [10:33:43.636] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:43.636] [bbotk] 2 226 8.826677e-07 0.5741103 0 0 0.172
## INFO [10:33:43.636] [bbotk] uhash
## INFO [10:33:43.636] [bbotk] 5472a9c1-2944-434f-a7e6-34720eb27d2e
## INFO [10:33:43.637] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:43.644] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:43.647] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:44.022] [mlr3] Finished benchmark
## INFO [10:33:44.033] [bbotk] Result of batch 3:
## INFO [10:33:44.034] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:44.034] [bbotk] 8 92 2.256231e-07 0.6690626 0 0 0.372
## INFO [10:33:44.034] [bbotk] uhash
## INFO [10:33:44.034] [bbotk] f036d229-598e-4362-8e8f-d5feb56c0360
## INFO [10:33:44.035] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:44.042] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:44.044] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:44.063] [mlr3] Finished benchmark
## INFO [10:33:44.074] [bbotk] Result of batch 4:
## INFO [10:33:44.075] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:44.075] [bbotk] 4 121 8.236629e-07 0.5 0 0 0.015
## INFO [10:33:44.075] [bbotk] uhash
## INFO [10:33:44.075] [bbotk] 348f83f0-e6f9-4c5f-81d3-f5100d6860d2
## INFO [10:33:44.077] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:44.085] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:44.088] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:46.368] [mlr3] Finished benchmark
## INFO [10:33:46.379] [bbotk] Result of batch 5:
## INFO [10:33:46.380] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:46.380] [bbotk] 16 517 6.949358e-08 0.6523656 0 0 2.273
## INFO [10:33:46.380] [bbotk] uhash
## INFO [10:33:46.380] [bbotk] 4bee7743-c705-45c6-9f0d-585c75f5824b
## INFO [10:33:46.382] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:46.389] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:46.392] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:49.224] [mlr3] Finished benchmark
## INFO [10:33:49.235] [bbotk] Result of batch 6:
## INFO [10:33:49.236] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:49.236] [bbotk] 14 473 6.225143e-07 0.6473471 0 0 2.828
## INFO [10:33:49.236] [bbotk] uhash
## INFO [10:33:49.236] [bbotk] bccd5cdb-4dca-4c57-9dad-d51129a112a3
## INFO [10:33:49.237] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:49.244] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:49.247] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:52.267] [mlr3] Finished benchmark
## INFO [10:33:52.278] [bbotk] Result of batch 7:
## INFO [10:33:52.278] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:52.278] [bbotk] 24 240 6.460873e-07 0.6432315 0 0 3.016
## INFO [10:33:52.278] [bbotk] uhash
## INFO [10:33:52.278] [bbotk] 2ae2922d-32c7-4629-b410-26a013af4f02
## INFO [10:33:52.280] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:52.291] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:52.293] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:53.516] [mlr3] Finished benchmark
## INFO [10:33:53.527] [bbotk] Result of batch 8:
## INFO [10:33:53.527] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:53.527] [bbotk] 10 785 8.753094e-07 0.6977429 0 0 1.219
## INFO [10:33:53.527] [bbotk] uhash
## INFO [10:33:53.527] [bbotk] 97a98381-8c48-48e5-97cd-f720a20de5ca
## INFO [10:33:53.529] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:53.536] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:53.539] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:54.785] [mlr3] Finished benchmark
## INFO [10:33:54.796] [bbotk] Result of batch 9:
## INFO [10:33:54.796] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:54.796] [bbotk] 8 744 8.059288e-07 0.7980125 0 0 1.243
## INFO [10:33:54.796] [bbotk] uhash
## INFO [10:33:54.796] [bbotk] 56e1e2b9-a86d-49c4-aceb-04e9ead5792e
## INFO [10:33:54.798] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:54.805] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:54.807] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:56.791] [mlr3] Finished benchmark
## INFO [10:33:56.802] [bbotk] Result of batch 10:
## INFO [10:33:56.803] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:56.803] [bbotk] 18 195 9.529746e-07 0.7046784 0 0 1.98
## INFO [10:33:56.803] [bbotk] uhash
## INFO [10:33:56.803] [bbotk] 66ab68b9-4d3a-4472-a896-4b71095197cc
## INFO [10:33:56.804] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:56.815] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:56.817] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:33:59.122] [mlr3] Finished benchmark
## INFO [10:33:59.133] [bbotk] Result of batch 11:
## INFO [10:33:59.134] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:33:59.134] [bbotk] 16 671 8.08948e-07 0.6921557 0 0 2.302
## INFO [10:33:59.134] [bbotk] uhash
## INFO [10:33:59.134] [bbotk] 1f758703-75fa-46bd-8289-62097420fc8e
## INFO [10:33:59.135] [bbotk] Evaluating 1 configuration(s)
## INFO [10:33:59.142] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:33:59.144] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:02.322] [mlr3] Finished benchmark
## INFO [10:34:02.333] [bbotk] Result of batch 12:
## INFO [10:34:02.333] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:02.333] [bbotk] 18 864 2.931686e-07 0.6273847 0 0 3.174
## INFO [10:34:02.333] [bbotk] uhash
## INFO [10:34:02.333] [bbotk] 2817f550-ca95-4c65-8d71-f540ff9143cf
## INFO [10:34:02.335] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:02.342] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:02.344] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:02.640] [mlr3] Finished benchmark
## INFO [10:34:02.654] [bbotk] Result of batch 13:
## INFO [10:34:02.655] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:02.655] [bbotk] 10 895 4.81355e-07 0.5769713 0 0 0.292
## INFO [10:34:02.655] [bbotk] uhash
## INFO [10:34:02.655] [bbotk] 132df872-573f-474c-92ec-d689588ec991
## INFO [10:34:02.657] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:02.663] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:02.666] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:02.767] [mlr3] Finished benchmark
## INFO [10:34:02.778] [bbotk] Result of batch 14:
## INFO [10:34:02.779] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:02.779] [bbotk] 4 138 2.959204e-07 0.621135 0 0 0.097
## INFO [10:34:02.779] [bbotk] uhash
## INFO [10:34:02.779] [bbotk] 7f096ac4-5deb-4d6d-b2db-6e57fa0b1f99
## INFO [10:34:02.780] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:02.787] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:02.790] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:03.155] [mlr3] Finished benchmark
## INFO [10:34:03.165] [bbotk] Result of batch 15:
## INFO [10:34:03.166] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:03.166] [bbotk] 6 944 2.432946e-07 0.6579352 0 0 0.362
## INFO [10:34:03.166] [bbotk] uhash
## INFO [10:34:03.166] [bbotk] b1733146-c921-4303-9fc3-1c71c48a2c98
## INFO [10:34:03.168] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:03.175] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:03.177] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:03.189] [mlr3] Finished benchmark
## INFO [10:34:03.204] [bbotk] Result of batch 16:
## INFO [10:34:03.205] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:03.205] [bbotk] 2 71 6.558129e-08 0.4989154 0 0 0.008
## INFO [10:34:03.205] [bbotk] uhash
## INFO [10:34:03.205] [bbotk] f5a85dca-9682-4e5a-865a-ddb2106f8fae
## INFO [10:34:03.206] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:03.214] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:03.216] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:04.571] [mlr3] Finished benchmark
## INFO [10:34:04.582] [bbotk] Result of batch 17:
## INFO [10:34:04.583] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:04.583] [bbotk] 16 925 4.462652e-07 0.6320865 0 0 1.351
## INFO [10:34:04.583] [bbotk] uhash
## INFO [10:34:04.583] [bbotk] 20b5cae2-a14b-4654-a363-8dcf44ed080a
## INFO [10:34:04.584] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:04.591] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:04.594] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:04.605] [mlr3] Finished benchmark
## INFO [10:34:04.616] [bbotk] Result of batch 18:
## INFO [10:34:04.616] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:04.616] [bbotk] 1 571 7.33617e-07 0.5 0 0 0.008
## INFO [10:34:04.616] [bbotk] uhash
## INFO [10:34:04.616] [bbotk] 2b3ba89a-ffe2-4072-8ce8-aea89a01e510
## INFO [10:34:04.618] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:04.625] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:04.628] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:04.790] [mlr3] Finished benchmark
## INFO [10:34:04.801] [bbotk] Result of batch 19:
## INFO [10:34:04.801] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:04.801] [bbotk] 15 556 8.621237e-07 0.5902972 0 0 0.16
## INFO [10:34:04.801] [bbotk] uhash
## INFO [10:34:04.801] [bbotk] c4d0a969-81b4-4daa-aaef-fad521f187ea
## INFO [10:34:04.803] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:04.810] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:04.812] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:04.853] [mlr3] Finished benchmark
## INFO [10:34:04.864] [bbotk] Result of batch 20:
## INFO [10:34:04.865] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:04.865] [bbotk] 4 736 7.943745e-07 0.5772469 0 0 0.038
## INFO [10:34:04.865] [bbotk] uhash
## INFO [10:34:04.865] [bbotk] 90ce1a26-7e99-4837-84e9-e71b20934f03
## INFO [10:34:04.866] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:04.873] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:04.876] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:09.492] [mlr3] Finished benchmark
## INFO [10:34:09.503] [bbotk] Result of batch 21:
## INFO [10:34:09.503] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:09.503] [bbotk] 15 991 4.896444e-07 0.8164859 0 0 4.613
## INFO [10:34:09.503] [bbotk] uhash
## INFO [10:34:09.503] [bbotk] 3dfd46a6-8604-4474-be2c-21e8180aa018
## INFO [10:34:09.505] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:09.516] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:09.519] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:09.687] [mlr3] Finished benchmark
## INFO [10:34:09.698] [bbotk] Result of batch 22:
## INFO [10:34:09.699] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:09.699] [bbotk] 6 521 4.253133e-07 0.5848918 0 0 0.165
## INFO [10:34:09.699] [bbotk] uhash
## INFO [10:34:09.699] [bbotk] 1c60bdf0-5152-4303-87e4-c3ac96ef8201
## INFO [10:34:09.700] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:09.707] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:09.709] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:09.752] [mlr3] Finished benchmark
## INFO [10:34:09.763] [bbotk] Result of batch 23:
## INFO [10:34:09.763] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:09.763] [bbotk] 1 396 5.185286e-07 0.6478103 0 0 0.04
## INFO [10:34:09.763] [bbotk] uhash
## INFO [10:34:09.763] [bbotk] 7f752f2a-50d6-4934-a058-c0ac5cbad6e3
## INFO [10:34:09.765] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:09.772] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:09.774] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:12.224] [mlr3] Finished benchmark
## INFO [10:34:12.238] [bbotk] Result of batch 24:
## INFO [10:34:12.239] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:12.239] [bbotk] 23 265 2.863235e-07 0.6061382 0 0 2.446
## INFO [10:34:12.239] [bbotk] uhash
## INFO [10:34:12.239] [bbotk] 3c17da97-9b29-4792-9573-e9f5e3ccd4b8
## INFO [10:34:12.241] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:12.248] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:12.250] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:12.327] [mlr3] Finished benchmark
## INFO [10:34:12.338] [bbotk] Result of batch 25:
## INFO [10:34:12.338] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:12.338] [bbotk] 5 885 9.570446e-07 0.5797854 0 0 0.073
## INFO [10:34:12.338] [bbotk] uhash
## INFO [10:34:12.338] [bbotk] 47433b8d-a56f-4ba0-a270-95ca65a2da95
## INFO [10:34:12.340] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:12.347] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:12.349] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:14.749] [mlr3] Finished benchmark
## INFO [10:34:14.760] [bbotk] Result of batch 26:
## INFO [10:34:14.760] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:14.760] [bbotk] 14 994 6.003776e-07 0.821305 0 0 2.395
## INFO [10:34:14.760] [bbotk] uhash
## INFO [10:34:14.760] [bbotk] 3de381c5-99c6-4935-8b05-6c768ababda5
## INFO [10:34:14.762] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:14.769] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:14.772] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:20.311] [mlr3] Finished