We are basically saying that given the presence of Genres(using the top 8) by month we are going to be able to predict whether the month results (streams=popularity)is going to be satisfactory. The majority of the genre counts in my data set is coming from the top 8 genres.

#install.packages("rpart")
#install.packages("partykit")
#install.packages("randomForest")
#install.packages("xgboost")
#install.packages("caret")

Let us first call a group libraries that we will need for this project.

library(e1071)
library(rpart)
library(partykit)
## Loading required package: grid
## Loading required package: libcoin
## Loading required package: mvtnorm
library(randomForest)
## randomForest 4.6-14
## Type rfNews() to see new features/changes/bug fixes.
library(xgboost)
library(caret)
## Loading required package: lattice
## Loading required package: ggplot2
## 
## Attaching package: 'ggplot2'
## The following object is masked from 'package:randomForest':
## 
##     margin

Always confirm the working directory

getwd()
## [1] "C:/Users/Norge/Documents"

The csv file we are using is called timeseries-project2 and is stored in the working directory. The name is due to the fact that we initially created to do time series analysis but found out that there was no seasonality.The month was not a factor, July is not any different from January or February when it comes to forecasting the #of Streams (popularity).

project<-read.csv("timeseries-project2.csv",sep = ",",header = TRUE)

Let us use the head function to have a preview of the dataset we are using in this notebook.

head(project)

It is good practice to apply summary to our dataset in order to see the five number summary for each column.

summary(project)
##  Month.of.Week.Starting     month             year         dance.pop    
##  Length:55              Min.   : 1.000   Min.   :16.00   Min.   : 3.00  
##  Class :character       1st Qu.: 3.000   1st Qu.:18.00   1st Qu.: 9.25  
##  Mode  :character       Median : 6.000   Median :19.00   Median :14.00  
##                         Mean   : 6.278   Mean   :18.69   Mean   :14.52  
##                         3rd Qu.: 9.000   3rd Qu.:20.00   3rd Qu.:17.00  
##                         Max.   :12.000   Max.   :21.00   Max.   :49.00  
##                         NA's   :1        NA's   :1       NA's   :1      
##     hip.hop           pop          pop.rap      post.teen.pop        rap       
##  Min.   : 1.00   Min.   :10.0   Min.   : 4.00   Min.   : 2.00   Min.   : 4.00  
##  1st Qu.: 7.25   1st Qu.:19.0   1st Qu.:11.00   1st Qu.: 7.00   1st Qu.:24.00  
##  Median :18.00   Median :23.5   Median :20.00   Median :11.00   Median :30.00  
##  Mean   :19.93   Mean   :25.3   Mean   :23.37   Mean   :12.43   Mean   :34.65  
##  3rd Qu.:27.00   3rd Qu.:31.0   3rd Qu.:28.00   3rd Qu.:16.00   3rd Qu.:46.25  
##  Max.   :68.00   Max.   :83.0   Max.   :66.00   Max.   :32.00   Max.   :85.00  
##  NA's   :1       NA's   :1      NA's   :1       NA's   :1       NA's   :1      
##  southern.hip.hop      trap       dance.pop.streams  hip.hop.streams   
##  Min.   : 1.00    Min.   : 3.00   Length:55          Length:55         
##  1st Qu.: 4.00    1st Qu.:11.25   Class :character   Class :character  
##  Median : 9.00    Median :21.50   Mode  :character   Mode  :character  
##  Mean   :10.08    Mean   :23.20                                        
##  3rd Qu.:15.00    3rd Qu.:29.50                                        
##  Max.   :31.00    Max.   :70.00                                        
##  NA's   :2        NA's   :1                                            
##  pop.streams        pop.rap.streams    post.teen.pop.streams rap.streams       
##  Length:55          Length:55          Length:55             Length:55         
##  Class :character   Class :character   Class :character      Class :character  
##  Mode  :character   Mode  :character   Mode  :character      Mode  :character  
##                                                                                
##                                                                                
##                                                                                
##                                                                                
##  southern.hip.hop.streams trap.streams           suma          
##  Length:55                Length:55          Length:55         
##  Class :character         Class :character   Class :character  
##  Mode  :character         Mode  :character   Mode  :character  
##                                                                
##                                                                
##                                                                
##                                                                
##   popularity       
##  Length:55         
##  Class :character  
##  Mode  :character  
##                    
##                    
##                    
##

Let us now find the data-type for each variable. What is the data type for our response variable (popularity)?

str(project)
## 'data.frame':    55 obs. of  21 variables:
##  $ Month.of.Week.Starting  : chr  "Dec-16" "Jan-17" "Feb-17" "Mar-17" ...
##  $ month                   : int  12 1 2 3 4 5 6 7 8 9 ...
##  $ year                    : int  16 17 17 17 17 17 17 17 17 17 ...
##  $ dance.pop               : int  49 16 14 17 17 17 22 14 19 11 ...
##  $ hip.hop                 : int  45 16 20 34 28 16 27 26 10 4 ...
##  $ pop                     : int  83 29 19 37 23 34 52 25 24 16 ...
##  $ pop.rap                 : int  57 19 54 49 8 24 44 16 9 8 ...
##  $ post.teen.pop           : int  29 6 11 12 9 20 23 8 16 10 ...
##  $ rap                     : int  78 24 50 47 31 24 43 42 30 11 ...
##  $ southern.hip.hop        : int  19 10 31 21 7 6 20 11 11 1 ...
##  $ trap                    : int  43 14 47 26 11 11 37 27 30 6 ...
##  $ dance.pop.streams       : chr  "94,202,784" "26,699,251" "26,745,865" "41,338,505" ...
##  $ hip.hop.streams         : chr  "91,651,796" "18,323,124" "45,263,868" "171,766,202" ...
##  $ pop.streams             : chr  "157,424,840" "59,021,051" "44,012,009" "116,496,818" ...
##  $ pop.rap.streams         : chr  "122,102,977" "23,096,570" "113,747,443" "196,149,071" ...
##  $ post.teen.pop.streams   : chr  "55,141,071" "7,536,277" "18,566,410" "30,210,076" ...
##  $ rap.streams             : chr  "156,221,181" "28,645,609" "109,719,047" "199,988,788" ...
##  $ southern.hip.hop.streams: chr  "35,138,863" "11,823,958" "72,319,920" "36,515,208" ...
##  $ trap.streams            : chr  "86,703,362" "18,026,006" "104,267,668" "47,305,722" ...
##  $ suma                    : chr  "798,586,874" "193,171,846" "534,642,230" "839,770,390" ...
##  $ popularity              : chr  "yes" "no" "yes" "yes" ...

We just noticed that popularity is a factor. Let me delete any missing value and proceed later to make popularity a factor.

mydata1<-na.omit(project)
mydata1$popularity<-as.factor(mydata1$popularity)

Let us confirm that popularity is now a factor.

#str(mydata1)

Let us proceed to eliminate a group of columns(#streams per month) that certainly we are not going to be using for this model.

data2<-mydata1[,-c(12:19)]

Let us now visualize the dataset data2

head(data2)

We have a total of 13 columns at this point but still there are some that better be removed in order to simplify our code from now on. Let us delete Month of Week Starting, month and year.

mydata2<-data2[,-c(1:3)]
head(mydata2)

Let us remove suma which is a calculated field with no business in this model. It was simply used during data pre-processing to understand the variable popularity.

mydata2<-mydata2[,-c(9)]
head(mydata2)

We are now ready for training and testing.

Train and Test Data

The purpose of creating two different datasets from the original one is to improve our ability so as to accurately predict the previously unused or unseen data.

There are a number of ways to proportionally split our data into train and test sets: 50/50, 60/40, 70/30, 80/20, and so forth. The data split that you select should be based on your experience and judgment. For this problem, we will use a 80/20 split, as follows:

set.seed(123)  # random number generator
ind <- sample(2, nrow(mydata2), replace = TRUE, prob = c(0.8, 0.2))
train1 <- mydata2[ind==1, ]  #the training set

test1 <- mydata2[ind==2, ]   # the testing set

Let us see how many columns and rows we have in our training and testing datasets.

dim(train1)
## [1] 42  9
dim(test1)
## [1] 11  9

The number of popular and very popular is a proportion which is very important to know before running our model.

table(train1$popularity)
## 
##  no yes 
##  25  17
table(test1$popularity)
## 
##  no yes 
##   5   6

We have 42 records in the training dataset and 11 in the testing one.

We will run decision trees using the rpart function.

tree.data<-rpart(popularity~.,data = train1)
tree.data$cptable
##          CP nsplit rel error    xerror      xstd
## 1 0.8823529      0 1.0000000 1.0000000 0.1871203
## 2 0.0100000      1 0.1176471 0.2941176 0.1234560
plot(as.party(tree.data))

hip hop is the most important predictor in this classification problem. In a given month, if we had a genre count superior to 19.5, so at least 20 tracks identified as hip hop, that month UMG will have a number of streams above average for any track formed by the top 8 genre presence in spotify.

cp<-min(tree.data$cptable[1,])
prune.tree.data<-prune(tree.data,cp<-cp)
plot(as.party(prune.tree.data))

Let us see how decision trees is able to define between popular and very popular based on the top genres we included in our mode;.

rparty.test<-predict(tree.data,newdata = test1,
                      type ="class")
table(rparty.test,test1$popularity)
##            
## rparty.test no yes
##         no   2   1
##         yes  3   5

Results above indicate that we predicted success in 6 months given the genre types included in our dataset and we were right 5 out 6 times. In addition, results also indicate that in 5 different months we did not predict success when it was a good month in 3 out of those 5 months. It could have been that the success (#streams) in those months was defined by the presence of a genre which is not on the top 8 genre count.

#install.packages("nnet")
library(nnet)
modelANN<-nnet(popularity~.,data=train1,size = 3,decay = 0.0001,maxit = 500)
## # weights:  31
## initial  value 33.293019 
## iter  10 value 17.306162
## iter  20 value 11.975505
## iter  30 value 10.348412
## iter  40 value 10.302007
## iter  50 value 10.299012
## iter  60 value 10.294144
## iter  70 value 10.273478
## iter  80 value 8.801219
## iter  90 value 7.596088
## iter 100 value 7.504282
## iter 110 value 7.503275
## iter 120 value 7.502008
## iter 130 value 7.500584
## iter 140 value 7.498690
## iter 150 value 7.498036
## iter 160 value 7.497457
## iter 170 value 7.497136
## iter 180 value 7.496747
## iter 190 value 7.496474
## iter 200 value 7.496012
## iter 210 value 7.495759
## iter 220 value 7.495652
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## iter 250 value 7.495406
## iter 260 value 7.495282
## iter 270 value 7.495182
## iter 280 value 7.495164
## iter 290 value 7.495141
## iter 300 value 7.495129
## iter 310 value 7.495119
## final  value 7.495118 
## converged
test1$pred_nnet<-predict(modelANN,test1,type="class")
confmat<-data.frame("Prediction"=test1$pred_nnet,"Actual"=test1$popularity)
confmat
#accuracyANN<-data.frame("Accuracy"=nrow(subset(confumatNaive#,Actual==Prediction))/nrow(confumatNaive))
#accuracyANN
#Function for different sizes and different samples in ANN
accuracyANNsize<-function(trials){
acc <- data.frame(i = integer(),j= integer(),Accuracy= integer())
for(i in 450:trials) {
# random sample
smp_size <- floor(0.80 * nrow(mydata2))



## set the seed to make the partition reproducible
set.seed(i)
train_ind <- sample(seq_len(nrow(mydata2)), size = smp_size)



trainC <- mydata2[train_ind, ]
testC <- mydata2[-train_ind, ]
for(j in 2:8){
modelANNC<-nnet(popularity~.,data=trainC,size = j,decay = 0.0001,maxit = 500)
testC$pred_nnet<-predict(modelANNC,testC,type="class")
confmatC<-data.frame(Prediction=testC$pred_nnet,Actual=testC$popularity)
accuracy<-nrow(subset(confmatC,Actual==Prediction))/nrow(confmatC)
Size=j
trial=i
attempt <- data.frame(Trial = trial, Size=Size,Accuracy = accuracy)
acc <- rbind(acc,attempt)
}
}
return(acc)
}
#Running the function for 77 combinations between sizes and random samples
accuracyANN10<-accuracyANNsize(460)
## # weights:  21
## initial  value 29.766704 
## iter  10 value 22.835986
## iter  20 value 21.448511
## iter  30 value 19.325457
## iter  40 value 18.736882
## iter  50 value 18.579766
## iter  60 value 18.388326
## iter  70 value 17.028287
## iter  80 value 16.345658
## iter  90 value 14.039060
## iter 100 value 13.928770
## iter 110 value 13.927112
## iter 120 value 13.923137
## iter 130 value 13.694111
## iter 140 value 13.503682
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## iter 330 value 12.005284
## iter 340 value 12.005227
## iter 350 value 12.005198
## iter 350 value 12.005198
## iter 350 value 12.005198
## final  value 12.005198 
## converged
## # weights:  31
## initial  value 30.239042 
## iter  10 value 22.948118
## iter  20 value 20.414725
## iter  30 value 16.241108
## iter  40 value 15.609594
## iter  50 value 15.324493
## iter  60 value 13.757548
## iter  70 value 11.874142
## iter  80 value 11.657754
## iter  90 value 11.655839
## iter 100 value 11.654799
## iter 110 value 9.824866
## iter 120 value 7.087984
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## iter 200 value 0.190540
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## iter 220 value 0.106126
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## iter 240 value 0.099090
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## iter 420 value 0.091439
## iter 430 value 0.091434
## iter 440 value 0.091429
## iter 450 value 0.091427
## final  value 0.091427 
## converged
## # weights:  41
## initial  value 30.561175 
## iter  10 value 18.299439
## iter  20 value 16.692679
## iter  30 value 15.333374
## iter  40 value 15.311937
## iter  50 value 15.311123
## iter  60 value 15.309935
## iter  70 value 15.308905
## iter  80 value 15.308027
## iter  90 value 15.307369
## iter 100 value 15.303779
## iter 110 value 15.301683
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## iter 270 value 11.140203
## iter 280 value 11.140162
## iter 290 value 11.140136
## iter 300 value 11.140116
## final  value 11.140098 
## converged
## # weights:  51
## initial  value 32.423661 
## iter  10 value 21.956538
## iter  20 value 18.467195
## iter  30 value 16.810210
## iter  40 value 16.772797
## iter  50 value 16.771458
## iter  60 value 16.770881
## iter  70 value 16.454675
## iter  80 value 15.321197
## iter  90 value 15.314509
## iter 100 value 15.311745
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## iter 130 value 12.519923
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## iter 210 value 6.834476
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## iter 270 value 4.104767
## iter 280 value 2.934712
## iter 290 value 2.888024
## iter 300 value 2.885247
## iter 310 value 2.884939
## iter 320 value 2.882872
## iter 330 value 2.876520
## iter 340 value 2.870842
## iter 350 value 2.865438
## iter 360 value 2.703359
## iter 370 value 2.045734
## iter 380 value 2.005648
## iter 390 value 2.001097
## iter 400 value 1.998744
## iter 410 value 1.996116
## iter 420 value 1.975018
## iter 430 value 1.547270
## iter 440 value 0.350128
## iter 450 value 0.258363
## iter 460 value 0.222895
## iter 470 value 0.206111
## iter 480 value 0.203920
## iter 490 value 0.199568
## iter 500 value 0.197894
## final  value 0.197894 
## stopped after 500 iterations
## # weights:  61
## initial  value 48.400364 
## iter  10 value 25.224169
## iter  20 value 20.815752
## iter  30 value 20.188707
## iter  40 value 20.182096
## iter  50 value 20.155850
## iter  60 value 19.134480
## iter  70 value 19.118048
## iter  80 value 19.117412
## iter  90 value 19.116797
## final  value 19.115347 
## converged
## # weights:  71
## initial  value 32.562189 
## iter  10 value 22.007590
## iter  20 value 16.611311
## iter  30 value 14.966873
## iter  40 value 14.583518
## iter  50 value 14.492460
## iter  60 value 14.487076
## iter  70 value 14.486469
## iter  80 value 14.445801
## iter  90 value 12.597174
## iter 100 value 12.491096
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## iter 120 value 12.489791
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## iter 150 value 10.659694
## iter 160 value 8.417772
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## iter 180 value 6.358923
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## iter 200 value 6.352328
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## iter 230 value 6.349599
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## iter 260 value 4.950030
## iter 270 value 3.947520
## iter 280 value 3.908063
## iter 290 value 3.893496
## iter 300 value 3.884682
## iter 310 value 3.882710
## iter 320 value 3.881461
## iter 330 value 3.879569
## iter 340 value 3.869375
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## iter 360 value 2.698787
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## iter 450 value 0.238682
## iter 460 value 0.114946
## iter 470 value 0.111572
## iter 480 value 0.110336
## iter 490 value 0.108742
## iter 500 value 0.107587
## final  value 0.107587 
## stopped after 500 iterations
## # weights:  81
## initial  value 40.290685 
## iter  10 value 20.832963
## iter  20 value 15.881191
## iter  30 value 15.002303
## iter  40 value 14.873721
## iter  50 value 14.791205
## iter  60 value 14.359645
## iter  70 value 14.329475
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## iter  90 value 14.323149
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## iter 280 value 5.482290
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## iter 300 value 4.620765
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## iter 320 value 4.607764
## iter 330 value 4.602653
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## iter 360 value 4.596876
## iter 370 value 3.763128
## iter 380 value 2.163578
## iter 390 value 2.021693
## iter 400 value 2.013716
## iter 410 value 2.007289
## iter 420 value 2.004867
## iter 430 value 2.002848
## iter 440 value 2.000732
## iter 450 value 1.999029
## iter 460 value 1.997673
## iter 470 value 1.995923
## iter 480 value 1.994410
## iter 490 value 1.992824
## iter 500 value 1.992054
## final  value 1.992054 
## stopped after 500 iterations
## # weights:  21
## initial  value 28.833679 
## iter  10 value 27.897906
## iter  20 value 23.678336
## iter  30 value 19.165309
## iter  40 value 18.462011
## iter  50 value 18.459945
## iter  60 value 18.459695
## iter  70 value 18.459639
## iter  80 value 18.459601
## iter  90 value 18.459545
## iter 100 value 18.216401
## iter 110 value 14.053188
## iter 120 value 13.995555
## iter 130 value 13.993871
## iter 140 value 13.993341
## iter 150 value 13.993097
## iter 160 value 13.992799
## iter 170 value 13.736179
## iter 180 value 13.734584
## iter 190 value 13.734235
## iter 200 value 13.262932
## iter 210 value 12.809042
## iter 220 value 12.793581
## iter 230 value 12.793132
## iter 240 value 12.792925
## iter 250 value 12.792901
## iter 260 value 12.792896
## iter 270 value 12.792874
## final  value 12.792871 
## converged
## # weights:  31
## initial  value 31.422125 
## iter  10 value 27.733324
## iter  20 value 21.365742
## iter  30 value 20.306798
## iter  40 value 15.145967
## iter  50 value 15.017297
## iter  60 value 15.014939
## iter  70 value 15.014166
## iter  80 value 14.854743
## iter  90 value 12.874977
## iter 100 value 12.003021
## iter 110 value 11.503739
## iter 120 value 11.358778
## iter 130 value 11.347442
## iter 140 value 11.345390
## iter 150 value 11.343674
## iter 160 value 11.342004
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## iter 220 value 11.340777
## iter 230 value 11.340712
## iter 240 value 11.340586
## iter 250 value 11.340562
## iter 260 value 11.340553
## iter 270 value 11.340542
## final  value 11.340534 
## converged
## # weights:  41
## initial  value 29.432504 
## iter  10 value 25.960580
## iter  20 value 15.751196
## iter  30 value 10.049561
## iter  40 value 9.107500
## iter  50 value 9.081894
## iter  60 value 8.955909
## iter  70 value 8.823760
## iter  80 value 8.706043
## iter  90 value 7.976200
## iter 100 value 7.130413
## iter 110 value 5.998119
## iter 120 value 2.640530
## iter 130 value 1.483424
## iter 140 value 0.438523
## iter 150 value 0.421245
## iter 160 value 0.419835
## iter 170 value 0.418489
## iter 180 value 0.416719
## iter 190 value 0.414895
## iter 200 value 0.414326
## iter 210 value 0.413280
## iter 220 value 0.412487
## iter 230 value 0.411682
## iter 240 value 0.411219
## iter 250 value 0.410569
## iter 260 value 0.410330
## iter 270 value 0.410017
## iter 280 value 0.401470
## iter 290 value 0.359749
## iter 300 value 0.314769
## iter 310 value 0.285406
## iter 320 value 0.251350
## iter 330 value 0.221493
## iter 340 value 0.195845
## iter 350 value 0.163741
## iter 360 value 0.157126
## iter 370 value 0.147937
## iter 380 value 0.128921
## iter 390 value 0.116029
## iter 400 value 0.109524
## iter 410 value 0.105898
## iter 420 value 0.102464
## iter 430 value 0.099241
## iter 440 value 0.098776
## iter 450 value 0.098240
## iter 460 value 0.098004
## iter 470 value 0.097592
## iter 480 value 0.097416
## iter 490 value 0.097270
## iter 500 value 0.097151
## final  value 0.097151 
## stopped after 500 iterations
## # weights:  51
## initial  value 28.075804 
## iter  10 value 17.152285
## iter  20 value 12.836881
## iter  30 value 12.420598
## iter  40 value 12.317971
## iter  50 value 12.311075
## iter  60 value 12.310206
## iter  70 value 12.309894
## iter  80 value 12.309702
## iter  90 value 12.309562
## iter 100 value 12.309492
## iter 110 value 12.309380
## iter 120 value 12.309333
## iter 130 value 12.309284
## iter 140 value 12.309273
## iter 150 value 12.309258
## iter 160 value 12.309237
## iter 170 value 12.309228
## iter 180 value 12.309221
## final  value 12.309216 
## converged
## # weights:  61
## initial  value 30.365096 
## iter  10 value 21.987285
## iter  20 value 15.176103
## iter  30 value 13.769944
## iter  40 value 13.268028
## iter  50 value 13.221558
## iter  60 value 13.214679
## iter  70 value 13.212274
## iter  80 value 13.207901
## iter  90 value 12.142710
## iter 100 value 10.838815
## iter 110 value 10.560968
## iter 120 value 10.425649
## iter 130 value 10.422799
## iter 140 value 10.418595
## iter 150 value 10.413066
## iter 160 value 8.925110
## iter 170 value 7.961435
## iter 180 value 6.377701
## iter 190 value 3.673528
## iter 200 value 3.306639
## iter 210 value 3.167076
## iter 220 value 3.163494
## iter 230 value 3.156341
## iter 240 value 3.155222
## iter 250 value 3.153702
## iter 260 value 3.151666
## iter 270 value 3.121342
## iter 280 value 3.010867
## iter 290 value 3.007793
## iter 300 value 3.006498
## iter 310 value 3.005766
## iter 320 value 3.004835
## iter 330 value 3.004414
## iter 340 value 3.003656
## iter 350 value 3.002414
## iter 360 value 3.002079
## iter 370 value 3.001931
## iter 380 value 3.001737
## iter 390 value 3.001651
## iter 400 value 3.001610
## iter 410 value 3.001592
## iter 420 value 3.001552
## iter 430 value 3.001525
## iter 440 value 3.001504
## iter 450 value 3.001034
## iter 460 value 2.957094
## iter 470 value 2.401263
## iter 480 value 2.380235
## iter 490 value 2.379009
## iter 500 value 2.294910
## final  value 2.294910 
## stopped after 500 iterations
## # weights:  71
## initial  value 40.274614 
## iter  10 value 24.255906
## iter  20 value 15.095723
## iter  30 value 14.341825
## iter  40 value 12.661157
## iter  50 value 11.393164
## iter  60 value 10.643822
## iter  70 value 10.215254
## iter  80 value 9.686500
## iter  90 value 8.712344
## iter 100 value 8.655806
## iter 110 value 8.652764
## iter 120 value 8.649095
## iter 