benchmark
## INFO [10:34:20.325] [bbotk] Result of batch 27:
## INFO [10:34:20.326] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:20.326] [bbotk] 20 864 4.072446e-07 0.6749897 0 0 5.536
## INFO [10:34:20.326] [bbotk] uhash
## INFO [10:34:20.326] [bbotk] 30f0dd44-bfc6-45ba-a0bc-f216a5e8c9c5
## INFO [10:34:20.327] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:20.334] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:20.337] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:20.349] [mlr3] Finished benchmark
## INFO [10:34:20.360] [bbotk] Result of batch 28:
## INFO [10:34:20.361] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:20.361] [bbotk] 2 200 9.340425e-07 0.5 0 0 0.009
## INFO [10:34:20.361] [bbotk] uhash
## INFO [10:34:20.361] [bbotk] 29bedee9-2867-49b8-b280-625b4d0871b7
## INFO [10:34:20.363] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:20.371] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:20.373] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:22.865] [mlr3] Finished benchmark
## INFO [10:34:22.876] [bbotk] Result of batch 29:
## INFO [10:34:22.877] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:22.877] [bbotk] 25 798 7.546768e-07 0.6440699 0 0 2.489
## INFO [10:34:22.877] [bbotk] uhash
## INFO [10:34:22.877] [bbotk] 21c64758-dfdc-4570-b2bf-3667ab47d0c9
## INFO [10:34:22.879] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:22.886] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:22.892] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:26.426] [mlr3] Finished benchmark
## INFO [10:34:26.438] [bbotk] Result of batch 30:
## INFO [10:34:26.439] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:26.439] [bbotk] 11 793 2.860464e-07 0.7213285 0 0 3.53
## INFO [10:34:26.439] [bbotk] uhash
## INFO [10:34:26.439] [bbotk] 83596aec-d6e8-4de6-a346-99d57f5ef803
## INFO [10:34:26.440] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:26.448] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:26.450] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:27.051] [mlr3] Finished benchmark
## INFO [10:34:27.063] [bbotk] Result of batch 31:
## INFO [10:34:27.064] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:27.064] [bbotk] 9 158 2.927323e-08 0.7420473 0 0 0.597
## INFO [10:34:27.064] [bbotk] uhash
## INFO [10:34:27.064] [bbotk] 4143351e-8314-49a6-b57b-18a7929e1f6e
## INFO [10:34:27.066] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:27.073] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:27.076] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:28.371] [mlr3] Finished benchmark
## INFO [10:34:28.382] [bbotk] Result of batch 32:
## INFO [10:34:28.383] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:28.383] [bbotk] 15 193 1.790674e-07 0.630058 0 0 1.292
## INFO [10:34:28.383] [bbotk] uhash
## INFO [10:34:28.383] [bbotk] f7e0c6eb-fc27-45c0-bfe8-35ff7d016a58
## INFO [10:34:28.385] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:28.396] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:28.398] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:29.067] [mlr3] Finished benchmark
## INFO [10:34:29.080] [bbotk] Result of batch 33:
## INFO [10:34:29.081] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:29.081] [bbotk] 5 412 7.070222e-07 0.7702879 0 0 0.665
## INFO [10:34:29.081] [bbotk] uhash
## INFO [10:34:29.081] [bbotk] 7dae7187-3e84-425d-9ac4-4d98a6193d27
## INFO [10:34:29.083] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:29.091] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:29.094] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:31.221] [mlr3] Finished benchmark
## INFO [10:34:31.233] [bbotk] Result of batch 34:
## INFO [10:34:31.234] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:31.234] [bbotk] 16 818 6.579328e-07 0.677411 0 0 2.124
## INFO [10:34:31.234] [bbotk] uhash
## INFO [10:34:31.234] [bbotk] 1c418a9b-1bd1-499d-86e8-4f5c6c32f2b7
## INFO [10:34:31.235] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:31.242] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:31.245] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:33.401] [mlr3] Finished benchmark
## INFO [10:34:33.423] [bbotk] Result of batch 35:
## INFO [10:34:33.424] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:33.424] [bbotk] 10 744 3.422352e-07 0.6227883 0 0 2.152
## INFO [10:34:33.424] [bbotk] uhash
## INFO [10:34:33.424] [bbotk] 654deacf-c708-4441-b729-8b52609797e1
## INFO [10:34:33.426] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:33.434] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:33.437] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:34.329] [mlr3] Finished benchmark
## INFO [10:34:34.342] [bbotk] Result of batch 36:
## INFO [10:34:34.343] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:34.343] [bbotk] 17 110 2.016451e-07 0.6242774 0 0 0.886
## INFO [10:34:34.343] [bbotk] uhash
## INFO [10:34:34.343] [bbotk] 804066f2-64e2-4cee-af81-a72e3bc9f4b3
## INFO [10:34:34.344] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:34.352] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:34.355] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:35.448] [mlr3] Finished benchmark
## INFO [10:34:35.460] [bbotk] Result of batch 37:
## INFO [10:34:35.461] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:35.461] [bbotk] 14 253 2.232124e-07 0.6307088 0 0 1.088
## INFO [10:34:35.461] [bbotk] uhash
## INFO [10:34:35.461] [bbotk] c2b4add6-c48f-4a7e-8384-dc344b7126f7
## INFO [10:34:35.463] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:35.471] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:35.474] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:35.606] [mlr3] Finished benchmark
## INFO [10:34:35.618] [bbotk] Result of batch 38:
## INFO [10:34:35.618] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:35.618] [bbotk] 3 558 6.560051e-07 0.6303101 0 0 0.124
## INFO [10:34:35.618] [bbotk] uhash
## INFO [10:34:35.618] [bbotk] 8ae9873c-e08f-404d-8a36-51f1b604bfbc
## INFO [10:34:35.620] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:35.627] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:35.630] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:40.257] [mlr3] Finished benchmark
## INFO [10:34:40.271] [bbotk] Result of batch 39:
## INFO [10:34:40.272] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:40.272] [bbotk] 18 728 3.559142e-07 0.7363077 0 0 4.623
## INFO [10:34:40.272] [bbotk] uhash
## INFO [10:34:40.272] [bbotk] 689330da-11f3-4e5e-9781-5e78c8cc4a23
## INFO [10:34:40.274] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:40.282] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:40.285] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:42.990] [mlr3] Finished benchmark
## INFO [10:34:43.008] [bbotk] Result of batch 40:
## INFO [10:34:43.009] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:43.009] [bbotk] 23 206 8.864399e-08 0.6760861 0 0 2.701
## INFO [10:34:43.009] [bbotk] uhash
## INFO [10:34:43.009] [bbotk] 5401bb22-7d85-4620-ab52-61c93c0a7919
## INFO [10:34:43.010] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:43.018] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:43.021] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:48.385] [mlr3] Finished benchmark
## INFO [10:34:48.397] [bbotk] Result of batch 41:
## INFO [10:34:48.398] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:48.398] [bbotk] 25 474 8.199991e-07 0.6257314 0 0 5.358
## INFO [10:34:48.398] [bbotk] uhash
## INFO [10:34:48.398] [bbotk] a362a6d9-2c8a-4624-a5dc-5926aaa5bc12
## INFO [10:34:48.400] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:48.409] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:48.412] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:48.975] [mlr3] Finished benchmark
## INFO [10:34:48.988] [bbotk] Result of batch 42:
## INFO [10:34:48.989] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:48.989] [bbotk] 10 144 2.504268e-07 0.6374216 0 0 0.56
## INFO [10:34:48.989] [bbotk] uhash
## INFO [10:34:48.989] [bbotk] 94bb701d-6fba-4c91-b3b3-a55f99ebe38b
## INFO [10:34:48.991] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:48.999] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:49.002] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:51.465] [mlr3] Finished benchmark
## INFO [10:34:51.479] [bbotk] Result of batch 43:
## INFO [10:34:51.480] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:51.480] [bbotk] 11 549 6.842607e-07 0.6548983 0 0 2.454
## INFO [10:34:51.480] [bbotk] uhash
## INFO [10:34:51.480] [bbotk] b0f94e12-6a42-4fc2-92a0-cefc900e8000
## INFO [10:34:51.482] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:51.490] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:51.493] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:54.105] [mlr3] Finished benchmark
## INFO [10:34:54.117] [bbotk] Result of batch 44:
## INFO [10:34:54.118] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:54.118] [bbotk] 9 658 7.020464e-07 0.6175764 0 0 2.608
## INFO [10:34:54.118] [bbotk] uhash
## INFO [10:34:54.118] [bbotk] 02f3bfd1-8453-40b3-9fcf-3cdfca1fca24
## INFO [10:34:54.119] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:54.126] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:54.129] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:54.208] [mlr3] Finished benchmark
## INFO [10:34:54.225] [bbotk] Result of batch 45:
## INFO [10:34:54.225] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:54.225] [bbotk] 2 238 4.271267e-07 0.5949346 0 0 0.075
## INFO [10:34:54.225] [bbotk] uhash
## INFO [10:34:54.225] [bbotk] 490979ee-a29a-4831-a596-8fcb607d00a9
## INFO [10:34:54.227] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:54.234] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:54.236] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:54.785] [mlr3] Finished benchmark
## INFO [10:34:54.796] [bbotk] Result of batch 46:
## INFO [10:34:54.796] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:54.796] [bbotk] 14 258 5.879298e-07 0.6124231 0 0 0.544
## INFO [10:34:54.796] [bbotk] uhash
## INFO [10:34:54.796] [bbotk] 23e02095-4540-4a6e-949e-31b76597555b
## INFO [10:34:54.798] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:54.805] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:54.808] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:34:59.179] [mlr3] Finished benchmark
## INFO [10:34:59.190] [bbotk] Result of batch 47:
## INFO [10:34:59.191] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:34:59.191] [bbotk] 20 468 9.309008e-07 0.6440699 0 0 4.368
## INFO [10:34:59.191] [bbotk] uhash
## INFO [10:34:59.191] [bbotk] 0d405473-35fa-4934-bbc8-af7e23b5dfa4
## INFO [10:34:59.193] [bbotk] Evaluating 1 configuration(s)
## INFO [10:34:59.200] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:34:59.202] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:01.212] [mlr3] Finished benchmark
## INFO [10:35:01.223] [bbotk] Result of batch 48:
## INFO [10:35:01.224] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:01.224] [bbotk] 14 566 6.168894e-07 0.6212523 0 0 2.006
## INFO [10:35:01.224] [bbotk] uhash
## INFO [10:35:01.224] [bbotk] 2e3141b6-3025-44ce-ba7d-512184943949
## INFO [10:35:01.225] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:01.232] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:01.235] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:01.474] [mlr3] Finished benchmark
## INFO [10:35:01.485] [bbotk] Result of batch 49:
## INFO [10:35:01.486] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:01.486] [bbotk] 6 160 9.403406e-07 0.6189248 0 0 0.236
## INFO [10:35:01.486] [bbotk] uhash
## INFO [10:35:01.486] [bbotk] 5a868113-22ca-4ba4-adcf-1db200e216a0
## INFO [10:35:01.487] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:01.494] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:01.497] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:02.706] [mlr3] Finished benchmark
## INFO [10:35:02.718] [bbotk] Result of batch 50:
## INFO [10:35:02.718] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:02.718] [bbotk] 8 795 7.388082e-07 0.6945829 0 0 1.206
## INFO [10:35:02.718] [bbotk] uhash
## INFO [10:35:02.718] [bbotk] 5ee01bc8-9e9f-4d16-b9c6-503cd4bb3507
## INFO [10:35:02.720] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:02.731] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:02.734] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:10.904] [mlr3] Finished benchmark
## INFO [10:35:10.915] [bbotk] Result of batch 51:
## INFO [10:35:10.916] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:10.916] [bbotk] 25 721 2.787597e-07 0.8114674 0 0 8.167
## INFO [10:35:10.916] [bbotk] uhash
## INFO [10:35:10.916] [bbotk] 79509879-7022-480e-a76a-7943daeaec0a
## INFO [10:35:10.919] [bbotk] Finished optimizing after 51 evaluation(s)
## INFO [10:35:10.919] [bbotk] Result:
## INFO [10:35:10.920] [bbotk] size maxit decay learner_param_vals x_domain classif.auc
## INFO [10:35:10.920] [bbotk] 14 994 6.003776e-07 <list[4]> <list[3]> 0.821305
## INFO [10:35:13.496] [mlr3] Applying learner 'classif.nnet.tuned' on task 'credit' (iter 3/5)
## INFO [10:35:13.514] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorRunTime> [secs=90]'
## INFO [10:35:13.525] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:13.532] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:13.534] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:18.870] [mlr3] Finished benchmark
## INFO [10:35:18.879] [bbotk] Result of batch 1:
## INFO [10:35:18.880] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:18.880] [bbotk] 21 619 8.604745e-07 0.6693897 0 0 5.332
## INFO [10:35:18.880] [bbotk] uhash
## INFO [10:35:18.880] [bbotk] 40585a89-ba12-4c0c-affb-89959647b998
## INFO [10:35:18.882] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:18.889] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:18.891] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:25.442] [mlr3] Finished benchmark
## INFO [10:35:25.453] [bbotk] Result of batch 2:
## INFO [10:35:25.453] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:25.453] [bbotk] 21 686 6.762934e-08 0.6680772 0 0 6.547
## INFO [10:35:25.453] [bbotk] uhash
## INFO [10:35:25.453] [bbotk] 559feb07-20bb-4c1c-8854-303a2ac91159
## INFO [10:35:25.455] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:25.462] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:25.465] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:27.136] [mlr3] Finished benchmark
## INFO [10:35:27.147] [bbotk] Result of batch 3:
## INFO [10:35:27.147] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:27.147] [bbotk] 22 149 8.90793e-07 0.6546953 0 0 1.668
## INFO [10:35:27.147] [bbotk] uhash
## INFO [10:35:27.147] [bbotk] 4d2c8e66-d956-40a9-8598-8a902b9d43a6
## INFO [10:35:27.149] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:27.156] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:27.159] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:36.483] [mlr3] Finished benchmark
## INFO [10:35:36.494] [bbotk] Result of batch 4:
## INFO [10:35:36.495] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:36.495] [bbotk] 22 867 2.589757e-07 0.655327 0 0 9.321
## INFO [10:35:36.495] [bbotk] uhash
## INFO [10:35:36.495] [bbotk] 66dd4703-4dd6-4e4a-83b3-cdd7eec9ec40
## INFO [10:35:36.497] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:36.503] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:36.506] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:38.176] [mlr3] Finished benchmark
## INFO [10:35:38.188] [bbotk] Result of batch 5:
## INFO [10:35:38.189] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:38.189] [bbotk] 20 617 2.031858e-07 0.6327703 0 0 1.665
## INFO [10:35:38.189] [bbotk] uhash
## INFO [10:35:38.189] [bbotk] 1fe608f4-213c-45a0-ae1c-dbd16c35f759
## INFO [10:35:38.190] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:38.197] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:38.200] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:40.447] [mlr3] Finished benchmark
## INFO [10:35:40.459] [bbotk] Result of batch 6:
## INFO [10:35:40.459] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:40.459] [bbotk] 18 707 6.042394e-07 0.6977787 0 0 2.244
## INFO [10:35:40.459] [bbotk] uhash
## INFO [10:35:40.459] [bbotk] b18d15b2-1159-42b3-838f-413948e39a61
## INFO [10:35:40.461] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:40.469] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:40.473] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:41.114] [mlr3] Finished benchmark
## INFO [10:35:41.129] [bbotk] Result of batch 7:
## INFO [10:35:41.130] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:41.130] [bbotk] 19 70 3.139536e-07 0.6707328 0 0 0.636
## INFO [10:35:41.130] [bbotk] uhash
## INFO [10:35:41.130] [bbotk] a83462ab-e3fb-47f5-a055-35e741287af8
## INFO [10:35:41.143] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:41.158] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:41.161] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:44.050] [mlr3] Finished benchmark
## INFO [10:35:44.061] [bbotk] Result of batch 8:
## INFO [10:35:44.062] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:44.062] [bbotk] 23 240 9.909161e-07 0.6674455 0 0 2.885
## INFO [10:35:44.062] [bbotk] uhash
## INFO [10:35:44.062] [bbotk] 0645f2c4-41ca-4575-a520-a18e448685e8
## INFO [10:35:44.063] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:44.070] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:44.073] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:44.750] [mlr3] Finished benchmark
## INFO [10:35:44.761] [bbotk] Result of batch 9:
## INFO [10:35:44.761] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:44.761] [bbotk] 8 580 5.917572e-08 0.7946043 0 0 0.673
## INFO [10:35:44.761] [bbotk] uhash
## INFO [10:35:44.761] [bbotk] 10d1a268-9cc3-4677-9d01-dbbcb8bc91b6
## INFO [10:35:44.763] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:44.770] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:44.772] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:48.045] [mlr3] Finished benchmark
## INFO [10:35:48.064] [bbotk] Result of batch 10:
## INFO [10:35:48.065] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:48.065] [bbotk] 12 658 1.062217e-07 0.8128864 0 0 3.269
## INFO [10:35:48.065] [bbotk] uhash
## INFO [10:35:48.065] [bbotk] 4ccd2464-8362-49fd-8f63-72c48e8f6af7
## INFO [10:35:48.068] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:48.075] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:48.077] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:48.616] [mlr3] Finished benchmark
## INFO [10:35:48.627] [bbotk] Result of batch 11:
## INFO [10:35:48.627] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:48.627] [bbotk] 17 62 9.190348e-07 0.6449379 0 0 0.535
## INFO [10:35:48.627] [bbotk] uhash
## INFO [10:35:48.627] [bbotk] c3179d52-f8e0-4ea8-adf5-64d423a4fada
## INFO [10:35:48.629] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:48.636] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:48.638] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:48.707] [mlr3] Finished benchmark
## INFO [10:35:48.718] [bbotk] Result of batch 12:
## INFO [10:35:48.719] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:48.719] [bbotk] 2 286 9.424395e-07 0.6366402 0 0 0.065
## INFO [10:35:48.719] [bbotk] uhash
## INFO [10:35:48.719] [bbotk] 0729192e-fae2-45b6-b4d4-8d4f27b44bb8
## INFO [10:35:48.720] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:48.727] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:48.730] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:50.695] [mlr3] Finished benchmark
## INFO [10:35:50.710] [bbotk] Result of batch 13:
## INFO [10:35:50.710] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:50.710] [bbotk] 10 406 9.855678e-07 0.8431704 0 0 1.961
## INFO [10:35:50.710] [bbotk] uhash
## INFO [10:35:50.710] [bbotk] 40fed0e3-89d5-4f43-a879-668478dc01b5
## INFO [10:35:50.712] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:50.719] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:50.721] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:51.110] [mlr3] Finished benchmark
## INFO [10:35:51.120] [bbotk] Result of batch 14:
## INFO [10:35:51.121] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:51.121] [bbotk] 4 577 3.886486e-07 0.6845624 0 0 0.385
## INFO [10:35:51.121] [bbotk] uhash
## INFO [10:35:51.121] [bbotk] 25eca6f5-3af7-4330-b32c-cdacb56bbbdb
## INFO [10:35:51.123] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:51.130] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:51.132] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:51.175] [mlr3] Finished benchmark
## INFO [10:35:51.186] [bbotk] Result of batch 15:
## INFO [10:35:51.186] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:51.186] [bbotk] 4 265 3.582679e-07 0.6197196 0 0 0.04
## INFO [10:35:51.186] [bbotk] uhash
## INFO [10:35:51.186] [bbotk] a2a3793d-a72c-4878-9d7e-e5e5a8be177b
## INFO [10:35:51.188] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:51.198] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:51.202] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:53.076] [mlr3] Finished benchmark
## INFO [10:35:53.087] [bbotk] Result of batch 16:
## INFO [10:35:53.088] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:53.088] [bbotk] 16 214 7.303307e-07 0.6300657 0 0 1.868
## INFO [10:35:53.088] [bbotk] uhash
## INFO [10:35:53.088] [bbotk] 0e3e9b3c-5b88-4b52-94a4-614ccc11338d
## INFO [10:35:53.089] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:53.096] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:53.099] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:57.594] [mlr3] Finished benchmark
## INFO [10:35:57.606] [bbotk] Result of batch 17:
## INFO [10:35:57.606] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:57.606] [bbotk] 18 962 7.246753e-07 0.6566333 0 0 4.492
## INFO [10:35:57.606] [bbotk] uhash
## INFO [10:35:57.606] [bbotk] 018f1754-2284-426c-8a73-0557264d6852
## INFO [10:35:57.608] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:57.615] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:57.618] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:35:58.195] [mlr3] Finished benchmark
## INFO [10:35:58.214] [bbotk] Result of batch 18:
## INFO [10:35:58.216] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:35:58.216] [bbotk] 12 108 7.257929e-07 0.6724684 0 0 0.575
## INFO [10:35:58.216] [bbotk] uhash
## INFO [10:35:58.216] [bbotk] 8fa1ce5a-5d55-44d8-90a8-5e524dc4b408
## INFO [10:35:58.218] [bbotk] Evaluating 1 configuration(s)
## INFO [10:35:58.224] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:35:58.227] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:01.432] [mlr3] Finished benchmark
## INFO [10:36:01.443] [bbotk] Result of batch 19:
## INFO [10:36:01.443] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:01.443] [bbotk] 21 286 5.155031e-07 0.7036294 0 0 3.201
## INFO [10:36:01.443] [bbotk] uhash
## INFO [10:36:01.443] [bbotk] 837ae4e5-d681-4898-896a-8d13b8eed274
## INFO [10:36:01.445] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:01.452] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:01.454] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:04.453] [mlr3] Finished benchmark
## INFO [10:36:04.464] [bbotk] Result of batch 20:
## INFO [10:36:04.465] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:04.465] [bbotk] 22 299 5.659666e-07 0.6749583 0 0 2.996
## INFO [10:36:04.465] [bbotk] uhash
## INFO [10:36:04.465] [bbotk] 14c9985f-fd06-4540-919c-f730de153d32
## INFO [10:36:04.467] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:04.474] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:04.476] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:05.129] [mlr3] Finished benchmark
## INFO [10:36:05.142] [bbotk] Result of batch 21:
## INFO [10:36:05.143] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:05.143] [bbotk] 7 484 3.701028e-07 0.7396845 0 0 0.645
## INFO [10:36:05.143] [bbotk] uhash
## INFO [10:36:05.143] [bbotk] 2e69c3aa-53f7-4911-9b7b-233a10dcd11b
## INFO [10:36:05.144] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:05.151] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:05.154] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:07.650] [mlr3] Finished benchmark
## INFO [10:36:07.661] [bbotk] Result of batch 22:
## INFO [10:36:07.662] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:07.662] [bbotk] 13 545 8.379664e-07 0.8060298 0 0 2.493
## INFO [10:36:07.662] [bbotk] uhash
## INFO [10:36:07.662] [bbotk] 948cef2d-f847-49a5-933e-27ff258fbb11
## INFO [10:36:07.663] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:07.670] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:07.673] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:08.183] [mlr3] Finished benchmark
## INFO [10:36:08.194] [bbotk] Result of batch 23:
## INFO [10:36:08.194] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:08.194] [bbotk] 13 94 9.123807e-07 0.7293752 0 0 0.506
## INFO [10:36:08.194] [bbotk] uhash
## INFO [10:36:08.194] [bbotk] ad6f0175-f624-4e32-9915-4643dba59986
## INFO [10:36:08.196] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:08.210] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:08.214] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:09.342] [mlr3] Finished benchmark
## INFO [10:36:09.352] [bbotk] Result of batch 24:
## INFO [10:36:09.353] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:09.353] [bbotk] 16 145 9.683526e-07 0.7318467 0 0 1.124
## INFO [10:36:09.353] [bbotk] uhash
## INFO [10:36:09.353] [bbotk] 9fe9e3e2-5394-48ad-be04-05d105d632a3
## INFO [10:36:09.355] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:09.362] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:09.364] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:09.418] [mlr3] Finished benchmark
## INFO [10:36:09.429] [bbotk] Result of batch 25:
## INFO [10:36:09.430] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:09.430] [bbotk] 4 56 6.422795e-07 0.6077973 0 0 0.05
## INFO [10:36:09.430] [bbotk] uhash
## INFO [10:36:09.430] [bbotk] fd4b2898-c183-4ac9-a0be-7f336af95254
## INFO [10:36:09.432] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:09.439] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:09.441] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:11.178] [mlr3] Finished benchmark
## INFO [10:36:11.193] [bbotk] Result of batch 26:
## INFO [10:36:11.193] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:11.193] [bbotk] 18 373 3.008377e-07 0.8462737 0 0 1.733
## INFO [10:36:11.193] [bbotk] uhash
## INFO [10:36:11.193] [bbotk] 4ce956aa-c9e6-4afd-a4d5-6ebab7ce9c7e
## INFO [10:36:11.195] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:11.202] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:11.204] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:17.706] [mlr3] Finished benchmark
## INFO [10:36:17.718] [bbotk] Result of batch 27:
## INFO [10:36:17.719] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:17.719] [bbotk] 24 840 8.142941e-08 0.8347194 0 0 6.498
## INFO [10:36:17.719] [bbotk] uhash
## INFO [10:36:17.719] [bbotk] 4e6c5cf2-b2f8-48ca-811a-84983cd207fa
## INFO [10:36:17.721] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:17.729] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:17.731] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:18.853] [mlr3] Finished benchmark
## INFO [10:36:18.864] [bbotk] Result of batch 28:
## INFO [10:36:18.865] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:18.865] [bbotk] 12 297 5.171562e-07 0.6476303 0 0 1.118
## INFO [10:36:18.865] [bbotk] uhash
## INFO [10:36:18.865] [bbotk] ea7f5b8b-20a2-4daf-a40a-543675d6c16e
## INFO [10:36:18.866] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:18.880] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:18.884] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:19.464] [mlr3] Finished benchmark
## INFO [10:36:19.475] [bbotk] Result of batch 29:
## INFO [10:36:19.476] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:19.476] [bbotk] 20 60 5.757237e-07 0.6457229 0 0 0.576
## INFO [10:36:19.476] [bbotk] uhash
## INFO [10:36:19.476] [bbotk] b4bf2e5a-168e-4b8f-8c8a-dbc6a149f346
## INFO [10:36:19.478] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:19.485] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:19.487] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:19.716] [mlr3] Finished benchmark
## INFO [10:36:19.729] [bbotk] Result of batch 30:
## INFO [10:36:19.730] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:19.730] [bbotk] 3 608 6.570584e-07 0.850395 0 0 0.225
## INFO [10:36:19.730] [bbotk] uhash
## INFO [10:36:19.730] [bbotk] d279d9b3-f117-47a3-8e06-6afa39777bbc
## INFO [10:36:19.733] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:19.743] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:19.746] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:24.896] [mlr3] Finished benchmark
## INFO [10:36:24.909] [bbotk] Result of batch 31:
## INFO [10:36:24.909] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:24.909] [bbotk] 21 407 6.066348e-07 0.8304632 0 0 5.146
## INFO [10:36:24.909] [bbotk] uhash
## INFO [10:36:24.909] [bbotk] 73b56bb3-9b77-4b14-a645-f8b4ebdd7beb
## INFO [10:36:24.911] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:24.918] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:24.920] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:26.686] [mlr3] Finished benchmark
## INFO [10:36:26.697] [bbotk] Result of batch 32:
## INFO [10:36:26.698] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:26.698] [bbotk] 13 270 9.820237e-07 0.7719311 0 0 1.762
## INFO [10:36:26.698] [bbotk] uhash
## INFO [10:36:26.698] [bbotk] a3c96ae1-38bd-4ee2-a556-b0d290b74cf0
## INFO [10:36:26.700] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:26.707] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:26.710] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:31.212] [mlr3] Finished benchmark
## INFO [10:36:31.245] [bbotk] Result of batch 33:
## INFO [10:36:31.246] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:31.246] [bbotk] 24 308 9.99459e-07 0.6649801 0 0 4.497
## INFO [10:36:31.246] [bbotk] uhash
## INFO [10:36:31.246] [bbotk] 3e4261b2-3957-4790-91f0-0b1adb09e6ac
## INFO [10:36:31.248] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:31.256] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:31.259] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:31.982] [mlr3] Finished benchmark
## INFO [10:36:32.000] [bbotk] Result of batch 34:
## INFO [10:36:32.000] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:32.000] [bbotk] 9 840 6.315352e-07 0.6839552 0 0 0.718
## INFO [10:36:32.000] [bbotk] uhash
## INFO [10:36:32.000] [bbotk] b1b84d71-a1b1-4daa-a081-51bf0fda6f31
## INFO [10:36:32.002] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:32.011] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:32.014] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:32.373] [mlr3] Finished benchmark
## INFO [10:36:32.385] [bbotk] Result of batch 35:
## INFO [10:36:32.386] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:32.386] [bbotk] 9 130 2.96043e-07 0.6249939 0 0 0.355
## INFO [10:36:32.386] [bbotk] uhash
## INFO [10:36:32.386] [bbotk] b336595e-b452-45a3-a62d-9a02b7df6718
## INFO [10:36:32.388] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:32.403] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:32.408] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:32.528] [mlr3] Finished benchmark
## INFO [10:36:32.540] [bbotk] Result of batch 36:
## INFO [10:36:32.541] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:32.541] [bbotk] 2 122 8.019102e-07 0.6521195 0 0 0.114
## INFO [10:36:32.541] [bbotk] uhash
## INFO [10:36:32.541] [bbotk] 45321983-3afe-4fb6-9436-b3b260df2ecd
## INFO [10:36:32.542] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:32.550] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:32.552] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:33.518] [mlr3] Finished benchmark
## INFO [10:36:33.529] [bbotk] Result of batch 37:
## INFO [10:36:33.530] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:33.530] [bbotk] 11 934 8.63858e-07 0.6629195 0 0 0.962
## INFO [10:36:33.530] [bbotk] uhash
## INFO [10:36:33.530] [bbotk] 60205a90-02c3-40c5-b71e-efea7351922d
## INFO [10:36:33.532] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:33.539] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:33.541] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:41.883] [mlr3] Finished benchmark
## INFO [10:36:41.896] [bbotk] Result of batch 38:
## INFO [10:36:41.897] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:41.897] [bbotk] 21 962 1.511911e-07 0.6519233 0 0 8.336
## INFO [10:36:41.897] [bbotk] uhash
## INFO [10:36:41.897] [bbotk] c9c4272f-d1d7-441b-8cac-0d34eaa04c10
## INFO [10:36:41.899] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:41.906] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:41.909] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:42.373] [mlr3] Finished benchmark
## INFO [10:36:42.384] [bbotk] Result of batch 39:
## INFO [10:36:42.385] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:42.385] [bbotk] 8 179 8.049895e-07 0.7791372 0 0 0.46
## INFO [10:36:42.385] [bbotk] uhash
## INFO [10:36:42.385] [bbotk] 5228a022-5b9f-443e-9bb5-731a446d7311
## INFO [10:36:42.387] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:42.394] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:42.397] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:43.187] [mlr3] Finished benchmark
## INFO [10:36:43.200] [bbotk] Result of batch 40:
## INFO [10:36:43.201] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:43.201] [bbotk] 5 986 1.818982e-07 0.6516596 0 0 0.786
## INFO [10:36:43.201] [bbotk] uhash
## INFO [10:36:43.201] [bbotk] dda43667-87ad-46a6-83f7-efec2dd05a27
## INFO [10:36:43.202] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:43.209] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:43.212] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:44.187] [mlr3] Finished benchmark
## INFO [10:36:44.199] [bbotk] Result of batch 41:
## INFO [10:36:44.199] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:44.199] [bbotk] 16 481 3.168327e-07 0.6586204 0 0 0.971
## INFO [10:36:44.199] [bbotk] uhash
## INFO [10:36:44.199] [bbotk] cfb95e86-2af7-45c3-b68e-d94497fd6df4
## INFO [10:36:44.203] [bbotk] Finished optimizing after 41 evaluation(s)
## INFO [10:36:44.203] [bbotk] Result:
## INFO [10:36:44.203] [bbotk] size maxit decay learner_param_vals x_domain classif.auc
## INFO [10:36:44.203] [bbotk] 3 608 6.570584e-07 <list[4]> <list[3]> 0.850395
## INFO [10:36:44.377] [mlr3] Applying learner 'classif.nnet.tuned' on task 'credit' (iter 4/5)
## INFO [10:36:44.395] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorRunTime> [secs=90]'
## INFO [10:36:44.401] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:44.408] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:44.411] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:45.468] [mlr3] Finished benchmark
## INFO [10:36:45.478] [bbotk] Result of batch 1:
## INFO [10:36:45.479] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:45.479] [bbotk] 13 933 5.873121e-07 0.7072606 0 0 1.054
## INFO [10:36:45.479] [bbotk] uhash
## INFO [10:36:45.479] [bbotk] b676b8da-8d5f-4aab-9e9b-fcbfca75cae6
## INFO [10:36:45.481] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:45.512] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:45.516] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:45.580] [mlr3] Finished benchmark
## INFO [10:36:45.592] [bbotk] Result of batch 2:
## INFO [10:36:45.593] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:45.593] [bbotk] 4 271 4.296047e-07 0.5957941 0 0 0.057
## INFO [10:36:45.593] [bbotk] uhash
## INFO [10:36:45.593] [bbotk] c79d9ff4-43e4-491c-b707-bbc8d1aff350
## INFO [10:36:45.595] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:45.602] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:45.604] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:49.387] [mlr3] Finished benchmark
## INFO [10:36:49.398] [bbotk] Result of batch 3:
## INFO [10:36:49.399] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:49.399] [bbotk] 18 740 1.411941e-07 0.6741889 0 0 3.78
## INFO [10:36:49.399] [bbotk] uhash
## INFO [10:36:49.399] [bbotk] 1fd57de3-6aff-442b-979e-d7279f716903
## INFO [10:36:49.401] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:49.408] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:49.411] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:49.604] [mlr3] Finished benchmark
## INFO [10:36:49.620] [bbotk] Result of batch 4:
## INFO [10:36:49.621] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:49.621] [bbotk] 8 74 8.99349e-08 0.6161565 0 0 0.19
## INFO [10:36:49.621] [bbotk] uhash
## INFO [10:36:49.621] [bbotk] f2e65bd5-5c95-4404-ba69-d8dc2b94712f
## INFO [10:36:49.624] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:49.637] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:49.640] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:52.035] [mlr3] Finished benchmark
## INFO [10:36:52.046] [bbotk] Result of batch 5:
## INFO [10:36:52.047] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:52.047] [bbotk] 17 567 7.599954e-07 0.6566981 0 0 2.391
## INFO [10:36:52.047] [bbotk] uhash
## INFO [10:36:52.047] [bbotk] 792c0c17-a671-454d-bbb7-ab16045c3e47
## INFO [10:36:52.049] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:52.056] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:52.058] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:52.166] [mlr3] Finished benchmark
## INFO [10:36:52.177] [bbotk] Result of batch 6:
## INFO [10:36:52.178] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:52.178] [bbotk] 6 608 6.955612e-07 0.5906136 0 0 0.104
## INFO [10:36:52.178] [bbotk] uhash
## INFO [10:36:52.178] [bbotk] 7d04a0c4-62b0-4700-a928-4c2bcae6fc59
## INFO [10:36:52.180] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:52.187] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:52.190] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:52.598] [mlr3] Finished benchmark
## INFO [10:36:52.620] [bbotk] Result of batch 7:
## INFO [10:36:52.622] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:52.622] [bbotk] 10 91 8.047404e-07 0.613298 0 0 0.405
## INFO [10:36:52.622] [bbotk] uhash
## INFO [10:36:52.622] [bbotk] 71c8ba89-fb1a-4cd6-b6dd-922cffda818d
## INFO [10:36:52.625] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:52.633] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:52.636] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:53.940] [mlr3] Finished benchmark
## INFO [10:36:53.951] [bbotk] Result of batch 8:
## INFO [10:36:53.952] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:53.952] [bbotk] 16 145 4.668474e-07 0.6553179 0 0 1.301
## INFO [10:36:53.952] [bbotk] uhash
## INFO [10:36:53.952] [bbotk] 772e6264-d911-4946-9727-d264d2278085
## INFO [10:36:53.953] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:53.960] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:53.963] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:36:55.912] [mlr3] Finished benchmark
## INFO [10:36:55.923] [bbotk] Result of batch 9:
## INFO [10:36:55.924] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:36:55.924] [bbotk] 10 560 5.225979e-07 0.6928964 0 0 1.945
## INFO [10:36:55.924] [bbotk] uhash
## INFO [10:36:55.924] [bbotk] e4faf268-32a4-4f38-b5d6-b1bb1dcd873c
## INFO [10:36:55.925] [bbotk] Evaluating 1 configuration(s)
## INFO [10:36:55.933] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:36:55.939] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:00.441] [mlr3] Finished benchmark
## INFO [10:37:00.455] [bbotk] Result of batch 10:
## INFO [10:37:00.456] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:00.456] [bbotk] 23 458 5.701647e-07 0.6486068 0 0 4.496
## INFO [10:37:00.456] [bbotk] uhash
## INFO [10:37:00.456] [bbotk] 59dd1b7c-6e32-4f8f-bc16-f9e63ac937b8
## INFO [10:37:00.458] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:00.465] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:00.467] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:03.415] [mlr3] Finished benchmark
## INFO [10:37:03.431] [bbotk] Result of batch 11:
## INFO [10:37:03.432] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:03.432] [bbotk] 19 326 5.534848e-07 0.7228087 0 0 2.944
## INFO [10:37:03.432] [bbotk] uhash
## INFO [10:37:03.432] [bbotk] 3fe2731f-830c-41ac-a6ad-c5d850f4bae7
## INFO [10:37:03.436] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:03.444] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:03.447] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:05.367] [mlr3] Finished benchmark
## INFO [10:37:05.385] [bbotk] Result of batch 12:
## INFO [10:37:05.386] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:05.386] [bbotk] 11 578 6.760241e-07 0.7131279 0 0 1.916
## INFO [10:37:05.386] [bbotk] uhash
## INFO [10:37:05.386] [bbotk] cdf8a5e7-4a44-42a0-8d4d-02afa6c811f8
## INFO [10:37:05.388] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:05.395] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:05.398] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:12.086] [mlr3] Finished benchmark
## INFO [10:37:12.097] [bbotk] Result of batch 13:
## INFO [10:37:12.098] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:12.098] [bbotk] 22 623 1.139261e-07 0.6635139 0 0 6.685
## INFO [10:37:12.098] [bbotk] uhash
## INFO [10:37:12.098] [bbotk] 4ee8c390-85d4-4cba-b49a-e40bd798c685
## INFO [10:37:12.099] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:12.106] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:12.109] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:12.128] [mlr3] Finished benchmark
## INFO [10:37:12.140] [bbotk] Result of batch 14:
## INFO [10:37:12.140] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:12.140] [bbotk] 4 405 2.359494e-07 0.5 0 0 0.015
## INFO [10:37:12.140] [bbotk] uhash
## INFO [10:37:12.140] [bbotk] 20957a3a-184f-4ad8-9442-5327dd153ab4
## INFO [10:37:12.142] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:12.155] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:12.159] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:16.309] [mlr3] Finished benchmark
## INFO [10:37:16.320] [bbotk] Result of batch 15:
## INFO [10:37:16.321] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:16.321] [bbotk] 24 322 4.050682e-07 0.7397436 0 0 4.145
## INFO [10:37:16.321] [bbotk] uhash
## INFO [10:37:16.321] [bbotk] 247fa9d8-0297-4975-a8cd-091c25052ce2
## INFO [10:37:16.323] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:16.330] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:16.332] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:20.913] [mlr3] Finished benchmark
## INFO [10:37:20.924] [bbotk] Result of batch 16:
## INFO [10:37:20.925] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:20.925] [bbotk] 14 796 7.433595e-07 0.8103087 0 0 4.577
## INFO [10:37:20.925] [bbotk] uhash
## INFO [10:37:20.925] [bbotk] 3472d168-4fd1-431b-8530-4145a34b845e
## INFO [10:37:20.927] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:20.934] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:20.937] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:21.364] [mlr3] Finished benchmark
## INFO [10:37:21.382] [bbotk] Result of batch 17:
## INFO [10:37:21.383] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:21.383] [bbotk] 16 363 7.358206e-07 0.6229919 0 0 0.422
## INFO [10:37:21.383] [bbotk] uhash
## INFO [10:37:21.383] [bbotk] a803c56f-1d49-4a0e-aa16-e403f6f0d09c
## INFO [10:37:21.384] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:21.391] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:21.394] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:21.468] [mlr3] Finished benchmark
## INFO [10:37:21.479] [bbotk] Result of batch 18:
## INFO [10:37:21.480] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:21.480] [bbotk] 5 941 5.690379e-07 0.6185832 0 0 0.071
## INFO [10:37:21.480] [bbotk] uhash
## INFO [10:37:21.480] [bbotk] 55a048df-26ad-4f49-bdd3-6460dac6d3d2
## INFO [10:37:21.482] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:21.489] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:21.492] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:22.900] [mlr3] Finished benchmark
## INFO [10:37:22.912] [bbotk] Result of batch 19:
## INFO [10:37:22.912] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:22.912] [bbotk] 10 982 2.85527e-07 0.8262428 0 0 1.404
## INFO [10:37:22.912] [bbotk] uhash
## INFO [10:37:22.912] [bbotk] 92fbecf1-7850-434b-8999-3809a8a25924
## INFO [10:37:22.914] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:22.928] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:22.932] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:28.264] [mlr3] Finished benchmark
## INFO [10:37:28.277] [bbotk] Result of batch 20:
## INFO [10:37:28.277] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:28.277] [bbotk] 23 487 4.052291e-07 0.6749869 0 0 5.325
## INFO [10:37:28.277] [bbotk] uhash
## INFO [10:37:28.277] [bbotk] f192c0bc-b7f3-4d38-bc1a-36514e235026
## INFO [10:37:28.279] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:28.286] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:28.289] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:30.169] [mlr3] Finished benchmark
## INFO [10:37:30.185] [bbotk] Result of batch 21:
## INFO [10:37:30.186] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:30.186] [bbotk] 9 622 9.051214e-07 0.8196886 0 0 1.872
## INFO [10:37:30.186] [bbotk] uhash
## INFO [10:37:30.186] [bbotk] 41d9d36a-4ba1-4910-b710-3d0a703480c3
## INFO [10:37:30.189] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:30.200] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:30.204] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:30.648] [mlr3] Finished benchmark
## INFO [10:37:30.665] [bbotk] Result of batch 22:
## INFO [10:37:30.666] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:30.666] [bbotk] 8 507 9.07732e-07 0.6089286 0 0 0.439
## INFO [10:37:30.666] [bbotk] uhash
## INFO [10:37:30.666] [bbotk] 35b11852-8351-4fe5-b936-115200e4927e
## INFO [10:37:30.668] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:30.675] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:30.678] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:34.326] [mlr3] Finished benchmark
## INFO [10:37:34.338] [bbotk] Result of batch 23:
## INFO [10:37:34.339] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:34.339] [bbotk] 23 396 6.290843e-07 0.638926 0 0 3.645
## INFO [10:37:34.339] [bbotk] uhash
## INFO [10:37:34.339] [bbotk] 0515713e-50d0-4b55-bf0c-6e75a0c1d68a
## INFO [10:37:34.341] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:34.349] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:34.351] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:34.384] [mlr3] Finished benchmark
## INFO [10:37:34.401] [bbotk] Result of batch 24:
## INFO [10:37:34.402] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:34.402] [bbotk] 4 375 1.842409e-07 0.5970761 0 0 0.029
## INFO [10:37:34.402] [bbotk] uhash
## INFO [10:37:34.402] [bbotk] 64fa2760-cb49-4e9d-925d-fadde6190b8b
## INFO [10:37:34.405] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:34.419] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:34.422] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:36.122] [mlr3] Finished benchmark
## INFO [10:37:36.133] [bbotk] Result of batch 25:
## INFO [10:37:36.134] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:36.134] [bbotk] 9 539 9.52047e-07 0.7998299 0 0 1.696
## INFO [10:37:36.134] [bbotk] uhash
## INFO [10:37:36.134] [bbotk] b994aa0f-b5e1-46b5-8e4b-d9149a242b78
## INFO [10:37:36.136] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:36.143] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:36.146] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:38.666] [mlr3] Finished benchmark
## INFO [10:37:38.678] [bbotk] Result of batch 26:
## INFO [10:37:38.678] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:38.678] [bbotk] 12 890 8.666457e-07 0.6906986 0 0 2.517
## INFO [10:37:38.678] [bbotk] uhash
## INFO [10:37:38.678] [bbotk] 2584956f-e710-4275-8355-b00454688ed3
## INFO [10:37:38.680] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:38.688] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:38.690] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:40.472] [mlr3] Finished benchmark
## INFO [10:37:40.492] [bbotk] Result of batch 27:
## INFO [10:37:40.493] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:40.493] [bbotk] 13 929 4.726298e-07 0.8223312 0 0 1.776
## INFO [10:37:40.493] [bbotk] uhash
## INFO [10:37:40.493] [bbotk] d617db0a-4b53-4c0a-9edf-b8bd79ba21d7
## INFO [10:37:40.495] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:40.502] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:40.505] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:43.794] [mlr3] Finished benchmark
## INFO [10:37:43.805] [bbotk] Result of batch 28:
## INFO [10:37:43.806] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:43.806] [bbotk] 21 349 5.958981e-07 0.6802198 0 0 3.285
## INFO [10:37:43.806] [bbotk] uhash
## INFO [10:37:43.806] [bbotk] 08e9f687-20f8-4454-adcb-dec35ce32723
## INFO [10:37:43.808] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:43.815] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:43.817] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:47.558] [mlr3] Finished benchmark
## INFO [10:37:47.576] [bbotk] Result of batch 29:
## INFO [10:37:47.577] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:47.577] [bbotk] 23 550 6.140905e-07 0.6744309 0 0 3.737
## INFO [10:37:47.577] [bbotk] uhash
## INFO [10:37:47.577] [bbotk] 55163de8-0f35-4b59-95a4-17c5712a8710
## INFO [10:37:47.578] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:47.585] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:47.588] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:47.780] [mlr3] Finished benchmark
## INFO [10:37:47.791] [bbotk] Result of batch 30:
## INFO [10:37:47.792] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:47.792] [bbotk] 4 547 4.933017e-08 0.6349621 0 0 0.188
## INFO [10:37:47.792] [bbotk] uhash
## INFO [10:37:47.792] [bbotk] 92cbfc61-02bf-4775-9070-c82c574d705e
## INFO [10:37:47.793] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:47.801] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:47.803] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:49.918] [mlr3] Finished benchmark
## INFO [10:37:49.936] [bbotk] Result of batch 31:
## INFO [10:37:49.937] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:49.937] [bbotk] 15 263 3.291115e-07 0.757411 0 0 2.11
## INFO [10:37:49.937] [bbotk] uhash
## INFO [10:37:49.937] [bbotk] d96d0752-9c93-4d49-b37e-38c2fac8d143
## INFO [10:37:49.938] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:49.945] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:49.948] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:50.612] [mlr3] Finished benchmark
## INFO [10:37:50.623] [bbotk] Result of batch 32:
## INFO [10:37:50.624] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:50.624] [bbotk] 9 619 1.933113e-07 0.7094715 0 0 0.661
## INFO [10:37:50.624] [bbotk] uhash
## INFO [10:37:50.624] [bbotk] 