130 value 8.647854
## iter 140 value 8.646187
## iter 150 value 8.644333
## iter 160 value 8.643352
## iter 170 value 8.119668
## iter 180 value 6.410424
## iter 190 value 5.443316
## iter 200 value 5.398560
## iter 210 value 5.387609
## iter 220 value 5.384379
## iter 230 value 5.379451
## iter 240 value 5.377166
## iter 250 value 5.371118
## iter 260 value 5.368605
## iter 270 value 5.366388
## iter 280 value 5.364247
## iter 290 value 5.362635
## iter 300 value 5.361690
## iter 310 value 5.360694
## iter 320 value 5.338908
## iter 330 value 4.578598
## iter 340 value 3.513517
## iter 350 value 3.484347
## iter 360 value 3.478105
## iter 370 value 3.475731
## iter 380 value 3.474864
## iter 390 value 3.474209
## iter 400 value 3.473264
## iter 410 value 3.472222
## iter 420 value 3.471778
## iter 430 value 3.471322
## iter 440 value 3.471066
## iter 450 value 3.470929
## iter 460 value 3.470772
## iter 470 value 3.470625
## iter 480 value 3.468369
## iter 490 value 3.181030
## iter 500 value 2.887267
## final  value 2.887267 
## stopped after 500 iterations
## # weights:  81
## initial  value 30.848739 
## iter  10 value 19.634303
## iter  20 value 12.509775
## iter  30 value 11.515240
## iter  40 value 8.124612
## iter  50 value 6.744691
## iter  60 value 6.505331
## iter  70 value 6.162088
## iter  80 value 6.157870
## iter  90 value 6.151668
## iter 100 value 6.147506
## iter 110 value 5.563339
## iter 120 value 5.352732
## iter 130 value 5.346549
## iter 140 value 5.339669
## iter 150 value 5.326965
## iter 160 value 4.828700
## iter 170 value 4.290197
## iter 180 value 3.694904
## iter 190 value 3.691283
## iter 200 value 3.689390
## iter 210 value 3.685593
## iter 220 value 3.683124
## iter 230 value 3.682034
## iter 240 value 3.681208
## iter 250 value 3.680510
## iter 260 value 3.676251
## iter 270 value 3.405700
## iter 280 value 3.192351
## iter 290 value 0.416910
## iter 300 value 0.182203
## iter 310 value 0.134854
## iter 320 value 0.132348
## iter 330 value 0.130870
## iter 340 value 0.127951
## iter 350 value 0.126283
## iter 360 value 0.124873
## iter 370 value 0.123103
## iter 380 value 0.121171
## iter 390 value 0.118506
## iter 400 value 0.114900
## iter 410 value 0.110079
## iter 420 value 0.105958
## iter 430 value 0.102302
## iter 440 value 0.098881
## iter 450 value 0.093797
## iter 460 value 0.090616
## iter 470 value 0.088688
## iter 480 value 0.083112
## iter 490 value 0.078888
## iter 500 value 0.076248
## final  value 0.076248 
## stopped after 500 iterations
## # weights:  21
## initial  value 32.933643 
## iter  10 value 28.682441
## final  value 28.682388 
## converged
## # weights:  31
## initial  value 28.305947 
## iter  10 value 18.373190
## iter  20 value 16.195336
## iter  30 value 15.400914
## iter  40 value 14.397649
## iter  50 value 14.225681
## iter  60 value 14.223037
## iter  70 value 14.222255
## iter  80 value 14.222074
## iter  90 value 14.221965
## iter 100 value 14.221903
## iter 110 value 14.221866
## iter 120 value 14.221846
## iter 130 value 14.221823
## iter 140 value 14.221761
## iter 150 value 14.208776
## iter 160 value 11.753650
## iter 170 value 10.524973
## iter 180 value 10.460794
## iter 190 value 10.456792
## iter 200 value 10.456010
## iter 210 value 10.454554
## iter 220 value 10.288041
## iter 230 value 10.286825
## iter 240 value 10.286124
## iter 250 value 10.285369
## iter 260 value 10.285030
## iter 270 value 10.284749
## iter 280 value 10.284495
## iter 290 value 10.284382
## iter 300 value 10.284252
## iter 310 value 10.284120
## iter 320 value 10.283779
## iter 330 value 9.951921
## iter 340 value 9.712475
## iter 350 value 9.554953
## iter 360 value 9.552411
## iter 370 value 9.551909
## iter 380 value 9.551575
## iter 390 value 9.289655
## iter 400 value 9.235307
## iter 410 value 9.234271
## iter 420 value 9.234024
## iter 430 value 9.233446
## iter 440 value 9.232745
## iter 450 value 9.232431
## iter 460 value 9.232067
## iter 470 value 8.992251
## iter 480 value 8.295053
## iter 490 value 8.280074
## iter 500 value 8.279428
## final  value 8.279428 
## stopped after 500 iterations
## # weights:  41
## initial  value 32.928166 
## iter  10 value 24.046117
## iter  20 value 15.155851
## iter  30 value 10.712963
## iter  40 value 9.713035
## iter  50 value 9.525363
## iter  60 value 9.521098
## iter  70 value 9.517982
## iter  80 value 9.516833
## iter  90 value 9.511859
## iter 100 value 9.507970
## iter 110 value 9.193262
## iter 120 value 8.956614
## iter 130 value 8.212860
## iter 140 value 8.170181
## iter 150 value 8.166518
## iter 160 value 8.166133
## iter 170 value 8.165989
## iter 180 value 8.165915
## iter 190 value 8.165750
## iter 200 value 8.165715
## iter 210 value 8.165607
## iter 220 value 8.165574
## iter 230 value 8.165554
## iter 240 value 8.165544
## iter 250 value 8.165520
## iter 260 value 8.165509
## iter 270 value 8.165489
## iter 280 value 8.165368
## iter 290 value 7.987537
## iter 300 value 6.792942
## iter 310 value 4.743171
## iter 320 value 4.359544
## iter 330 value 3.617325
## iter 340 value 2.920276
## iter 350 value 2.877193
## iter 360 value 2.860563
## iter 370 value 2.856548
## iter 380 value 2.849917
## iter 390 value 2.840698
## iter 400 value 2.837391
## iter 410 value 2.835355
## iter 420 value 2.831841
## iter 430 value 2.829082
## iter 440 value 2.826185
## iter 450 value 2.822463
## iter 460 value 2.820447
## iter 470 value 2.813405
## iter 480 value 2.688060
## iter 490 value 2.524234
## iter 500 value 2.387152
## final  value 2.387152 
## stopped after 500 iterations
## # weights:  51
## initial  value 30.586269 
## iter  10 value 22.291875
## iter  20 value 17.738453
## iter  30 value 16.868971
## iter  40 value 16.626993
## iter  50 value 15.943740
## iter  60 value 15.933682
## iter  70 value 15.928607
## iter  80 value 15.925140
## iter  90 value 15.919375
## iter 100 value 15.913247
## iter 110 value 15.911434
## iter 120 value 15.910547
## iter 130 value 15.908963
## iter 140 value 15.908075
## iter 150 value 15.907978
## iter 160 value 15.907863
## iter 170 value 15.907766
## iter 180 value 15.896260
## iter 190 value 13.951301
## iter 200 value 12.549897
## iter 210 value 12.486139
## iter 220 value 12.244306
## iter 230 value 10.855860
## iter 240 value 10.851198
## iter 250 value 10.850147
## iter 260 value 10.848924
## iter 270 value 10.847068
## iter 280 value 10.845158
## iter 290 value 10.844682
## iter 300 value 10.844385
## iter 310 value 10.844231
## iter 320 value 10.839198
## iter 330 value 9.605350
## iter 340 value 8.085648
## iter 350 value 7.888913
## iter 360 value 7.449946
## iter 370 value 7.288103
## iter 380 value 7.284474
## iter 390 value 7.282232
## iter 400 value 6.777660
## iter 410 value 6.211130
## iter 420 value 3.863629
## iter 430 value 2.390634
## iter 440 value 2.369542
## iter 450 value 2.363492
## iter 460 value 2.361711
## iter 470 value 2.360805
## iter 480 value 2.360278
## iter 490 value 2.359321
## iter 500 value 2.358981
## final  value 2.358981 
## stopped after 500 iterations
## # weights:  61
## initial  value 28.513840 
## iter  10 value 18.195770
## iter  20 value 16.242295
## iter  30 value 15.939526
## iter  40 value 15.938037
## iter  50 value 15.937370
## iter  60 value 15.937014
## iter  70 value 15.933776
## iter  80 value 15.415017
## iter  90 value 15.378912
## iter 100 value 15.378472
## iter 110 value 15.378296
## iter 120 value 15.378154
## iter 130 value 15.377737
## iter 140 value 15.377657
## final  value 15.377567 
## converged
## # weights:  71
## initial  value 32.874814 
## iter  10 value 25.234388
## iter  20 value 16.937616
## iter  30 value 16.538656
## iter  40 value 15.054594
## iter  50 value 14.781067
## iter  60 value 14.614309
## iter  70 value 14.592088
## iter  80 value 14.590819
## iter  90 value 14.589965
## iter 100 value 14.589405
## iter 110 value 14.589084
## iter 120 value 14.587348
## iter 130 value 14.586793
## iter 140 value 14.586590
## iter 150 value 14.586545
## final  value 14.586543 
## converged
## # weights:  81
## initial  value 29.767434 
## iter  10 value 18.869336
## iter  20 value 13.888423
## iter  30 value 10.614149
## iter  40 value 10.170257
## iter  50 value 8.957260
## iter  60 value 8.749997
## iter  70 value 8.742715
## iter  80 value 8.740423
## iter  90 value 8.739180
## iter 100 value 8.609024
## iter 110 value 7.104298
## iter 120 value 7.101436
## iter 130 value 7.099558
## iter 140 value 7.098743
## iter 150 value 7.097903
## iter 160 value 6.806387
## iter 170 value 4.146461
## iter 180 value 1.916428
## iter 190 value 1.658357
## iter 200 value 1.612240
## iter 210 value 1.588942
## iter 220 value 1.572982
## iter 230 value 1.562174
## iter 240 value 1.547590
## iter 250 value 1.543001
## iter 260 value 1.538171
## iter 270 value 1.532307
## iter 280 value 1.477826
## iter 290 value 0.697709
## iter 300 value 0.222001
## iter 310 value 0.175927
## iter 320 value 0.159149
## iter 330 value 0.149301
## iter 340 value 0.140949
## iter 350 value 0.133074
## iter 360 value 0.128183
## iter 370 value 0.126421
## iter 380 value 0.124196
## iter 390 value 0.121937
## iter 400 value 0.118491
## iter 410 value 0.117558
## iter 420 value 0.116273
## iter 430 value 0.115133
## iter 440 value 0.113787
## iter 450 value 0.113003
## iter 460 value 0.112395
## iter 470 value 0.112115
## iter 480 value 0.111958
## iter 490 value 0.111786
## iter 500 value 0.111271
## final  value 0.111271 
## stopped after 500 iterations
## # weights:  21
## initial  value 30.887865 
## iter  10 value 21.814938
## iter  20 value 15.514662
## iter  30 value 11.626567
## iter  40 value 10.629190
## iter  50 value 10.534897
## iter  60 value 10.293725
## iter  70 value 9.651555
## iter  80 value 9.602128
## iter  90 value 9.595896
## iter 100 value 9.468544
## iter 110 value 8.567288
## iter 120 value 8.320252
## iter 130 value 7.290130
## iter 140 value 7.079271
## iter 150 value 7.077756
## iter 160 value 7.076527
## iter 170 value 7.075732
## iter 180 value 7.075553
## iter 190 value 7.038387
## iter 200 value 6.444105
## iter 210 value 3.224647
## iter 220 value 0.971408
## iter 230 value 0.119909
## iter 240 value 0.116743
## iter 250 value 0.116077
## iter 260 value 0.115870
## iter 270 value 0.115307
## iter 280 value 0.114600
## iter 290 value 0.114378
## iter 300 value 0.114315
## iter 310 value 0.114184
## iter 320 value 0.113849
## iter 330 value 0.113775
## iter 340 value 0.113707
## iter 350 value 0.113673
## iter 360 value 0.113647
## iter 370 value 0.113627
## final  value 0.113622 
## converged
## # weights:  31
## initial  value 29.048940 
## iter  10 value 23.538610
## iter  20 value 22.882904
## iter  30 value 22.880568
## iter  40 value 22.880092
## iter  50 value 22.859386
## iter  60 value 20.634351
## iter  70 value 14.201181
## iter  80 value 13.146615
## iter  90 value 12.805944
## iter 100 value 12.142389
## iter 110 value 10.944857
## iter 120 value 10.858544
## iter 130 value 10.853725
## iter 140 value 10.842347
## iter 150 value 10.634706
## iter 160 value 10.599255
## iter 170 value 10.594337
## iter 180 value 10.590297
## iter 190 value 10.542218
## iter 200 value 10.278885
## iter 210 value 10.259923
## iter 220 value 10.252475
## iter 230 value 9.904269
## iter 240 value 8.701437
## iter 250 value 8.449388
## iter 260 value 8.400388
## iter 270 value 8.312965
## iter 280 value 5.737682
## iter 290 value 0.571210
## iter 300 value 0.180501
## iter 310 value 0.146620
## iter 320 value 0.143447
## iter 330 value 0.138668
## iter 340 value 0.135791
## iter 350 value 0.133450
## iter 360 value 0.128330
## iter 370 value 0.126359
## iter 380 value 0.117469
## iter 390 value 0.110428
## iter 400 value 0.107301
## iter 410 value 0.106441
## iter 420 value 0.105314
## iter 430 value 0.104498
## iter 440 value 0.103430
## iter 450 value 0.102890
## iter 460 value 0.102313
## iter 470 value 0.102140
## iter 480 value 0.101703
## iter 490 value 0.101517
## iter 500 value 0.101394
## final  value 0.101394 
## stopped after 500 iterations
## # weights:  41
## initial  value 30.534710 
## iter  10 value 28.346660
## iter  20 value 28.346347
## iter  30 value 28.332906
## iter  40 value 