403d09ce-98d2-4b1b-8985-cb007e99d8a0
## INFO [10:37:50.625] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:50.633] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:50.635] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:51.344] [mlr3] Finished benchmark
## INFO [10:37:51.362] [bbotk] Result of batch 33:
## INFO [10:37:51.363] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:51.363] [bbotk] 8 784 8.29537e-07 0.6883111 0 0 0.704
## INFO [10:37:51.363] [bbotk] uhash
## INFO [10:37:51.363] [bbotk] 5c85fd4c-5d59-4acd-8b1f-e6982952d498
## INFO [10:37:51.364] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:51.371] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:51.374] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:51.589] [mlr3] Finished benchmark
## INFO [10:37:51.600] [bbotk] Result of batch 34:
## INFO [10:37:51.601] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:51.601] [bbotk] 4 685 8.94751e-07 0.6449045 0 0 0.212
## INFO [10:37:51.601] [bbotk] uhash
## INFO [10:37:51.601] [bbotk] c6554c3c-4caa-4b7f-b0f5-8590b49d204b
## INFO [10:37:51.603] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:51.610] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:51.613] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:54.281] [mlr3] Finished benchmark
## INFO [10:37:54.299] [bbotk] Result of batch 35:
## INFO [10:37:54.300] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:54.300] [bbotk] 24 235 5.644007e-09 0.6707025 0 0 2.664
## INFO [10:37:54.300] [bbotk] uhash
## INFO [10:37:54.300] [bbotk] ba83cb0c-84f2-48ef-87fc-a3acd5a84f59
## INFO [10:37:54.303] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:54.311] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:54.313] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:55.276] [mlr3] Finished benchmark
## INFO [10:37:55.287] [bbotk] Result of batch 36:
## INFO [10:37:55.288] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:55.288] [bbotk] 13 986 9.530623e-09 0.6329409 0 0 0.959
## INFO [10:37:55.288] [bbotk] uhash
## INFO [10:37:55.288] [bbotk] 7b3d3589-e70f-456c-b699-109fd44dcf89
## INFO [10:37:55.290] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:55.297] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:55.299] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:37:57.276] [mlr3] Finished benchmark
## INFO [10:37:57.294] [bbotk] Result of batch 37:
## INFO [10:37:57.295] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:37:57.295] [bbotk] 14 536 3.549375e-08 0.6490188 0 0 1.973
## INFO [10:37:57.295] [bbotk] uhash
## INFO [10:37:57.295] [bbotk] 5ee95648-3279-4655-9033-0f20dcabf10a
## INFO [10:37:57.298] [bbotk] Evaluating 1 configuration(s)
## INFO [10:37:57.308] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:37:57.310] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:00.564] [mlr3] Finished benchmark
## INFO [10:38:00.575] [bbotk] Result of batch 38:
## INFO [10:38:00.576] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:00.576] [bbotk] 11 858 1.806053e-07 0.6637755 0 0 3.251
## INFO [10:38:00.576] [bbotk] uhash
## INFO [10:38:00.576] [bbotk] e8cb8a47-8856-4696-9ba5-8a0cd8578f1a
## INFO [10:38:00.578] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:00.585] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:00.588] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:01.680] [mlr3] Finished benchmark
## INFO [10:38:01.691] [bbotk] Result of batch 39:
## INFO [10:38:01.692] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:01.692] [bbotk] 6 724 6.365011e-07 0.8211931 0 0 1.089
## INFO [10:38:01.692] [bbotk] uhash
## INFO [10:38:01.692] [bbotk] cd9cc947-33fc-4860-8a23-b9b49a9a948d
## INFO [10:38:01.694] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:01.706] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:01.710] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:02.643] [mlr3] Finished benchmark
## INFO [10:38:02.658] [bbotk] Result of batch 40:
## INFO [10:38:02.659] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:02.659] [bbotk] 11 217 9.315255e-07 0.8274987 0 0 0.926
## INFO [10:38:02.659] [bbotk] uhash
## INFO [10:38:02.659] [bbotk] 8ddf00c8-f6a3-4dce-bf83-7ab38451d253
## INFO [10:38:02.661] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:02.668] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:02.670] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:04.947] [mlr3] Finished benchmark
## INFO [10:38:04.958] [bbotk] Result of batch 41:
## INFO [10:38:04.959] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:04.959] [bbotk] 10 565 3.508323e-07 0.8152669 0 0 2.274
## INFO [10:38:04.959] [bbotk] uhash
## INFO [10:38:04.959] [bbotk] 869c489f-2dcb-4060-8a68-613ef0155e50
## INFO [10:38:04.961] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:04.968] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:04.970] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:08.310] [mlr3] Finished benchmark
## INFO [10:38:08.328] [bbotk] Result of batch 42:
## INFO [10:38:08.329] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:08.329] [bbotk] 17 802 1.271779e-07 0.7218472 0 0 3.334
## INFO [10:38:08.329] [bbotk] uhash
## INFO [10:38:08.329] [bbotk] ef0cd30c-c07b-4a2f-bee1-f1d8b7079b41
## INFO [10:38:08.332] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:08.339] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:08.342] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:08.416] [mlr3] Finished benchmark
## INFO [10:38:08.427] [bbotk] Result of batch 43:
## INFO [10:38:08.428] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:08.428] [bbotk] 1 176 4.740726e-08 0.5961931 0 0 0.07
## INFO [10:38:08.428] [bbotk] uhash
## INFO [10:38:08.428] [bbotk] 64789539-d74e-46cf-b894-f2caea87a9bb
## INFO [10:38:08.430] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:08.437] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:08.439] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:09.218] [mlr3] Finished benchmark
## INFO [10:38:09.236] [bbotk] Result of batch 44:
## INFO [10:38:09.238] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:09.238] [bbotk] 10 724 8.951984e-07 0.6751832 0 0 0.776
## INFO [10:38:09.238] [bbotk] uhash
## INFO [10:38:09.238] [bbotk] ed728861-37e8-41d8-aed1-fe9029e8763c
## INFO [10:38:09.241] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:09.254] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:09.257] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:09.322] [mlr3] Finished benchmark
## INFO [10:38:09.333] [bbotk] Result of batch 45:
## INFO [10:38:09.333] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:09.333] [bbotk] 8 260 3.043118e-08 0.5918956 0 0 0.061
## INFO [10:38:09.333] [bbotk] uhash
## INFO [10:38:09.333] [bbotk] 3559981d-0118-425a-9d21-2ad6238c7aa9
## INFO [10:38:09.335] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:09.342] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:09.344] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:09.426] [mlr3] Finished benchmark
## INFO [10:38:09.438] [bbotk] Result of batch 46:
## INFO [10:38:09.439] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:09.439] [bbotk] 4 441 8.399596e-07 0.5915489 0 0 0.078
## INFO [10:38:09.439] [bbotk] uhash
## INFO [10:38:09.439] [bbotk] f968bc22-c41c-4f03-b365-ca49d53439dc
## INFO [10:38:09.440] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:09.448] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:09.450] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:10.083] [mlr3] Finished benchmark
## INFO [10:38:10.100] [bbotk] Result of batch 47:
## INFO [10:38:10.101] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:10.101] [bbotk] 8 235 9.788883e-07 0.7599621 0 0 0.624
## INFO [10:38:10.101] [bbotk] uhash
## INFO [10:38:10.101] [bbotk] d7a61330-7711-4d29-88ed-cb0bfa48a9a4
## INFO [10:38:10.104] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:10.111] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:10.114] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:14.599] [mlr3] Finished benchmark
## INFO [10:38:14.610] [bbotk] Result of batch 48:
## INFO [10:38:14.611] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:14.611] [bbotk] 23 352 5.996979e-07 0.8171507 0 0 4.482
## INFO [10:38:14.611] [bbotk] uhash
## INFO [10:38:14.611] [bbotk] 058d21f4-10dc-4280-8b30-54f5d4697bc8
## INFO [10:38:14.614] [bbotk] Finished optimizing after 48 evaluation(s)
## INFO [10:38:14.614] [bbotk] Result:
## INFO [10:38:14.615] [bbotk] size maxit decay learner_param_vals x_domain classif.auc
## INFO [10:38:14.615] [bbotk] 11 217 9.315255e-07 <list[4]> <list[3]> 0.8274987
## INFO [10:38:16.134] [mlr3] Applying learner 'classif.nnet.tuned' on task 'credit' (iter 5/5)
## INFO [10:38:16.158] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorRunTime> [secs=90]'
## INFO [10:38:16.164] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:16.171] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:16.174] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:24.818] [mlr3] Finished benchmark
## INFO [10:38:24.828] [bbotk] Result of batch 1:
## INFO [10:38:24.829] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:24.829] [bbotk] 25 889 1.04593e-07 0.8425485 0 0 8.64
## INFO [10:38:24.829] [bbotk] uhash
## INFO [10:38:24.829] [bbotk] 8a163aa4-64de-4fd0-90e4-bde68cdd188d
## INFO [10:38:24.831] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:24.842] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:24.846] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:27.098] [mlr3] Finished benchmark
## INFO [10:38:27.114] [bbotk] Result of batch 2:
## INFO [10:38:27.115] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:27.115] [bbotk] 13 323 3.568332e-07 0.7419883 0 0 2.247
## INFO [10:38:27.115] [bbotk] uhash
## INFO [10:38:27.115] [bbotk] ea9ce0b4-57b8-47d5-baa2-0e8ec08d5bcf
## INFO [10:38:27.117] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:27.123] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:27.126] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:33.039] [mlr3] Finished benchmark
## INFO [10:38:33.050] [bbotk] Result of batch 3:
## INFO [10:38:33.051] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:33.051] [bbotk] 21 567 2.635135e-07 0.7316282 0 0 5.91
## INFO [10:38:33.051] [bbotk] uhash
## INFO [10:38:33.051] [bbotk] 4aa0a6d4-47f2-48d2-9c7a-da4612e50fd1
## INFO [10:38:33.053] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:33.060] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:33.063] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:34.284] [mlr3] Finished benchmark
## INFO [10:38:34.302] [bbotk] Result of batch 4:
## INFO [10:38:34.303] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:34.303] [bbotk] 11 270 9.080826e-07 0.6666297 0 0 1.216
## INFO [10:38:34.303] [bbotk] uhash
## INFO [10:38:34.303] [bbotk] 54688ffb-c95e-476f-802a-adf8a557eb74
## INFO [10:38:34.306] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:34.313] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:34.316] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:36.051] [mlr3] Finished benchmark
## INFO [10:38:36.062] [bbotk] Result of batch 5:
## INFO [10:38:36.063] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:36.063] [bbotk] 14 296 4.006173e-07 0.6363989 0 0 1.732
## INFO [10:38:36.063] [bbotk] uhash
## INFO [10:38:36.063] [bbotk] 54ee87e2-32e5-4736-94e1-f533ce5b4074
## INFO [10:38:36.065] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:36.081] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:36.085] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:38.707] [mlr3] Finished benchmark
## INFO [10:38:38.718] [bbotk] Result of batch 6:
## INFO [10:38:38.718] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:38.718] [bbotk] 15 432 2.614097e-08 0.6444814 0 0 2.616
## INFO [10:38:38.718] [bbotk] uhash
## INFO [10:38:38.718] [bbotk] c4bb30b9-7301-4126-b550-f2e3c26114c9
## INFO [10:38:38.720] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:38.727] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:38.730] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:39.498] [mlr3] Finished benchmark
## INFO [10:38:39.525] [bbotk] Result of batch 7:
## INFO [10:38:39.527] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:39.527] [bbotk] 10 165 1.146371e-07 0.6898861 0 0 0.765
## INFO [10:38:39.527] [bbotk] uhash
## INFO [10:38:39.527] [bbotk] fbf6879b-4009-47d7-a14e-e7b48906d53c
## INFO [10:38:39.529] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:39.543] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:39.547] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:39.690] [mlr3] Finished benchmark
## INFO [10:38:39.701] [bbotk] Result of batch 8:
## INFO [10:38:39.702] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:39.702] [bbotk] 4 83 7.507029e-07 0.6635026 0 0 0.139
## INFO [10:38:39.702] [bbotk] uhash
## INFO [10:38:39.702] [bbotk] 7fbef4e3-8bf4-4209-9bf0-e9b215c8e4e3
## INFO [10:38:39.704] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:39.711] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:39.713] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:42.238] [mlr3] Finished benchmark
## INFO [10:38:42.250] [bbotk] Result of batch 9:
## INFO [10:38:42.251] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:42.251] [bbotk] 15 514 4.580805e-07 0.6798954 0 0 2.52
## INFO [10:38:42.251] [bbotk] uhash
## INFO [10:38:42.251] [bbotk] cd7231dd-b555-4ff6-ac77-ffc0b55a5192
## INFO [10:38:42.252] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:42.261] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:42.268] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:44.630] [mlr3] Finished benchmark
## INFO [10:38:44.647] [bbotk] Result of batch 10:
## INFO [10:38:44.648] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:44.648] [bbotk] 15 408 2.319003e-07 0.8261988 0 0 2.355
## INFO [10:38:44.648] [bbotk] uhash
## INFO [10:38:44.648] [bbotk] 2af22fdb-b405-46e0-93a2-19846476e2d5
## INFO [10:38:44.651] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:44.659] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:44.662] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:45.082] [mlr3] Finished benchmark
## INFO [10:38:45.093] [bbotk] Result of batch 11:
## INFO [10:38:45.093] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:45.093] [bbotk] 12 315 1.059144e-07 0.6617051 0 0 0.417
## INFO [10:38:45.093] [bbotk] uhash
## INFO [10:38:45.093] [bbotk] a2c21be3-718e-41ca-934f-c8ddf96e460d
## INFO [10:38:45.095] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:45.102] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:45.105] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:48.928] [mlr3] Finished benchmark
## INFO [10:38:48.946] [bbotk] Result of batch 12:
## INFO [10:38:48.947] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:48.947] [bbotk] 19 422 7.906792e-07 0.697667 0 0 3.819
## INFO [10:38:48.947] [bbotk] uhash
## INFO [10:38:48.947] [bbotk] e9b0a282-614a-4a0b-90cc-a4e697dd0ca8
## INFO [10:38:48.950] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:48.960] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:48.963] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:48.976] [mlr3] Finished benchmark
## INFO [10:38:48.987] [bbotk] Result of batch 13:
## INFO [10:38:48.988] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:48.988] [bbotk] 1 65 5.314839e-07 0.5896584 0 0 0.011
## INFO [10:38:48.988] [bbotk] uhash
## INFO [10:38:48.988] [bbotk] f4587216-1371-4077-a67f-8c02fd8c559c
## INFO [10:38:48.989] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:48.997] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:48.999] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:49.111] [mlr3] Finished benchmark
## INFO [10:38:49.127] [bbotk] Result of batch 14:
## INFO [10:38:49.128] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:49.128] [bbotk] 5 245 8.387533e-08 0.5834287 0 0 0.108
## INFO [10:38:49.128] [bbotk] uhash
## INFO [10:38:49.128] [bbotk] 3f1b38e7-4d28-4d54-a297-a8ba70ca0728
## INFO [10:38:49.131] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:49.144] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:49.148] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:49.301] [mlr3] Finished benchmark
## INFO [10:38:49.312] [bbotk] Result of batch 15:
## INFO [10:38:49.312] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:49.312] [bbotk] 4 884 8.925806e-07 0.569289 0 0 0.149
## INFO [10:38:49.312] [bbotk] uhash
## INFO [10:38:49.312] [bbotk] 670bd64c-229a-4cdb-a2eb-b8906a9edc5e
## INFO [10:38:49.314] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:49.321] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:49.323] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:50.410] [mlr3] Finished benchmark
## INFO [10:38:50.421] [bbotk] Result of batch 16:
## INFO [10:38:50.421] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:50.421] [bbotk] 8 344 7.310005e-07 0.7049738 0 0 1.083
## INFO [10:38:50.421] [bbotk] uhash
## INFO [10:38:50.421] [bbotk] 2f3a47d6-20cc-4cf6-bf88-0693604dfd1c
## INFO [10:38:50.423] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:50.430] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:50.433] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:50.857] [mlr3] Finished benchmark
## INFO [10:38:50.874] [bbotk] Result of batch 17:
## INFO [10:38:50.875] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:50.875] [bbotk] 8 145 1.801951e-07 0.6134503 0 0 0.419
## INFO [10:38:50.875] [bbotk] uhash
## INFO [10:38:50.875] [bbotk] 0832715a-181e-4b07-aa95-a8ae831e15d0
## INFO [10:38:50.878] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:50.887] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:50.890] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:52.822] [mlr3] Finished benchmark
## INFO [10:38:52.833] [bbotk] Result of batch 18:
## INFO [10:38:52.834] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:52.834] [bbotk] 9 839 3.180075e-07 0.7768052 0 0 1.928
## INFO [10:38:52.834] [bbotk] uhash
## INFO [10:38:52.834] [bbotk] db2a5337-bba2-4ddb-980c-59270d80fc35
## INFO [10:38:52.835] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:52.842] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:52.845] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:56.697] [mlr3] Finished benchmark
## INFO [10:38:56.708] [bbotk] Result of batch 19:
## INFO [10:38:56.708] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:56.708] [bbotk] 23 313 7.692487e-07 0.7162696 0 0 3.848
## INFO [10:38:56.708] [bbotk] uhash
## INFO [10:38:56.708] [bbotk] b1e1a86e-1e09-445a-8ec2-5706d22a8f6b
## INFO [10:38:56.710] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:56.717] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:56.719] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:38:57.066] [mlr3] Finished benchmark
## INFO [10:38:57.077] [bbotk] Result of batch 20:
## INFO [10:38:57.077] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:38:57.077] [bbotk] 5 493 5.379358e-07 0.6663897 0 0 0.343
## INFO [10:38:57.077] [bbotk] uhash
## INFO [10:38:57.077] [bbotk] 71d1051e-8456-44da-ba61-6082a6931cd3
## INFO [10:38:57.079] [bbotk] Evaluating 1 configuration(s)
## INFO [10:38:57.086] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:38:57.089] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:00.521] [mlr3] Finished benchmark
## INFO [10:39:00.532] [bbotk] Result of batch 21:
## INFO [10:39:00.533] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:00.533] [bbotk] 22 278 9.333214e-07 0.7110619 0 0 3.429
## INFO [10:39:00.533] [bbotk] uhash
## INFO [10:39:00.533] [bbotk] 10e96384-dbcc-4a24-9f20-06528b2f4d11
## INFO [10:39:00.535] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:00.542] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:00.544] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:00.555] [mlr3] Finished benchmark
## INFO [10:39:00.567] [bbotk] Result of batch 22:
## INFO [10:39:00.568] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:00.568] [bbotk] 1 417 6.741705e-07 0.5 0 0 0.007
## INFO [10:39:00.568] [bbotk] uhash
## INFO [10:39:00.568] [bbotk] cc2ab1d3-e6f7-4f37-865c-cde85b07e3fa
## INFO [10:39:00.570] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:00.577] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:00.580] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:00.761] [mlr3] Finished benchmark
## INFO [10:39:00.772] [bbotk] Result of batch 23:
## INFO [10:39:00.772] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:00.772] [bbotk] 7 744 3.149061e-07 0.6594952 0 0 0.174
## INFO [10:39:00.772] [bbotk] uhash
## INFO [10:39:00.772] [bbotk] c8bd2074-6de3-4034-b8c6-5db12a8ccb76
## INFO [10:39:00.774] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:00.781] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:00.783] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:04.911] [mlr3] Finished benchmark
## INFO [10:39:04.922] [bbotk] Result of batch 24:
## INFO [10:39:04.922] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:04.922] [bbotk] 16 744 4.482913e-07 0.6768544 0 0 4.124
## INFO [10:39:04.922] [bbotk] uhash
## INFO [10:39:04.922] [bbotk] f5bffe1f-1ff1-4783-b43d-99da3e112415
## INFO [10:39:04.924] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:04.931] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:04.934] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:05.035] [mlr3] Finished benchmark
## INFO [10:39:05.047] [bbotk] Result of batch 25:
## INFO [10:39:05.047] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:05.047] [bbotk] 2 159 6.673346e-07 0.6404309 0 0 0.097
## INFO [10:39:05.047] [bbotk] uhash
## INFO [10:39:05.047] [bbotk] 38810a8d-b1c4-4684-83b7-5df0a756eb06
## INFO [10:39:05.049] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:05.056] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:05.059] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:09.073] [mlr3] Finished benchmark
## INFO [10:39:09.084] [bbotk] Result of batch 26:
## INFO [10:39:09.085] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:09.085] [bbotk] 18 690 2.191951e-07 0.623755 0 0 4.011
## INFO [10:39:09.085] [bbotk] uhash
## INFO [10:39:09.085] [bbotk] 83c4328f-9ca3-4c18-b02f-e72c753c9bef
## INFO [10:39:09.087] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:09.093] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:09.096] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:11.720] [mlr3] Finished benchmark
## INFO [10:39:11.731] [bbotk] Result of batch 27:
## INFO [10:39:11.731] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:11.731] [bbotk] 12 883 5.961912e-07 0.6770452 0 0 2.621
## INFO [10:39:11.731] [bbotk] uhash
## INFO [10:39:11.731] [bbotk] 5f3f352e-3da6-4e25-8bc2-7537fb90a652
## INFO [10:39:11.733] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:11.740] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:11.742] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:13.609] [mlr3] Finished benchmark
## INFO [10:39:13.620] [bbotk] Result of batch 28:
## INFO [10:39:13.621] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:13.621] [bbotk] 17 297 9.055221e-07 0.6353524 0 0 1.863
## INFO [10:39:13.621] [bbotk] uhash
## INFO [10:39:13.621] [bbotk] 6ea545df-7ec8-4ef9-b843-d7390c1d762d
## INFO [10:39:13.622] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:13.629] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:13.632] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:13.965] [mlr3] Finished benchmark
## INFO [10:39:13.976] [bbotk] Result of batch 29:
## INFO [10:39:13.976] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:13.976] [bbotk] 5 325 8.820898e-08 0.6500339 0 0 0.33
## INFO [10:39:13.976] [bbotk] uhash
## INFO [10:39:13.976] [bbotk] 5bbc8410-2914-46d8-a7cf-e1c927cafbff
## INFO [10:39:13.978] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:13.985] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:13.988] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:14.768] [mlr3] Finished benchmark
## INFO [10:39:14.779] [bbotk] Result of batch 30:
## INFO [10:39:14.780] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:14.780] [bbotk] 6 959 4.673044e-07 0.635414 0 0 0.777
## INFO [10:39:14.780] [bbotk] uhash
## INFO [10:39:14.780] [bbotk] 6e3d58bd-4ec9-4edb-80a8-08f12b38a5f3
## INFO [10:39:14.782] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:14.788] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:14.791] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:18.748] [mlr3] Finished benchmark
## INFO [10:39:18.759] [bbotk] Result of batch 31:
## INFO [10:39:18.760] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:18.760] [bbotk] 23 330 4.673104e-07 0.6809357 0 0 3.954
## INFO [10:39:18.760] [bbotk] uhash
## INFO [10:39:18.760] [bbotk] 87c3be62-e127-4c09-9f4c-6f66ae5792ee
## INFO [10:39:18.762] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:18.769] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:18.771] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:22.063] [mlr3] Finished benchmark
## INFO [10:39:22.074] [bbotk] Result of batch 32:
## INFO [10:39:22.075] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:22.075] [bbotk] 24 882 1.452788e-07 0.6619945 0 0 3.288
## INFO [10:39:22.075] [bbotk] uhash
## INFO [10:39:22.075] [bbotk] d4ee770e-a3e3-402b-aab7-464cb09affdd
## INFO [10:39:22.076] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:22.083] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:22.086] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:22.872] [mlr3] Finished benchmark
## INFO [10:39:22.885] [bbotk] Result of batch 33:
## INFO [10:39:22.886] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:22.886] [bbotk] 15 892 5.986936e-07 0.675611 0 0 0.782
## INFO [10:39:22.886] [bbotk] uhash
## INFO [10:39:22.886] [bbotk] e8a1f72f-e428-4b48-be88-e69987844123
## INFO [10:39:22.888] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:22.895] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:22.897] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:25.533] [mlr3] Finished benchmark
## INFO [10:39:25.544] [bbotk] Result of batch 34:
## INFO [10:39:25.545] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:25.545] [bbotk] 15 646 7.833465e-07 0.6322992 0 0 2.632
## INFO [10:39:25.545] [bbotk] uhash
## INFO [10:39:25.545] [bbotk] ed29ef1a-df82-43e1-ad3b-8191e02ee811
## INFO [10:39:25.546] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:25.553] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:25.556] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:26.417] [mlr3] Finished benchmark
## INFO [10:39:26.429] [bbotk] Result of batch 35:
## INFO [10:39:26.430] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:26.430] [bbotk] 14 140 4.907423e-07 0.6210834 0 0 0.858
## INFO [10:39:26.430] [bbotk] uhash
## INFO [10:39:26.430] [bbotk] f6c241e4-3a8b-4442-a8e0-c8bc2094cfda
## INFO [10:39:26.431] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:26.439] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:26.441] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:27.792] [mlr3] Finished benchmark
## INFO [10:39:27.803] [bbotk] Result of batch 36:
## INFO [10:39:27.803] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:27.803] [bbotk] 15 684 9.01418e-07 0.6507479 0 0 1.347
## INFO [10:39:27.803] [bbotk] uhash
## INFO [10:39:27.803] [bbotk] 1ea0fe91-fc9c-485e-8614-1da86498185a
## INFO [10:39:27.805] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:27.812] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:27.815] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:28.020] [mlr3] Finished benchmark
## INFO [10:39:28.034] [bbotk] Result of batch 37:
## INFO [10:39:28.035] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:28.035] [bbotk] 6 100 3.740383e-07 0.6364112 0 0 0.201
## INFO [10:39:28.035] [bbotk] uhash
## INFO [10:39:28.035] [bbotk] 62882319-b3a2-473c-9980-598e7bce1a86
## INFO [10:39:28.037] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:28.043] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:28.046] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:30.917] [mlr3] Finished benchmark
## INFO [10:39:30.928] [bbotk] Result of batch 38:
## INFO [10:39:30.929] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:30.929] [bbotk] 21 305 5.184147e-07 0.7089812 0 0 2.868
## INFO [10:39:30.929] [bbotk] uhash
## INFO [10:39:30.929] [bbotk] d4be098e-c6dd-4dee-8306-8077b311f5f3
## INFO [10:39:30.931] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:30.938] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:30.940] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:32.011] [mlr3] Finished benchmark
## INFO [10:39:32.022] [bbotk] Result of batch 39:
## INFO [10:39:32.022] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:32.022] [bbotk] 12 559 1.924962e-07 0.6899169 0 0 1.067
## INFO [10:39:32.022] [bbotk] uhash
## INFO [10:39:32.022] [bbotk] 2fa94349-11ba-47a2-952e-1db66591fccc
## INFO [10:39:32.024] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:32.031] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:32.034] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:34.320] [mlr3] Finished benchmark
## INFO [10:39:34.331] [bbotk] Result of batch 40:
## INFO [10:39:34.332] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:34.332] [bbotk] 19 217 8.266657e-08 0.7205479 0 0 2.282
## INFO [10:39:34.332] [bbotk] uhash
## INFO [10:39:34.332] [bbotk] ae5cc932-db0f-40fe-99f0-ad08ace32c3c
## INFO [10:39:34.338] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:34.345] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:34.347] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:41.035] [mlr3] Finished benchmark
## INFO [10:39:41.048] [bbotk] Result of batch 41:
## INFO [10:39:41.049] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:41.049] [bbotk] 21 543 2.554367e-07 0.8345214 0 0 6.684
## INFO [10:39:41.049] [bbotk] uhash
## INFO [10:39:41.049] [bbotk] b1341b32-d71f-4b90-aeb1-282ab91a9a5a
## INFO [10:39:41.051] [bbotk] Evaluating 1 configuration(s)
## INFO [10:39:41.059] [mlr3] Running benchmark with 1 resampling iterations
## INFO [10:39:41.061] [mlr3] Applying learner 'classif.nnet' on task 'credit' (iter 1/1)
## INFO [10:39:49.531] [mlr3] Finished benchmark
## INFO [10:39:49.542] [bbotk] Result of batch 42:
## INFO [10:39:49.543] [bbotk] size maxit decay classif.auc warnings errors runtime_learners
## INFO [10:39:49.543] [bbotk] 20 877 6.086415e-07 0.7544475 0 0 8.467
## INFO [10:39:49.543] [bbotk] uhash
## INFO [10:39:49.543] [bbotk] 8d3b8a8c-bec8-4068-b58d-546859c486cf
## INFO [10:39:49.546] [bbotk] Finished optimizing after 42 evaluation(s)
## INFO [10:39:49.546] [bbotk] Result:
## INFO [10:39:49.547] [bbotk] size maxit decay learner_param_vals x_domain classif.auc
## INFO [10:39:49.547] [bbotk] 25 889 1.04593e-07 <list[4]> <list[3]> 0.8425485## Note - Terminator may need to be time based for efficiency sake if using mbo tuning. Running it for 30 iterations takes more time (approx 25 minutes). Tuning using this method yielded worse results
## Note - The second run we adjusted the terminator to 25 evaluations, tuner to grid search, and number of inner folds to 3. Run time - 12 minutes. Results - No improvement over the base model. Definite improvement over the first run.
## Note - The third run we adjusted the terminator to time based evaluations and the inner resampling was adjusted to the holdout method using a 0.8 ratio. Run time - 8 minutes. This approach vastly improved our outer AUC score to approximately 0.8.
end = Sys.time()## Amount of time to run the previous chunk
end - start## Time difference of 7.901592 minsParameter Value Tuning Results
Inner CV Results
## Extract tuning results for the inner sampling
extract_inner_tuning_results(credit_nn_v3)[ , list(maxit, decay, size, classif.auc)]## maxit decay size classif.auc
## 1: 524 8.752843e-07 10 0.8374610
## 2: 994 6.003776e-07 14 0.8213050
## 3: 608 6.570584e-07 3 0.8503950
## 4: 217 9.315255e-07 11 0.8274987
## 5: 889 1.045930e-07 25 0.8425485Intepretation Note: The third fold presents the best AUC score of approximately 0.850395
Outer CV Results
## Test Data AUC
credit_nn_v3$score(credit_msr_auc)[ , list(classif.auc)]## classif.auc
## 1: 0.8057938
## 2: 0.7531414
## 3: 0.6709426
## 4: 0.7673972
## 5: 0.7334859Interpretation Note: Although the 3rd fold presents the best results on the inner resampling, the 1st fold provides the best prediction as the AUC score is 0.8057938. As a result, we extracted the following values from the 1st fold to build our final model:
- maxit: 524
- decay: 8.752843^{-7}
- size: 10
Aggregate Results
##Aggregate Results
credit_nn_v3$aggregate(credit_msr_auc)## classif.auc
## 0.7461522## Extract the maxit, decay, and size from model ## to build our full model
credit_lrn_nn = lrn("classif.nnet",
size = extract_inner_tuning_results(credit_nn_v3)[1]$size,
maxit = extract_inner_tuning_results(credit_nn_v3)[1]$maxit,
decay = extract_inner_tuning_results(credit_nn_v3)[1]$decay)Full Model Build and Visualization
Note: This section is additional practice for building the full model and not required for the exercise.
## Full Model Build
credit_nn.full = credit_lrn_nn$train(credit_task)## # weights: 241
## initial value 5056.597318
## iter 10 value 2193.382624
## iter 20 value 2166.343852
## iter 30 value 2143.549895
## iter 40 value 2139.381161
## iter 50 value 2133.007723
## iter 60 value 2119.085102
## iter 70 value 2113.150157
## iter 80 value 2111.286632
## iter 90 value 2109.451370
## iter 100 value 2083.670665
## iter 110 value 2069.411293
## iter 120 value 2046.862996
## iter 130 value 2024.765518
## iter 140 value 2009.487852
## iter 150 value 2006.777177
## iter 160 value 2005.185488
## iter 170 value 2000.921818
## iter 180 value 2000.454021
## iter 190 value 1999.919863
## iter 200 value 1999.210326
## iter 210 value 1998.646387
## iter 220 value 1996.878936
## iter 230 value 1995.762600
## iter 240 value 1991.734060
## iter 250 value 1990.328831
## iter 260 value 1987.771345
## iter 270 value 1976.002268
## iter 280 value 1967.206486
## iter 290 value 1962.796074
## iter 300 value 1958.360302
## iter 310 value 1957.838244
## iter 320 value 1957.386225
## iter 330 value 1957.318951
## iter 340 value 1957.087311
## iter 350 value 1956.961131
## iter 360 value 1956.594081
## iter 370 value 1956.292455
## iter 380 value 1955.995223
## iter 390 value 1955.771001
## final value 1955.642988
## converged## Load the required package
library(nnet)
## Rebuild the model
credit_nn_final = nnet(Status ~ .,
credit_data,
size = extract_inner_tuning_results(credit_nn_v3)[1]$size,
maxit = extract_inner_tuning_results(credit_nn_v3)[1]$maxit,
decay = extract_inner_tuning_results(credit_nn_v3)[1]$decay)## # weights: 241
## initial value 2533.456963
## iter 10 value 2177.437717
## iter 20 value 2141.319800
## iter 30 value 2124.540273
## iter 40 value 2118.550600
## iter 50 value 2104.908047
## iter 60 value 2096.268865
## iter 70 value 2075.247314
## iter 80 value 2070.856332
## iter 90 value 2049.007364
## iter 100 value 2034.468560
## iter 110 value 2027.090354
## iter 120 value 2015.270567
## iter 130 value 2008.250373
## iter 140 value 2005.466426
## iter 150 value 2000.879169
## iter 160 value 1983.672486
## iter 170 value 1966.363502
## iter 180 value 1907.614967
## iter 190 value 1815.622408
## iter 200 value 1781.986478
## iter 210 value 1772.146893
## iter 220 value 1766.454783
## iter 230 value 1761.880164
## iter 240 value 1734.991056
## iter 250 value 1721.847653
## iter 260 value 1697.310628
## iter 270 value 1687.605628
## iter 280 value 1684.522077
## iter 290 value 1679.605531
## iter 300 value 1678.550668
## iter 310 value 1676.349025
## iter 320 value 1667.612257
## iter 330 value 1661.180088
## iter 340 value 1657.527769
## iter 350 value 1656.341063
## iter 360 value 1656.169210
## iter 370 value 1655.688693
## iter 380 value 1655.165405
## iter 390 value 1654.916377
## iter 390 value 1654.916372
## iter 390 value 1654.916364
## final value 1654.916364
## converged##Neural Network Plot
plot(credit_nn_final)
Summary
I tuned the size of the hidden layer, maximum number of iterations, and the decay function of the credit data three times using the following approaches:
Please note that the parameter sets were held constant through each approach. The size ranged from 1-25, the maximum iterations ranged from 50-1000, and the decay ranged from 0-1e-5. I did adjust the upper bounds of the decay function to 1e-6 on the third approach as an experiment to improve our model’s performance. Additionally, the same performance measure was used during each approach.
Approach 1: This approach used the following setup: tuner - “mbo” - Bayesian Optimization evaluation - “evals” - Set to 30 evaluations inner resampling - “cv” - Set to 5 folds
This approach yielded worse AUC scores for both our inner and outer resampling compared to our initial model. Additionally, it took approximately 25 minutes to run.
Approach 2: This approach used the following setup: tuner - “grid_search” - Grid Search evaluation - “evals” - Set to 25 evaluations inner resampling - “cv” - Set to 3 folds
This approach yielded similar AUC scores for both our inner and outer resampling compared to our initial model. The run time improved significantly as it took approximately 12 minutes to process.
Approach 3: This approach used the following setup: tuner - “random_search” - Random Search evaluation - “run_time” - Set to 90 seconds inner resampling - “holdout” - Set to a 0.8 ratio
This approach yielded better AUC scores for both our inner and outer resampling compared to our initial model. The run time improved significantly as it took approximately 8 minutes to process. This approach was selected to tune our final model as it yielded the best results and required the least computing time.
Approach 3’s tuning parameters and inner cross-validation results are listed above along with the outer cross-validation results. To reiterate, the third inner fold presents the best AUC score of approximately 0.850395. Although the 3rd fold presents the best results on the inner resampling, the 1st fold provides the best prediction as the AUC score is 0.8057938. As a result, we extracted the following values from the 1st fold to build our final model:
- maxit: 524
- decay: 8.752843^{-7}
- size: 10
Future experiments on this model could include adjusting the parameter set values for the tuning and using approach 3 to see if one could improve the model performance.