27.844532
## iter  50 value 27.831887
## iter  60 value 27.829127
## iter  70 value 27.827866
## iter  80 value 27.826023
## iter  90 value 27.689736
## iter 100 value 20.495637
## iter 110 value 19.697538
## iter 120 value 19.693297
## iter 130 value 19.691472
## iter 140 value 19.690277
## iter 150 value 19.678947
## iter 160 value 16.317021
## iter 170 value 11.575562
## iter 180 value 9.769149
## iter 190 value 9.073921
## iter 200 value 9.052632
## iter 210 value 9.048447
## iter 220 value 8.030663
## iter 230 value 6.181884
## iter 240 value 5.759754
## iter 250 value 5.753651
## iter 260 value 5.719468
## iter 270 value 5.662657
## iter 280 value 5.661653
## iter 290 value 5.660304
## iter 300 value 5.639923
## iter 310 value 5.410681
## iter 320 value 5.324636
## iter 330 value 5.322421
## iter 340 value 5.321857
## iter 350 value 5.321440
## iter 360 value 5.321091
## iter 370 value 5.320717
## iter 380 value 5.320310
## iter 390 value 5.320208
## iter 400 value 5.320130
## iter 410 value 5.320104
## iter 420 value 5.320073
## iter 430 value 5.320030
## iter 440 value 5.319992
## iter 450 value 3.602099
## iter 460 value 2.642274
## iter 470 value 2.597734
## iter 480 value 2.355784
## iter 490 value 2.347166
## iter 500 value 2.344811
## final  value 2.344811 
## stopped after 500 iterations
## # weights:  51
## initial  value 36.635476 
## iter  10 value 28.349023
## iter  20 value 23.749153
## iter  30 value 21.286081
## iter  40 value 19.362721
## iter  50 value 18.181851
## iter  60 value 18.031990
## iter  70 value 16.112905
## iter  80 value 15.575670
## iter  90 value 15.568805
## iter 100 value 15.566896
## iter 110 value 15.566158
## iter 120 value 15.565036
## iter 130 value 15.563813
## iter 140 value 15.563257
## iter 150 value 15.563079
## iter 160 value 13.578764
## iter 170 value 11.456574
## iter 180 value 11.226828
## iter 190 value 11.143234
## iter 200 value 11.139565
## iter 210 value 11.138775
## iter 220 value 11.115670
## iter 230 value 11.021075
## iter 240 value 10.577887
## iter 250 value 8.034100
## iter 260 value 3.935846
## iter 270 value 3.197524
## iter 280 value 2.901240
## iter 290 value 2.888086
## iter 300 value 2.886086
## iter 310 value 2.884171
## iter 320 value 2.878369
## iter 330 value 2.873556
## iter 340 value 1.067215
## iter 350 value 0.406250
## iter 360 value 0.197698
## iter 370 value 0.137893
## iter 380 value 0.126106
## iter 390 value 0.119953
## iter 400 value 0.111129
## iter 410 value 0.102851
## iter 420 value 0.095108
## iter 430 value 0.093879
## iter 440 value 0.092864
## iter 450 value 0.092415
## iter 460 value 0.091956
## iter 470 value 0.091428
## iter 480 value 0.091116
## iter 490 value 0.090720
## iter 500 value 0.090522
## final  value 0.090522 
## stopped after 500 iterations
## # weights:  61
## initial  value 29.295443 
## iter  10 value 26.400863
## iter  20 value 18.584781
## iter  30 value 17.996034
## iter  40 value 15.478654
## iter  50 value 14.420547
## iter  60 value 13.541824
## iter  70 value 12.185459
## iter  80 value 11.688674
## iter  90 value 11.506711
## iter 100 value 11.409086
## iter 110 value 11.406460
## iter 120 value 11.404807
## iter 130 value 11.398063
## iter 140 value 9.504510
## iter 150 value 8.741899
## iter 160 value 8.717989
## iter 170 value 8.716423
## iter 180 value 8.714805
## iter 190 value 8.714128
## iter 200 value 8.711912
## iter 210 value 8.710971
## iter 220 value 8.710441
## iter 230 value 8.710108
## iter 240 value 8.707693
## iter 250 value 8.389866
## iter 260 value 4.525698
## iter 270 value 4.299565
## iter 280 value 4.261613
## iter 290 value 4.259948
## iter 300 value 4.259150
## iter 310 value 4.258561
## iter 320 value 4.257935
## iter 330 value 4.257719
## iter 340 value 4.257584
## iter 350 value 4.257470
## iter 360 value 4.257448
## iter 370 value 3.949836
## iter 380 value 0.461478
## iter 390 value 0.165735
## iter 400 value 0.127594
## iter 410 value 0.114485
## iter 420 value 0.106853
## iter 430 value 0.103775
## iter 440 value 0.101409
## iter 450 value 0.099913
## iter 460 value 0.096908
## iter 470 value 0.093696
## iter 480 value 0.087975
## iter 490 value 0.083288
## iter 500 value 0.078695
## final  value 0.078695 
## stopped after 500 iterations
## # weights:  71
## initial  value 32.790465 
## iter  10 value 26.262300
## iter  20 value 24.881948
## iter  30 value 17.277388
## iter  40 value 14.936631
## iter  50 value 14.920715
## iter  60 value 14.912983
## iter  70 value 14.909784
## iter  80 value 14.906320
## iter  90 value 14.904742
## iter 100 value 14.901905
## iter 110 value 14.665756
## iter 120 value 14.372314
## iter 130 value 14.325968
## iter 140 value 14.324568
## iter 150 value 14.323847
## iter 160 value 14.323115
## iter 170 value 14.322202
## iter 180 value 14.320420
## iter 190 value 8.597088
## iter 200 value 5.255054
## iter 210 value 3.136075
## iter 220 value 2.413501
## iter 230 value 2.342928
## iter 240 value 2.338179
## iter 250 value 2.336813
## iter 260 value 2.334604
## iter 270 value 2.332103
## iter 280 value 2.330683
## iter 290 value 2.330278
## iter 300 value 2.210101
## iter 310 value 2.010358
## iter 320 value 1.998563
## iter 330 value 1.996594
## iter 340 value 1.995090
## iter 350 value 1.991533
## iter 360 value 1.989380
## iter 370 value 1.987782
## iter 380 value 1.985825
## iter 390 value 1.984839
## iter 400 value 1.984202
## iter 410 value 1.983807
## iter 420 value 1.983664
## iter 430 value 1.983428
## iter 440 value 1.983150
## iter 450 value 1.983112
## iter 460 value 1.983069
## iter 470 value 1.982389
## iter 480 value 1.982121
## iter 490 value 1.981988
## iter 500 value 1.981841
## final  value 1.981841 
## stopped after 500 iterations
## # weights:  81
## initial  value 33.329619 
## iter  10 value 22.612619
## iter  20 value 18.584998
## iter  30 value 13.845870
## iter  40 value 12.494568
## iter  50 value 12.087503
## iter  60 value 11.985281
## iter  70 value 11.072058
## iter  80 value 10.593306
## iter  90 value 10.550701
## iter 100 value 10.537345
## iter 110 value 10.534520
## iter 120 value 10.531898
## iter 130 value 10.531352
## iter 140 value 10.530723
## iter 150 value 10.530165
## iter 160 value 10.528354
## iter 170 value 7.623154
## iter 180 value 1.765017
## iter 190 value 0.303844
## iter 200 value 0.235846
## iter 210 value 0.178320
## iter 220 value 0.155080
## iter 230 value 0.144410
## iter 240 value 0.139783
## iter 250 value 0.135586
## iter 260 value 0.130558
## iter 270 value 0.126342
## iter 280 value 0.115989
## iter 290 value 0.111431
## iter 300 value 0.103785
## iter 310 value 0.095947
## iter 320 value 0.093038
## iter 330 value 0.091082
## iter 340 value 0.089568
## iter 350 value 0.088719
## iter 360 value 0.087911
## iter 370 value 0.087562
## iter 380 value 0.087102
## iter 390 value 0.086536
## iter 400 value 0.086113
## iter 410 value 0.083737
## iter 420 value 0.081838
## iter 430 value 0.080113
## iter 440 value 0.078826
## iter 450 value 0.076655
## iter 460 value 0.076150
## iter 470 value 0.075908
## iter 480 value 0.075723
## iter 490 value 0.075545
## iter 500 value 0.075368
## final  value 0.075368 
## stopped after 500 iterations
## # weights:  21
## initial  value 29.418564 
## iter  10 value 20.884510
## iter  20 value 14.920476
## iter  30 value 14.098860
## iter  40 value 13.669281
## iter  50 value 13.185270
## iter  60 value 13.173950
## iter  70 value 13.168520
## iter  80 value 13.161646
## iter  90 value 12.276214
## iter 100 value 12.261741
## iter 110 value 12.259675
## iter 120 value 12.258690
## iter 130 value 12.254650
## iter 140 value 12.253691
## iter 150 value 12.252774
## iter 160 value 12.251527
## iter 170 value 12.249276
## iter 180 value 9.149371
## iter 190 value 8.517924
## iter 200 value 8.497549
## iter 210 value 8.494723
## iter 220 value 8.494317
## iter 230 value 8.494083
## iter 240 value 8.494023
## iter 250 value 8.493774
## iter 260 value 8.487717
## iter 270 value 8.287114
## iter 280 value 8.188263
## iter 290 value 8.184216
## iter 300 value 8.183442
## iter 310 value 8.182796
## iter 320 value 8.182429
## iter 330 value 8.182037
## iter 340 value 8.181536
## iter 350 value 8.181292
## iter 360 value 8.181256
## iter 370 value 8.181212
## iter 380 value 8.181188
## iter 390 value 8.181181
## final  value 8.181179 
## converged
## # weights:  31
## initial  value 29.513165 
## iter  10 value 20.257216
## iter  20 value 17.969107
## iter  30 value 16.344334
## iter  40 value 16.323811
## iter  50 value 16.323514
## iter  60 value 16.323347
## iter  70 value 16.323090
## iter  80 value 16.322820
## final  value 16.322817 
## converged
## # weights:  41
## initial  value 30.063505 
## iter  10 value 16.992614
## iter  20 value 14.818269
## iter  30 value 14.382090
## iter  40 value 13.688983
## iter  50 value 13.641227
## iter  60 value 13.638423
## iter  70 value 13.637776
## iter  80 value 13.637615
## iter  90 value 13.637231
## iter 100 value 13.636802
## iter 110 value 13.635502
## iter 120 value 10.866281
## iter 130 value 10.131943
## iter 140 value 10.123059
## iter 150 value 9.607766
## iter 160 value 9.603471
## iter 170 value 9.599839
## iter 180 value 9.409938
## iter 190 value 9.407101
## iter 200 value 9.406321
## iter 210 value 9.194662
## iter 220 value 9.192886
## iter 230 value 9.192304
## iter 240 value 9.191147
## iter 250 value 9.190301
## iter 260 value 9.190067
## iter 270 value 9.115543
## iter 280 value 7.960541
## iter 290 value 5.667340
## iter 300 value 5.621233
## iter 310 value 5.617470
## iter 320 value 5.616707
## iter 330 value 5.616118
## iter 340 value 5.614831
## iter 350 value 5.613730
## iter 360 value 5.613016
## iter 370 value 5.612537
## iter 380 value 5.612096
## iter 390 value 5.611656
## iter 400 value 5.611457
## iter 410 value 5.610078
## iter 420 value 4.925787
## iter 430 value 4.752052
## iter 440 value 4.749650
## iter 450 value 4.748558
## iter 460 value 4.748165
## iter 470 value 4.747814
## iter 480 value 4.747504
## iter 490 value 4.747295
## iter 500 value 4.747099
## final  value 4.747099 
## stopped after 500 iterations
## # weights:  51
## initial  value 36.451269 
## iter  10 value 23.517034
## iter  20 value 22.892077
## iter  30 value 22.880319
## iter  40 value 22.878511
## iter  50 value 22.151452
## iter  60 value 21.683146
## iter  70 value 18.188964
## iter  80 value 10.872334
## iter  90 value 10.136221
## iter 100 value 8.040317
## iter 110 value 6.646621
## iter 120 value 6.092678
## iter 130 value 5.852759
## iter 140 value 4.016932
## iter 150 value 3.240581
## iter 160 value 3.028019
## iter 170 value 2.475779
## iter 180 value 2.074939
## iter 190 value 0.399174
## iter 200 value 0.156546
## iter 210 value 0.136780
## iter 220 value 0.131457
## iter 230 value 0.127717
## iter 240 value 0.125815
## iter 250 value 0.120119
## iter 260 value 0.116929
## iter 270 value 0.115999
## iter 280 value 0.115341
## iter 290 value 0.115030
## iter 300 value 0.114614
## iter 310 value 0.114035
## iter 320 value 0.113832
## iter 330 value 0.113472
## iter 340 value 0.113121
## iter 350 value 0.112818
## iter 360 value 0.112573
## iter 370 value 0.112487
## iter 380 value 0.112439
## iter 390 value 0.112413
## iter 400 value 0.112403
## iter 410 value 0.112385
## iter 420 value 0.112359
## iter 430 value 0.112266
## iter 440 value 0.111301
## iter 450 value 0.108307
## iter 460 value 0.107145
## iter 470 value 0.105570
## iter 480 value 0.103492
## iter 490 value 0.100620
## iter 500 value 0.099509
## final  value 0.099509 
## stopped after 500 iterations
## # weights:  61
## initial  value 38.415144 
## iter  10 value 24.204124
## iter  20 value 19.259627
## iter  30 value 15.663026
## iter  40 value 14.332165
## iter  50 value 14.328580
## iter  60 value 14.326727
## iter  70 value 14.324726
## iter  80 value 14.322565
## iter  90 value 14.321955
## iter 100 value 14.317138
## iter 110 value 12.161344
## iter 120 value 11.346743
## iter 130 value 11.298554
## iter 140 value 9.265891
## iter 150 value 9.234503
## iter 160 value 9.233575
## iter 170 value 9.232499
## iter 180 value 9.232025
## iter 190 value 9.063530
## iter 200 value 8.216820
## iter 210 value 6.799597
## iter 220 value 5.355047
## iter 230 value 5.325269
## iter 240 value 5.324176
## iter 250 value 5.323867
## iter 260 value 5.323299
## iter 270 value 5.322737
## iter 280 value 5.322312
## iter 290 value 5.322147
## iter 300 value 4.996643
## iter 310 value 3.110361
## iter 320 value 2.904080
## iter 330 value 2.886158
## iter 340 value 2.885256
## iter 350 value 2.884364
## iter 360 value 2.883428
## iter 370 value 2.881846
## iter 380 value 2.881247
## iter 390 value 2.880840
## iter 400 value 2.738406
## iter 410 value 2.052010
## iter 420 value 2.048112
## iter 430 value 2.043615
## iter 440 value 1.740972
## iter 450 value 0.517978
## iter 460 value 0.335748
## iter 470 value 0.308848
## iter 480 value 0.300465
## iter 490 value 0.276471
## iter 500 value 0.266448
## final  value 0.266448 
## stopped after 500 iterations
## # weights:  71
## initial  value 33.435936 
## iter  10 value 20.469682
## iter  20 value 20.460174
## iter  30 value 20.436753
## iter  40 value 18.986848
## iter  50 value 15.267280
## iter  60 value 14.961485
## iter  70 value 14.047186
## iter  80 value 14.027442
## iter  90 value 14.025208
## iter 100 value 14.024321
## iter 110 value 14.022254
## iter 120 value 14.020868
## iter 130 value 12.648714
## iter 140 value 11.434204
## iter 150 value 11.428794
## iter 160 value 11.428520
## iter 170 value 11.428149
## iter 180 value 11.428030
## iter 190 value 11.427703
## iter 200 value 11.427482
## iter 210 value 11.427356
## iter 220 value 11.427260
## iter 230 value 11.427215
## final  value 11.427214 
## converged
## # weights:  81
## initial  value 40.810561 
## iter  10 value 23.317103
## iter  20 value 15.993346
## iter  30 value 12.183086
## iter  40 value 10.007462
## iter  50 value 7.509317
## iter  60 value 7.370745
## iter  70 value 7.364027
## iter  80 value 7.362912
## iter  90 value 7.362223
## iter 100 value 7.360142
## iter 110 value 6.666949
## iter 120 value 6.440200
## iter 130 value 6.429778
## iter 140 value 6.428340
## iter 150 value 6.428002
## iter 160 value 6.427743
## iter 170 value 6.426998
## iter 180 value 6.426467
## iter 190 value 6.425936
## iter 200 value 6.425422
## iter 210 value 6.425230
## iter 220 value 6.425150
## iter 230 value 6.425090
## iter 240 value 6.425067
## iter 250 value 6.425055
## final  value 6.425055 
## converged
## # weights:  21
## initial  value 33.204163 
## final  value 28.682546 
## converged
## # weights:  31
## initial  value 30.371155 
## iter  10 value 27.078810
## iter  20 value 27.047312
## iter  30 value 27.047075
## iter  40 value 22.723941
## iter  50 value 22.650096
## iter  60 value 18.967786
## iter  70 value 17.200806
## iter  80 value 17.198688
## iter  90 value 17.197904
## iter 100 value 17.197706
## iter 110 value 17.196926
## iter 120 value 17.196661
## iter 130 value 17.196405
## iter 140 value 17.196159
## iter 150 value 17.044842
## iter 160 value 15.291885
## iter 170 value 15.181114
## iter 180 value 14.441295
## iter 190 value 14.427852
## iter 200 value 14.426224
## iter 210 value 14.425575
## iter 220 value 14.425041
## iter 230 value 14.424354
## iter 240 value 14.424205
## iter 250 value 14.424186
## iter 260 value 14.424172
## iter 270 value 14.423825
## iter 280 value 13.316188
## iter 290 value 8.450221
## iter 300 value 6.126229
## iter 310 value 5.496234
## iter 320 value 5.047900
## iter 330 value 4.147216
## iter 340 value 3.895562
## iter 350 value 3.284776
## iter 360 value 2.908917
## iter 370 value 2.611966
## iter 380 value 0.591977
## iter 390 value 0.142533
## iter 400 value 0.133111
## iter 410 value 0.127927
## iter 420 value 0.121516
## iter 430 value 0.114437
## iter 440 value 0.110759
## iter 450 value 0.107746
## iter 460 value 0.106936
## iter 470 value 0.104148
## iter 480 value 0.103823
## iter 490 value 0.102307
## iter 500 value 0.100634
## final  value 0.100634 
## stopped after 500 iterations
## # weights:  41
## initial  value 31.798399 
## iter  10 value 28.682692
## iter  20 value 24.590840
## iter  30 value 22.809666
## iter  40 value 22.808163
## iter  50 value 22.807564
## iter  60 value 22.772149
## iter  70 value 19.685276
## iter  80 value 17.898172
## iter  90 value 17.789577
## iter 100 value 17.787182
## iter 110 value 16.426762
## iter 120 value 16.333178
## iter 130 value 15.520466
## iter 140 value 15.490868
## iter 150 value 15.489635
## iter 160 value 15.489374
## iter 170 value 15.489083
## iter 180 value 15.482141
## iter 190 value 14.527789
## iter 200 value 13.215848
## iter 210 value 13.176957
## iter 220 value 13.175374
## iter 230 value 13.175142
## iter 240 value 13.175034
## iter 250 value 13.174883
## iter 260 value 12.969938
## iter 270 value 12.531741
## iter 280 value 12.527483
## iter 290 value 12.527015
## iter 300 value 7.131845
## iter 310 value 6.180496
## iter 320 value 6.178023
## iter 330 value 6.177050
## iter 340 value 4.512015
## iter 350 value 3.421087
## iter 360 value 3.365186
## iter 370 value 3.357555
## iter 380 value 3.351691
## iter 390 value 3.350275
## iter 400 value 3.348552
## iter 410 value 3.346579
## iter 420 value 3.344428
## iter 430 value 3.343456
## iter 440 value 3.343110
## iter 450 value 3.342543
## iter 460 value 3.274412
## iter 470 value 0.762287
## iter 480 value 0.129811
## iter 490 value 0.121461
## iter 500 value 0.116151
## final  value 0.116151 
## stopped after 500 iterations
## # weights:  51
## initial  value 28.289407 
## iter  10 value 20.312547
## iter  20 value 20.299809
## iter  30 value 20.299205
## iter  40 value 20.298359
## iter  50 value 20.294732
## iter  60 value 19.611719
## iter  70 value 18.318273
## iter  80 value 18.317726
## iter  90 value 18.314096
## iter 100 value 14.563983
## iter 110 value 13.763090
## iter 120 value 13.760967
## iter 130 value 12.551438
## iter 140 value 9.372085
## iter 150 value 7.421305
## iter 160 value 6.423544
## iter 170 value 6.361536
## iter 180 value 6.339835
## iter 190 value 6.339199
## iter 200 value 6.337551
## iter 210 value 6.335510
## iter 220 value 6.333982
## iter 230 value 6.324867
## iter 240 value 6.226243
## iter 250 value 5.673291
## iter 260 value 4.466445
## iter 270 value 1.322380
## iter 280 value 0.281151
## iter 290 value 0.188520
## iter 300 value 0.177834
## iter 310 value 0.173908
## iter 320 value 0.171889
## iter 330 value 0.168808
## iter 340 value 0.163420
## iter 350 value 0.157477
## iter 360 value 0.152102
## iter 370 value 0.143182
## iter 380 value 0.134181
## iter 390 value 0.125348
## iter 400 value 0.118134
## iter 410 value 0.114970
## iter 420 value 0.110105
## iter 430 value 0.104629
## iter 440 value 0.102206
## iter 450 value 0.101108
## iter 460 value 0.100660
## iter 470 value 0.100156
## iter 480 value 0.098856
## iter 490 value 0.095350
## iter 500 value 0.094324
## final  value 0.094324 
## stopped after 500 iterations
## # weights:  61
## initial  value 29.188870 
## iter  10 value 25.461437
## iter  20 value 19.904936
## iter  30 value 11.603029
## iter  40 value 10.586892
## iter  50 value 8.833194
## iter  60 value 7.558752
## iter  70 value 7.172517
## iter  80 value 7.160287
## iter  90 value 6.983217
## iter 100 value 6.680496
## iter 110 value 4.931724
## iter 120 value 4.493442
## iter 130 value 4.480809
## iter 140 value 4.476945
## iter 150 value 4.474359
## iter 160 value 2.343630
## iter 170 value 2.088314
## iter 180 value 2.037534
## iter 190 value 0.835423
## iter 200 value 0.164879
## iter 210 value 0.153498
## iter 220 value 0.148786
## iter 230 value 0.146958
## iter 240 value 0.143330
## iter 250 value 0.140724
## iter 260 value 0.138188
## iter 270 value 0.135647
## iter 280 value 0.126851
## iter 290 value 0.115294
## iter 300 value 0.101688
## iter 310 value 0.094343
## iter 320 value 0.090833
## iter 330 value 0.084430
## iter 340 value 0.076036
## iter 350 value 0.073188
## iter 360 value 0.072002
## iter 370 value 0.070147
## iter 380 value 0.068815
## iter 390 value 0.068061
## iter 400 value 0.066868
## iter 410 value 0.066522
## iter 420 value 0.066178
## iter 430 value 0.065934
## iter 440 value 0.065896
## iter 450 value 0.065830
## iter 460 value 0.065733
## iter 470 value 0.065658
## iter 480 value 0.065590
## iter 490 value 0.065538
## iter 500 value 0.065519
## final  value 0.065519 
## stopped after 500 iterations
## # weights:  71
## initial  value 45.841868 
## iter  10 value 23.363959
## iter  20 value 17.810248
## iter  30 value 15.559739
## iter  40 value 15.534401
## iter  50 value 15.531143
## iter  60 value 15.530034
## iter  70 value 15.529416
## iter  80 value 15.528189
## iter  90 value 15.526213
## iter 100 value 15.509634
## iter 110 value 13.531420
## iter 120 value 12.485161
## iter 130 value 12.457638
## iter 140 value 12.453424
## iter 150 value 12.448114
## iter 160 value 12.444282
## iter 170 value 12.439407
## iter 180 value 12.392998
## iter 190 value 7.367415
## iter 200 value 6.302446
## iter 210 value 4.516420
## iter 220 value 4.356300
## iter 230 value 4.348103
## iter 240 value 4.336447
## iter 250 value 4.319545
## iter 260 value 3.524330
## iter 270 value 3.514791
## iter 280 value 3.510928
## iter 290 value 3.506889
## iter 300 value 3.414947
## iter 310 value 2.400433
## iter 320 value 2.392914
## iter 330 value 2.390387
## iter 340 value 2.383790
## iter 350 value 2.379773
## iter 360 value 2.023621
## iter 370 value 0.549538
## iter 380 value 0.304654
## iter 390 value 0.236933
## iter 400 value 0.203779
## iter 410 value 0.190340
## iter 420 value 0.179971
## iter 430 value 0.167633
## iter 440 value 0.154697
## iter 450 value 0.144147
## iter 460 value 0.139879
## iter 470 value 0.133928
## iter 480 value 0.127766
## iter 490 value 0.121114
## iter 500 value 0.115301
## final  value 0.115301 
## stopped after 500 iterations
## # weights:  81
## initial  value 42.657579 
## iter  10 value 28.472588
## iter  20 value 23.177088
## iter  30 value 23.002610
## iter  40 value 18.888111
## iter  50 value 11.553714
## iter  60 value 11.312836
## iter  70 value 11.309383
## iter  80 value 11.307810
## iter  90 value 11.306503
## iter 100 value 11.305766
## iter 110 value 11.305327
## iter 120 value 11.208082
## iter 130 value 9.406200
## iter 140 value 3.030319
## iter 150 value 2.163927
## iter 160 value 2.095949
## iter 170 value 2.064244
## iter 180 value 2.051361
## iter 190 value 2.041701
## iter 200 value 2.038986
## iter 210 value 2.037365
## iter 220 value 2.033389
## iter 230 value 2.025045
## iter 240 value 1.815897
## iter 250 value 0.268207
## iter 260 value 0.162759
## iter 270 value 0.149420
## iter 280 value 0.140773
## iter 290 value 0.135465
## iter 300 value 0.128807
## iter 310 value 0.124763
## iter 320 value 0.121584
## iter 330 value 0.117794
## iter 340 value 0.111215
## iter 350 value 0.104371
## iter 360 value 0.101848
## iter 370 value 0.100096
## iter 380 value 0.098065
## iter 390 value 0.095762
## iter 400 value 0.093378
## iter 410 value 0.091617
## iter 420 value 0.090499
## iter 430 value 0.088964
## iter 440 value 0.087394
## iter 450 value 0.085160
## iter 460 value 0.082415
## iter 470 value 0.080029
## iter 480 value 0.078699
## iter 490 value 0.077614
## iter 500 value 0.076712
## final  value 0.076712 
## stopped after 500 iterations
## # weights:  21
## initial  value 29.215097 
## iter  10 value 27.372469
## iter  20 value 23.341563
## iter  30 value 23.148730
## iter  40 value 23.110342
## iter  50 value 22.084074
## iter  60 value 20.010308
## iter  70 value 18.698459
## iter  80 value 18.690775
## iter  90 value 18.690202
## iter 100 value 18.690131
## iter 110 value 18.690030
## iter 120 value 18.689982
## iter 130 value 18.689815
## iter 140 value 16.994014
## iter 150 value 15.347692
## iter 160 value 15.319315
## iter 170 value 13.569284
## iter 180 value 13.091950
## iter 190 value 13.023625
## iter 200 value 12.154838
## iter 210 value 11.751365
## iter 220 value 10.814801
## iter 230 value 10.240711
## iter 240 value 10.231336
## iter 250 value 10.229646
## iter 260 value 10.226863
## iter 270 value 10.225684
## iter 280 value 10.224447
## iter 290 value 10.220426
## iter 300 value 10.219173
## iter 310 value 10.218190
## iter 320 value 10.216896
## iter 330 value 10.216508
## iter 340 value 10.215980
## iter 350 value 10.215812
## iter 360 value 10.215639
## iter 370 value 10.215373
## iter 380 value 10.215201
## iter 390 value 10.215144
## iter 400 value 10.215093
## iter 410 value 10.215018
## iter 420 value 10.214952
## iter 430 value 10.214922
## iter 440 value 10.214891
## iter 450 value 10.214855
## iter 460 value 10.214849
## iter 470 value 10.214845
## iter 480 value 10.214842
## iter 490 value 10.214837
## final  value 10.214827 
## converged
## # weights:  31
## initial  value 29.436850 
## iter  10 value 24.586429
## iter  20 value 21.183244
## iter  30 value 19.403894
## iter  40 value 19.303849
## iter  50 value 14.844705
## iter  60 value 14.171483
## iter  70 value 13.953038
## iter  80 value 13.913549
## iter  90 value 13.906880
## iter 100 value 13.814341
## iter 110 value 13.462502
## iter 120 value 13.230845
## iter 130 value 12.750469
## iter 140 value 12.158372
## iter 150 value 11.941904
## iter 160 value 11.852396
## iter 170 value 11.555465
## iter 180 value 11.499583
## iter 190 value 11.493404
## iter 200 value 11.492748
## iter 210 value 11.492114
## iter 220 value 11.491742
## iter 230 value 11.491564
## iter 240 value 11.491414
## iter 250 value 11.491287
## iter 260 value 11.491206
## iter 270 value 11.491185
## final  value 11.491141 
## converged
## # weights:  41
## initial  value 28.190106 
## iter  10 value 21.501238
## iter  20 value 18.071252
## iter  30 value 16.611834
## iter  40 value 16.530927
## iter  50 value 16.530051
## iter  60 value 16.529156
## iter  70 value 16.518673
## iter  80 value 14.401417
## iter  90 value 14.169596
## iter 100 value 14.168426
## iter 110 value 14.164636
## iter 120 value 12.704939
## iter 130 value 11.733594
## iter 140 value 11.690998
## iter 150 value 11.689568
## iter 160 value 11.544815
## iter 170 value 11.478635
## iter 180 value 11.478025
## iter 190 value 11.477606
## iter 200 value 11.476488
## iter 210 value 11.476198
## iter 220 value 11.475939
## iter 230 value 11.475772
## iter 240 value 11.475713
## iter 250 value 11.475677
## iter 260 value 11.475613
## iter 270 value 11.475574
## iter 280 value 11.475507
## iter 290 value 11.475451
## iter 300 value 11.473742
## iter 310 value 11.100065
## iter 320 value 7.416213
## iter 330 value 7.279801
## iter 340 value 7.277681
## iter 350 value 7.275559
## iter 360 value 7.274578
## iter 370 value 7.273273
## iter 380 value 7.271564
## iter 390 value 7.270802
## iter 400 value 7.270400
## iter 410 value 6.231577
## iter 420 value 6.139622
## iter 430 value 6.136175
## iter 440 value 6.135599
## iter 450 value 6.134582
## iter 460 value 6.131995
## iter 470 value 6.055793
## iter 480 value 5.439359
## iter 490 value 5.362510
## iter 500 value 5.355664
## final  value 5.355664 
## stopped after 500 iterations
## # weights:  51
## initial  value 27.746746 
## iter  10 value 18.957125
## iter  20 value 14.474737
## iter  30 value 12.703390
## iter  40 value 12.292552
## iter  50 value 12.043526
## iter  60 value 11.571839
## iter  70 value 10.818094
## iter  80 value 9.599729
## iter  90 value 8.402397
## iter 100 value 8.131895
## iter 110 value 8.054448
## iter 120 value 6.828483
## iter 130 value 6.363690
## iter 140 value 6.315993
## iter 150 value 6.298712
## iter 160 value 5.840478
## iter 170 value 5.694650
## iter 180 value 5.653401
## iter 190 value 5.651997
## iter 200 value 5.650350
## iter 210 value 5.648119
## iter 220 value 5.646367
## iter 230 value 5.645646
## iter 240 value 5.643822
## iter 250 value 5.641570
## iter 260 value 5.641115
## iter 270 value 5.640524
## iter 280 value 5.639851
## iter 290 value 5.552258
## iter 300 value 3.783972
## iter 310 value 2.198701
## iter 320 value 1.862992
## iter 330 value 1.538791
## iter 340 value 1.509512
## iter 350 value 1.496603
## iter 360 value 1.494675
## iter 370 value 1.493679
## iter 380 value 1.492830
## iter 390 value 1.491478
## iter 400 value 1.052175
## iter 410 value 0.271418
## iter 420 value 0.142790
## iter 430 value 0.129267
## iter 440 value 0.124407
## iter 450 value 0.121983
## iter 460 value 0.119078
## iter 470 value 0.116654
## iter 480 value 0.114691
## iter 490 value 0.112858
## iter 500 value 0.110843
## final  value 0.110843 
## stopped after 500 iterations
## # weights:  61
## initial  value 33.093842 
## iter  10 value 21.416973
## iter  20 value 15.859603
## iter  30 value 15.365342
## iter  40 value 15.346958
## iter  50 value 15.346137
## iter  60 value 15.345997
## iter  70 value 15.345517
## iter  80 value 15.211884
## iter  90 value 9.376465
## iter 100 value 9.176846
## iter 110 value 8.824434
## iter 120 value 7.817573
## iter 130 value 4.371229
## iter 140 value 1.770567
## iter 150 value 1.588751
## iter 160 value 1.580708
## iter 170 value 1.568894
## iter 180 value 1.558988
## iter 190 value 1.547869
## iter 200 value 1.539201
## iter 210 value 1.536355
## iter 220 value 1.533622
## iter 230 value 1.531313
## iter 240 value 1.513959
## iter 250 value 0.525123
## iter 260 value 0.252335
## iter 270 value 0.232215
## iter 280 value 0.218442
## iter 290 value 0.215209
## iter 300 value 0.213253
## iter 310 value 0.209184
## iter 320 value 0.203792
## iter 330 value 0.188743
## iter 340 value 0.173387
## iter 350 value 0.156459
## iter 360 value 0.146060
## iter 370 value 0.143885
## iter 380 value 0.139430
## iter 390 value 0.131969
## iter 400 value 0.124559
## iter 410 value 0.115970
## iter 420 value 0.111582
## iter 430 value 0.110048
## iter 440 value 0.108790
## iter 450 value 0.107927
## iter 460 value 0.106953
## iter 470 value 0.105178
## iter 480 value 0.103990
## iter 490 value 0.103698
## iter 500 value 0.103310
## final  value 0.103310 
## stopped after 500 iterations
## # weights:  71
## initial  value 32.772103 
## iter  10 value 28.744761
## iter  20 value 26.458475
## iter  30 value 14.605585
## iter  40 value 13.914617
## iter  50 value 13.908917
## iter  60 value 13.907791
## iter  70 value 13.906523
## iter  80 value 13.904321
## iter  90 value 13.838487
## iter 100 value 12.204166
## iter 110 value 8.616023
## iter 120 value 6.159873
## iter 130 value 5.676750
## iter 140 value 5.671916
## iter 150 value 5.664350
## iter 160 value 5.656166
## iter 170 value 5.654260
## iter 180 value 3.587828
## iter 190 value 2.983742
## iter 200 value 2.977839
## iter 210 value 2.973069
## iter 220 value 2.972089
## iter 230 value 2.970366
## iter 240 value 2.968294
## iter 250 value 2.964967
## iter 260 value 2.963457
## iter 270 value 2.962581
## iter 280 value 2.961988
## iter 290 value 2.960950
## iter 300 value 2.958949
## iter 310 value 2.940776
## iter 320 value 2.848717
## iter 330 value 2.397201
## iter 340 value 0.934303
## iter 350 value 0.318512
## iter 360 value 0.200872
## iter 370 value 0.172902
## iter 380 value 0.165806
## iter 390 value 0.158796
## iter 400 value 0.147679
## iter 410 value 0.136301
## iter 420 value 0.124421
## iter 430 value 0.119473
## iter 440 value 0.114046
## iter 450 value 0.108300
## iter 460 value 0.106421
## iter 470 value 0.104685
## iter 480 value 0.103654
## iter 490 value 0.102730
## iter 500 value 0.101201
## final  value 0.101201 
## stopped after 500 iterations
## # weights:  81
## initial  value 30.206656 
## iter  10 value 21.037900
## iter  20 value 16.719574
## iter  30 value 13.754470
## iter  40 value 8.033226
## iter  50 value 6.019484
## iter  60 value 5.826794
## iter  70 value 5.820333
## iter  80 value 5.810129
## iter  90 value 5.056828
## iter 100 value 4.379199
## iter 110 value 3.908554
## iter 120 value 3.897460
## iter 130 value 3.799391
## iter 140 value 2.192190
## iter 150 value 2.056092
## iter 160 value 2.038509
## iter 170 value 2.035527
## iter 180 value 1.510221
## iter 190 value 0.275433
## iter 200 value 0.151944
## iter 210 value 0.146081
## iter 220 value 0.141193
## iter 230 value 0.137244
## iter 240 value 0.134336
## iter 250 value 0.132111
## iter 260 value 0.121295
## iter 270 value 0.103907
## iter 280 value 0.096430
## iter 290 value 0.091834
## iter 300 value 0.084717
## iter 310 value 0.080425
## iter 320 value 0.078084
## iter 330 value 0.077020
## iter 340 value 0.076555
## iter 350 value 0.076418
## iter 360 value 0.076275
## iter 370 value 0.076157
## iter 380 value 0.075990
## iter 390 value 0.075790
## iter 400 value 0.075335
## iter 410 value 0.074243
## iter 420 value 0.073546
## iter 430 value 0.073193
## iter 440 value 0.072901
## iter 450 value 0.072753
## iter 460 value 0.072588
## iter 470 value 0.072516
## iter 480 value 0.072439
## iter 490 value 0.071293
## iter 500 value 0.069461
## final  value 0.069461 
## stopped after 500 iterations
## # weights:  21
## initial  value 27.855471 
## final  value 27.374122 
## converged
## # weights:  31
## initial  value 26.612910 
## iter  10 value 16.326813
## iter  20 value 14.363665
## iter  30 value 11.559322
## iter  40 value 11.372335
## iter  50 value 11.335839
## iter  60 value 11.234190
## iter  70 value 11.150510
## iter  80 value 10.882469
## iter  90 value 10.849596
## iter 100 value 10.848520
## iter 110 value 10.848422
## iter 120 value 10.848329
## iter 130 value 10.848150
## iter 140 value 10.848050
## iter 150 value 10.848002
## iter 160 value 10.847964
## iter 170 value 10.847631
## iter 180 value 10.847614
## iter 190 value 10.847593
## final  value 10.847584 
## converged
## # weights:  41
## initial  value 30.063314 
## iter  10 value 16.143901
## iter  20 value 12.876116
## iter  30 value 10.948204
## iter  40 value 10.909226
## iter  50 value 10.908044
## iter  60 value 10.906936
## iter  70 value 8.928865
## iter  80 value 6.248579
## iter  90 value 6.194803
## iter 100 value 6.192068
## iter 110 value 6.190538
## iter 120 value 6.188971
## iter 130 value 6.188130
## iter 140 value 6.187512
## iter 150 value 6.186924
## iter 160 value 6.154450
## iter 170 value 6.153951
## iter 180 value 6.153501
## iter 190 value 5.884392
## iter 200 value 4.285369
## iter 210 value 4.252057
## iter 220 value 3.926457
## iter 230 value 3.876324
## iter 240 value 3.873226
## iter 250 value 3.871517
## iter 260 value 3.870136
## iter 270 value 3.869255
## iter 280 value 3.868732
## iter 290 value 3.868405
## iter 300 value 2.926736
## iter 310 value 2.828939
## iter 320 value 2.827059
## iter 330 value 2.826012
## iter 340 value 2.825764
## iter 350 value 2.825392
## iter 360 value 2.825261
## iter 370 value 2.825073
## iter 380 value 2.824788
## iter 390 value 2.824367
## iter 400 value 2.824308
## iter 410 value 2.824268
## iter 420 value 2.824247
## iter 430 value 2.824216
## final  value 2.824210 
## converged
## # weights:  51
## initial  value 31.183002 
## iter  10 value 26.060584
## iter  20 value 20.264618
## iter  30 value 18.094617
## iter  40 value 13.207397
## iter  50 value 13.181660
## iter  60 value 13.180984
## iter  70 value 13.180371
## iter  80 value 13.179860
## iter  90 value 13.179681
## iter 100 value 13.179436
## iter 110 value 13.179369
## iter 120 value 13.170066
## iter 130 value 11.992445
## iter 140 value 9.820892
## iter 150 value 9.796094
## iter 160 value 9.644852
## iter 170 value 9.213215
## iter 180 value 8.376568
## iter 190 value 7.758448
## iter 200 value 7.720430
## iter 210 value 7.719602
## iter 220 value 7.717969
## iter 230 value 7.717384
## iter 240 value 7.716768
## iter 250 value 6.102943
## iter 260 value 4.995510
## iter 270 value 4.991651
## iter 280 value 4.985794
## iter 290 value 4.981621
## iter 300 value 4.977333
## iter 310 value 4.971845
## iter 320 value 4.828320
## iter 330 value 4.682405
## iter 340 value 4.586840
## iter 350 value 4.584886
## iter 360 value 4.584356
## iter 370 value 4.583406
## iter 380 value 4.582138
## iter 390 value 4.580841
## iter 400 value 4.505772
## iter 410 value 4.456036
## iter 420 value 4.454464
## iter 430 value 4.445884
## iter 440 value 4.322075
## iter 450 value 4.316970
## iter 460 value 4.316386
## iter 470 value 4.316140
## iter 480 value 4.315703
## iter 490 value 4.315533
## iter 500 value 4.315382
## final  value 4.315382 
## stopped after 500 iterations
## # weights:  61
## initial  value 29.020289 
## iter  10 value 15.155203
## iter  20 value 14.729080
## iter  30 value 11.506321
## iter  40 value 10.558387
## iter  50 value 9.956419
## iter  60 value 9.949159
## iter  70 value 9.912972
## iter  80 value 9.519558
## iter  90 value 9.511452
## iter 100 value 9.482238
## iter 110 value 9.108664
## iter 120 value 9.018004
## iter 130 value 8.955824
## iter 140 value 8.499994
## iter 150 value 8.388461
## iter 160 value 8.385890
## iter 170 value 8.384364
## iter 180 value 8.382365
## iter 190 value 8.380222
## iter 200 value 8.379494
## iter 210 value 8.378768
## iter 220 value 8.037842
## iter 230 value 7.600986
## iter 240 value 7.163698
## iter 250 value 6.532685
## iter 260 value 6.369814
## iter 270 value 6.368813
## iter 280 value 6.368267
## iter 290 value 6.367761
## iter 300 value 6.367323
## iter 310 value 6.366937
## iter 320 value 6.366125
## iter 330 value 6.364985
## iter 340 value 6.362407
## iter 350 value 6.360555
## iter 360 value 6.359643
## iter 370 value 6.358982
## iter 380 value 6.358567
## iter 390 value 6.358082
## iter 400 value 6.358034
## iter 410 value 6.357695
## iter 420 value 6.119741
## iter 430 value 4.019067
## iter 440 value 3.959580
## iter 450 value 3.949205
## iter 460 value 3.948132
## iter 470 value 3.945884
## iter 480 value 3.941357
## iter 490 value 3.423891
## iter 500 value 1.713094
## final  value 1.713094 
## stopped after 500 iterations
## # weights:  71
## initial  value 49.153068 
## iter  10 value 18.713107
## iter  20 value 12.803310
## iter  30 value 8.090482
## iter  40 value 7.427939
## iter  50 value 7.423489
## iter  60 value 7.420837
## iter  70 value 7.419088
## iter  80 value 7.219621
## iter  90 value 6.347274
## iter 100 value 6.323232
## iter 110 value 6.314880
## iter 120 value 6.309166
## iter 130 value 6.306807
## iter 140 value 6.303827
## iter 150 value 3.380178
## iter 160 value 3.159767
## iter 170 value 3.128247
## iter 180 value 3.114601
## iter 190 value 3.100240
## iter 200 value 3.088747
## iter 210 value 3.018659
## iter 220 value 2.161192
## iter 230 value 0.468314
## iter 240 value 0.308515
## iter 250 value 0.238176
## iter 260 value 0.219527
## iter 270 value 0.216648
## iter 280 value 0.211482
## iter 290 value 0.203549
## iter 300 value 0.193600
## iter 310 value 0.179765
## iter 320 value 0.171223
## iter 330 value 0.156251
## iter 340 value 0.144882
## iter 350 value 0.132332
## iter 360 value 0.120842
## iter 370 value 0.114851
## iter 380 value 0.110697
## iter 390 value 0.101682
## iter 400 value 0.093420
## iter 410 value 0.087221
## iter 420 value 0.082727
## iter 430 value 0.078162
## iter 440 value 0.074559
## iter 450 value 0.067651
## iter 460 value 0.062917
## iter 470 value 0.059998
## iter 480 value 0.057489
## iter 490 value 0.055624
## iter 500 value 0.054443
## final  value 0.054443 
## stopped after 500 iterations
## # weights:  81
## initial  value 28.353790 
## iter  10 value 20.095902
## iter  20 value 15.507328
## iter  30 value 10.977292
## iter  40 value 8.006481
## iter  50 value 7.161931
## iter  60 value 7.005715
## iter  70 value 7.002971
## iter  80 value 7.001811
## iter  90 value 7.000746
## iter 100 value 6.960268
## iter 110 value 6.494225
## iter 120 value 5.719243
## iter 130 value 5.465279
## iter 140 value 5.458188
## iter 150 value 5.452053
## iter 160 value 5.442580
## iter 170 value 5.430558
## iter 180 value 5.427336
## iter 190 value 5.423913
## iter 200 value 5.075772
## iter 210 value 4.524373
## iter 220 value 4.511117
## iter 230 value 4.504844
## iter 240 value 4.499823
## iter 250 value 4.496578
## iter 260 value 4.490718
## iter 270 value 4.485117
## iter 280 value 4.477398
## iter 290 value 0.275815
## iter 300 value 0.143904
## iter 310 value 0.117420
## iter 320 value 0.112648
## iter 330 value 0.105581
## iter 340 value 0.099977
## iter 350 value 0.096223
## iter 360 value 0.089404
## iter 370 value 0.085040
## iter 380 value 0.080136
## iter 390 value 0.078236
## iter 400 value 0.073478
## iter 410 value 0.070023
## iter 420 value 0.067334
## iter 430 value 0.065266
## iter 440 value 0.064247
## iter 450 value 0.063762
## iter 460 value 0.063453
## iter 470 value 0.062925
## iter 480 value 0.062565
## iter 490 value 0.062259
## iter 500 value 0.061662
## final  value 0.061662 
## stopped after 500 iterations
## # weights:  21
## initial  value 31.626081 
## iter  10 value 19.387964
## iter  20 value 16.744461
## iter  30 value 16.593237
## iter  40 value 16.592317
## iter  50 value 16.592080
## iter  60 value 16.592022
## iter  70 value 16.592007
## iter  80 value 16.591923
## final  value 16.591909 
## converged
## # weights:  31
## initial  value 28.652883 
## iter  10 value 19.274347
## iter  20 value 16.899457
## iter  30 value 16.628891
## iter  40 value 16.467872
## iter  50 value 16.278075
## iter  60 value 16.096034
## iter  70 value 15.998482
## iter  80 value 15.708269
## iter  90 value 15.693096
## iter 100 value 15.691404
## iter 110 value 15.690686
## iter 120 value 15.690528
## iter 130 value 15.690450
## iter 140 value 15.690410
## iter 150 value 15.690391
## iter 160 value 15.690311
## iter 170 value 15.690240
## iter 180 value 15.690206
## iter 190 value 15.690146
## final  value 15.690139 
## converged
## # weights:  41
## initial  value 31.826722 
## iter  10 value 22.064352
## iter  20 value 18.489769
## iter  30 value 13.166684
## iter  40 value 10.226269
## iter  50 value 9.481282
## iter  60 value 9.471644
## iter  70 value 9.470487
## iter  80 value 9.469301
## iter  90 value 9.316926
## iter 100 value 9.236537
## iter 110 value 9.236093
## iter 120 value 9.235792
## iter 130 value 9.235466
## iter 140 value 9.235239
## iter 150 value 9.235133
## iter 160 value 9.235041
## iter 170 value 9.234967
## iter 180 value 9.003257
## iter 190 value 5.253135
## iter 200 value 5.007862
## iter 210 value 3.514466
## iter 220 value 3.503065
## iter 230 value 3.501759
## iter 240 value 3.498801
## iter 250 value 3.496023
## iter 260 value 3.494801
## iter 270 value 3.493912
## iter 280 value 3.492181
## iter 290 value 3.489426
## iter 300 value 3.488650
## iter 310 value 3.488053
## iter 320 value 3.487578
## iter 330 value 3.487445
## iter 340 value 3.487223
## iter 350 value 3.486941
## iter 360 value 3.486757
## iter 370 value 3.486669
## iter 380 value 3.486474
## iter 390 value 3.486041
## iter 400 value 3.485833
## iter 410 value 3.485562
## iter 420 value 3.485488
## iter 430 value 3.485397
## iter 440 value 3.485336
## iter 450 value 3.485310
## final  value 3.485301 
## converged
## # weights:  51
## initial  value 30.549782 
## iter  10 value 28.346631
## iter  20 value 28.346570
## iter  30 value 24.584858
## iter  40 value 18.735242
## iter  50 value 18.067628
## iter  60 value 18.037243
## iter  70 value 17.164750
## iter  80 value 15.498232
## iter  90 value 15.396587
## iter 100 value 14.858948
## iter 110 value 14.839626
## iter 120 value 14.837399
## iter 130 value 14.835960
## iter 140 value 14.834454
## iter 150 value 14.832919
## iter 160 value 14.831266
## iter 170 value 13.243453
## iter 180 value 11.840123
## iter 190 value 11.832087
## iter 200 value 11.830679
## iter 210 value 11.829291
## iter 220 value 11.827487
## iter 230 value 11.826551
## iter 240 value 11.825246
## iter 250 value 11.824387
## iter 260 value 10.438598
## iter 270 value 10.014654
## iter 280 value 9.995261
## iter 290 value 9.992158
## iter 300 value 9.991382
## iter 310 value 9.990118
## iter 320 value 9.215596
## iter 330 value 9.179833
## iter 340 value 9.178581
## iter 350 value 9.177947
## iter 360 value 9.171132
## iter 370 value 8.973268
## iter 380 value 8.084764
## iter 390 value 8.080030
## iter 400 value 8.078956
## iter 410 value 8.078589
## iter 420 value 8.078033
## iter 430 value 8.077630
## iter 440 value 8.077192
## iter 450 value 8.076998
## iter 460 value 8.076885
## iter 470 value 8.076805
## iter 480 value 8.076797
## iter 490 value 8.076788
## iter 500 value 8.076780
## final  value 8.076780 
## stopped after 500 iterations
## # weights:  61
## initial  value 29.847128 
## iter  10 value 21.518473
## iter  20 value 20.956379
## iter  30 value 20.955186
## iter  40 value 16.204498
## iter  50 value 14.468399
## iter  60 value 12.691002
## iter  70 value 9.889549
## iter  80 value 9.595519
## iter  90 value 9.313574
## iter 100 value 9.034426
## iter 110 value 9.030692
## iter 120 value 9.027080
## iter 130 value 8.990119
## iter 140 value 7.699156
## iter 150 value 7.646048
## iter 160 value 7.643824
## iter 170 value 7.642592
## iter 180 value 7.641990
## iter 190 value 7.641498
## iter 200 value 7.641111
## iter 210 value 7.640722
## iter 220 value 7.640596
## iter 230 value 5.082817
## iter 240 value 2.759681
## iter 250 value 0.615368
## iter 260 value 0.214534
## iter 270 value 0.135948
## iter 280 value 0.131196
## iter 290 value 0.127242
## iter 300 value 0.125112
## iter 310 value 0.119460
## iter 320 value 0.115494
## iter 330 value 0.112513
## iter 340 value 0.111298
## iter 350 value 0.110723
## iter 360 value 0.109047
## iter 370 value 0.104716
## iter 380 value 0.103093
## iter 390 value 0.101924
## iter 400 value 0.101139
## iter 410 value 0.100128
## iter 420 value 0.099127
## iter 430 value 0.098660
## iter 440 value 0.098279
## iter 450 value 0.097810
## iter 460 value 0.097489
## iter 470 value 0.097102
## iter 480 value 0.096169
## iter 490 value 0.095308
## iter 500 value 0.094996
## final  value 0.094996 
## stopped after 500 iterations
## # weights:  71
## initial  value 44.993777 
## iter  10 value 21.993243
## iter  20 value 19.355053
## iter  30 value 18.743140
## iter  40 value 17.592289
## iter  50 value 14.688390
## iter  60 value 14.454751
## iter  70 value 14.450455
## iter  80 value 14.290371
## iter  90 value 13.292925
## iter 100 value 13.113448
## iter 110 value 12.861983
## iter 120 value 12.844356
## iter 130 value 12.757252
## iter 140 value 12.584234
## iter 150 value 10.641751
## iter 160 value 10.494393
## iter 170 value 10.486863
## iter 180 value 10.479131
## iter 190 value 10.469244
## iter 200 value 9.828721
## iter 210 value 9.811576
## iter 220 value 9.792183
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## iter 250 value 8.567823
## iter 260 value 7.737655
## iter 270 value 7.680666
## iter 280 value 7.678730
## iter 290 value 7.676397
## iter 300 value 7.673540
## iter 310 value 7.671166
## iter 320 value 7.667245
## iter 330 value 7.665324
## iter 340 value 7.662211
## iter 350 value 7.661134
## iter 360 value 7.660667
## iter 370 value 7.659912
## iter 380 value 7.659578
## iter 390 value 7.653940
## iter 400 value 6.967818
## iter 410 value 6.786623
## iter 420 value 6.573065
## iter 430 value 5.859033
## iter 440 value 5.824906
## iter 450 value 5.823795
## iter 460 value 5.823377
## iter 470 value 5.823094
## iter 480 value 5.822812
## iter 490 value 5.822709
## iter 500 value 5.822646
## final  value 5.822646 
## stopped after 500 iterations
## # weights:  81
## initial  value 38.652729 
## iter  10 value 20.458344
## iter  20 value 13.119006
## iter  30 value 11.191442
## iter  40 value 10.782316
## iter  50 value 10.304337
## iter  60 value 10.285048
## iter  70 value 10.282539
## iter  80 value 9.975786
## iter  90 value 9.966174
## iter 100 value 9.964580
## iter 110 value 8.734901
## iter 120 value 8.727862
## iter 130 value 8.725910
## iter 140 value 8.721157
## iter 150 value 8.700504
## iter 160 value 8.429754
## iter 170 value 7.658613
## iter 180 value 7.599711
## iter 190 value 7.476578
## iter 200 value 7.016353
## iter 210 value 7.006545
## iter 220 value 7.005777
## iter 230 value 7.004586
## iter 240 value 7.003983
## iter 250 value 7.003456
## iter 260 value 7.002669
## iter 270 value 7.002365
## iter 280 value 7.002095
## iter 290 value 7.001778
## iter 300 value 6.304565
## iter 310 value 4.772724
## iter 320 value 4.728780
## iter 330 value 4.727102
## iter 340 value 4.726456
## iter 350 value 4.725977
## iter 360 value 4.725597
## iter 370 value 4.725258
## iter 380 value 4.725110
## iter 390 value 4.724984
## iter 400 value 4.724856
## iter 410 value 4.724745
## iter 420 value 1.062615
## iter 430 value 0.310208
## iter 440 value 0.136601
## iter 450 value 0.124562
## iter 460 value 0.122682
## iter 470 value 0.121958
## iter 480 value 0.120222
## iter 490 value 0.118339
## iter 500 value 0.117656
## final  value 0.117656 
## stopped after 500 iterations
## # weights:  21
## initial  value 41.545025 
## iter  10 value 18.365296
## iter  20 value 17.818097
## iter  30 value 16.883158
## iter  40 value 16.869036
## iter  50 value 16.868412
## iter  60 value 16.868298
## iter  70 value 16.868124
## iter  80 value 16.867869
## iter  90 value 16.867776
## iter 100 value 16.867636
## iter 110 value 16.867612
## iter 120 value 16.867586
## final  value 16.867585 
## converged
## # weights:  31
## initial  value 27.829250 
## iter  10 value 23.728891
## iter  20 value 19.959786
## iter  30 value 18.986470
## iter  40 value 17.810424
## iter  50 value 14.289746
## iter  60 value 13.962633
## iter  70 value 13.954862
## iter  80 value 13.952775
## iter  90 value 13.951934
## iter 100 value 13.949937
## iter 110 value 12.616299
## iter 120 value 12.561556
## iter 130 value 11.580131
## iter 140 value 11.423296
## iter 150 value 11.397068
## iter 160 value 11.366530
## iter 170 value 11.354114
## iter 180 value 11.313449
## iter 190 value 11.308156
## iter 200 value 11.307497
## iter 210 value 11.306828
## iter 220 value 11.304284
## iter 230 value 11.162035
## iter 240 value 11.045391
## iter 250 value 11.007083
## iter 260 value 10.986332
## iter 270 value 10.957548
## iter 280 value 10.956889
## iter 290 value 10.956155
## iter 300 value 10.955133
## iter 310 value 10.954633
## iter 320 value 10.954395
## iter 330 value 10.954104
## iter 340 value 10.891892
## iter 350 value 9.535844
## iter 360 value 8.984176
## iter 370 value 8.975098
## iter 380 value 8.972727
## iter 390 value 8.971827
## iter 400 value 8.971355
## iter 410 value 8.970887
## iter 420 value 8.970695
## iter 430 value 8.970429
## iter 440 value 8.970221
## iter 450 value 8.970053
## iter 460 value 8.969983
## iter 470 value 8.969926
## iter 470 value 8.969926
## final  value 8.969926 
## converged
## # weights:  41
## initial  value 27.700754 
## iter  10 value 19.070345
## iter  20 value 15.786635
## iter  30 value 13.934771
## iter  40 value 13.670289
## iter  50 value 12.376515
## iter  60 value 12.333644
## iter  70 value 12.331118
## iter  80 value 12.330031
## iter  90 value 12.328941
## iter 100 value 12.328440
## iter 110 value 12.323648
## iter 120 value 12.257578
## iter 130 value 5.464314
## iter 140 value 3.649668
## iter 150 value 1.771284
## iter 160 value 0.611835
## iter 170 value 0.186864
## iter 180 value 0.128181
## iter 190 value 0.118436
## iter 200 value 0.116717
## iter 210 value 0.114929
## iter 220 value 0.113898
## iter 230 value 0.111786
## iter 240 value 0.110967
## iter 250 value 0.110184
## iter 260 value 0.109435
## iter 270 value 0.108762
## iter 280 value 0.107067
## iter 290 value 0.106084
## iter 300 value 0.104058
## iter 310 value 0.103185
## iter 320 value 0.102953
## iter 330 value 0.102682
## iter 340 value 0.102522
## iter 350 value 0.102200
## iter 360 value 0.101591
## iter 370 value 0.101474
## iter 380 value 0.101415
## iter 390 value 0.101388
## iter 400 value 0.101358
## iter 410 value 0.101343
## iter 420 value 0.101337
## iter 430 value 0.101319
## iter 440 value 0.101198
## iter 450 value 0.101115
## iter 460 value 0.101029
## iter 470 value 0.100999
## iter 480 value 0.100984
## iter 490 value 0.100961
## iter 500 value 0.100948
## final  value 0.100948 
## stopped after 500 iterations
## # weights:  51
## initial  value 37.593837 
## iter  10 value 22.544840
## iter  20 value 20.948252
## iter  30 value 19.875223
## iter  40 value 18.744859
## iter  50 value 18.589713
## iter  60 value 18.588667
## iter  70 value 18.587364
## iter  80 value 18.585894
## iter  90 value 18.585443
## iter 100 value 18.584959
## iter 110 value 18.583619
## iter 120 value 18.475080
## iter 130 value 12.949186
## iter 140 value 12.752067
## iter 150 value 12.666237
## iter 160 value 12.139387
## iter 170 value 12.132213
## iter 180 value 12.128539
## iter 190 value 12.123966
## iter 200 value 12.112209
## iter 210 value 11.994133
## iter 220 value 5.575706
## iter 230 value 4.392081
## iter 240 value 3.671022
## iter 250 value 3.542224
## iter 260 value 3.531876
## iter 270 value 3.518907
## iter 280 value 3.508315
## iter 290 value 3.503081
## iter 300 value 3.486045
## iter 310 value 3.482509
## iter 320 value 3.475743
## iter 330 value 3.468780
## iter 340 value 2.046879
## iter 350 value 0.296722
## iter 360 value 0.192341
## iter 370 value 0.145360
## iter 380 value 0.138919
## iter 390 value 0.133084
## iter 400 value 0.127240
## iter 410 value 0.123751
## iter 420 value 0.120889
## iter 430 value 0.119275
## iter 440 value 0.116217
## iter 450 value 0.114932
## iter 460 value 0.112693
## iter 470 value 0.110925
## iter 480 value 0.108921
## iter 490 value 0.107022
## iter 500 value 0.105492
## final  value 0.105492 
## stopped after 500 iterations
## # weights:  61
## initial  value 34.062493 
## iter  10 value 19.717215
## iter  20 value 12.210992
## iter  30 value 6.737348
## iter  40 value 6.452226
## iter  50 value 6.433437
## iter  60 value 6.409305
## iter  70 value 6.113590
## iter  80 value 5.980441
## iter  90 value 5.972779
## iter 100 value 5.829217
## iter 110 value 5.823664
## iter 120 value 5.815688
## iter 130 value 5.813804
## iter 140 value 5.810390
## iter 150 value 5.805838
## iter 160 value 5.804088
## iter 170 value 5.801797
## iter 180 value 5.738487
## iter 190 value 5.239901
## iter 200 value 5.193340
## iter 210 value 5.188888
## iter 220 value 5.185495
## iter 230 value 5.184116
## iter 240 value 5.170974
## iter 250 value 3.036202
## iter 260 value 2.638148
## iter 270 value 1.426797
## iter 280 value 0.196065
## iter 290 value 0.149699
## iter 300 value 0.134353
## iter 310 value 0.131772
## iter 320 value 0.130191
## iter 330 value 0.125752
## iter 340 value 0.122848
## iter 350 value 0.121339
## iter 360 value 0.120200
## iter 370 value 0.119874
## iter 380 value 0.119415
## iter 390 value 0.119163
## iter 400 value 0.117590
## iter 410 value 0.117345
## iter 420 value 0.115806
## iter 430 value 0.114974
## iter 440 value 0.114709
## iter 450 value 0.114425
## iter 460 value 0.114252
## iter 470 value 0.114069
## iter 480 value 0.113797
## iter 490 value 0.113612
## iter 500 value 0.113502
## final  value 0.113502 
## stopped after 500 iterations
## # weights:  71
## initial  value 41.766084 
## iter  10 value 27.348471
## iter  20 value 20.070372
## iter  30 value 19.175942
## iter  40 value 19.174689
## iter  50 value 19.172988
## iter  60 value 18.534363
## iter  70 value 15.532743
## iter  80 value 15.451368
## iter  90 value 15.134361
## iter 100 value 15.129962
## iter 110 value 15.128510
## iter 120 value 15.055764
## iter 130 value 14.579013
## iter 140 value 14.425009
## iter 150 value 14.422652
## iter 160 value 14.211384
## iter 170 value 13.217880
## iter 180 value 13.095395
## iter 190 value 13.079117
## iter 200 value 12.794173
## iter 210 value 12.791105
## iter 220 value 12.789695
## iter 230 value 11.829414
## iter 240 value 10.910390
## iter 250 value 10.624902
## iter 260 value 9.161131
## iter 270 value 7.453586
## iter 280 value 6.696441
## iter 290 value 6.658860
## iter 300 value 6.617622
## iter 310 value 6.599628
## iter 320 value 6.586792
## iter 330 value 6.571851
## iter 340 value 6.561864
## iter 350 value 6.552577
## iter 360 value 6.520182
## iter 370 value 2.506669
## iter 380 value 2.385291
## iter 390 value 2.372008
## iter 400 value 2.357781
## iter 410 value 2.348771
## iter 420 value 2.341939
## iter 430 value 2.337957
## iter 440 value 2.334520
## iter 450 value 2.331133
## iter 460 value 2.330117
## iter 470 value 2.328914
## iter 480 value 2.327913
## iter 490 value 2.324883
## iter 500 value 1.918317
## final  value 1.918317 
## stopped after 500 iterations
## # weights:  81
## initial  value 30.872735 
## iter  10 value 18.075290
## iter  20 value 16.450156
## iter  30 value 15.343398
## iter  40 value 13.481717
## iter  50 value 12.479000
## iter  60 value 12.462183
## iter  70 value 12.430980
## iter  80 value 12.392523
## iter  90 value 12.382125
## iter 100 value 12.377279
## iter 110 value 12.376054
## iter 120 value 12.374905
## iter 130 value 12.372459
## iter 140 value 12.368765
## iter 150 value 10.653880
## iter 160 value 9.193373
## iter 170 value 9.067343
## iter 180 value 9.046602
## iter 190 value 9.023346
## iter 200 value 8.262026
## iter 210 value 7.880887
## iter 220 value 6.438278
## iter 230 value 6.352346
## iter 240 value 6.232391
## iter 250 value 4.410605
## iter 260 value 4.051219
## iter 270 value 4.010281
## iter 280 value 3.993643
## iter 290 value 3.971635
## iter 300 value 3.239274
## iter 310 value 0.607993
## iter 320 value 0.231998
## iter 330 value 0.181649
## iter 340 value 0.171896
## iter 350 value 0.166731
## iter 360 value 0.158782
## iter 370 value 0.151093
## iter 380 value 0.142662
## iter 390 value 0.137204
## iter 400 value 0.135767
## iter 410 value 0.126513
## iter 420 value 0.120168
## iter 430 value 0.116825
## iter 440 value 0.111654
## iter 450 value 0.105219
## iter 460 value 0.102944
## iter 470 value 0.100268
## iter 480 value 0.097804
## iter 490 value 0.096074
## iter 500 value 0.093352
## final  value 0.093352 
## stopped after 500 iterations
## # weights:  21
## initial  value 28.246381 
## iter  10 value 23.834740
## iter  20 value 18.611897
## iter  30 value 17.883686
## iter  40 value 17.882415
## iter  50 value 17.304205
## iter  60 value 16.659497
## iter  70 value 16.656144
## iter  80 value 16.655722
## iter  90 value 15.661717
## iter 100 value 15.637945
## iter 110 value 14.937099
## iter 120 value 13.891578
## iter 130 value 12.898300
## iter 140 value 12.452197
## iter 150 value 12.365349
## iter 160 value 12.363362
## iter 170 value 12.361937
## iter 180 value 12.361779
## iter 190 value 12.361473
## iter 200 value 12.361298
## final  value 12.361140 
## converged
## # weights:  31
## initial  value 28.943838 
## iter  10 value 24.680856
## iter  20 value 17.861500
## iter  30 value 16.797221
## iter  40 value 16.796091
## iter  50 value 16.795685
## iter  60 value 16.795421
## iter  70 value 16.795318
## iter  80 value 16.795006
## iter  90 value 12.610447
## iter 100 value 10.988601
## iter 110 value 10.962378
## iter 120 value 10.959160
## iter 130 value 10.958734
## iter 140 value 10.958126
## iter 150 value 10.956213
## iter 160 value 10.955447
## iter 170 value 10.955154
## iter 180 value 10.954820
## iter 190 value 10.954605
## iter 200 value 10.954421
## final  value 10.954404 
## converged
## # weights:  41
## initial  value 32.626750 
## iter  10 value 20.832739
## iter  20 value 15.605383
## iter  30 value 14.871252
## iter  40 value 10.943694
## iter  50 value 8.609817
## iter  60 value 8.516206
## iter  70 value 8.510512
## iter  80 value 8.508485
## iter  90 value 8.506770
## iter 100 value 8.505465
## iter 110 value 8.504853
## iter 120 value 8.504132
## iter 130 value 8.503075
## iter 140 value 8.502827
## iter 150 value 8.500825
## iter 160 value 8.215580
## iter 170 value 6.823146
## iter 180 value 3.234493
## iter 190 value 3.023041
## iter 200 value 2.988640
## iter 210 value 2.987395
## iter 220 value 2.683942
## iter 230 value 1.136718
## iter 240 value 0.205300
## iter 250 value 0.185225
## iter 260 value 0.178992
## iter 270 value 0.176673
## iter 280 value 0.176006
## iter 290 value 0.169032
## iter 300 value 0.166292
## iter 310 value 0.156022
## iter 320 value 0.137950
## iter 330 value 0.133154
## iter 340 value 0.127891
## iter 350 value 0.124212
## iter 360 value 0.121195
## iter 370 value 0.120134
## iter 380 value 0.119846
## iter 390 value 0.119110
## iter 400 value 0.118988
## iter 410 value 0.118853
## iter 420 value 0.118739
## iter 430 value 0.118663
## iter 440 value 0.118636
## iter 450 value 0.118611
## iter 460 value 0.118476
## iter 470 value 0.117249
## iter 480 value 0.116200
## iter 490 value 0.115810
## iter 500 value 0.115668
## final  value 0.115668 
## stopped after 500 iterations
## # weights:  51
## initial  value 33.617829 
## iter  10 value 24.289708
## iter  20 value 20.178308
## iter  30 value 17.517383
## iter  40 value 16.879550
## iter  50 value 16.553820
## iter  60 value 16.076680
## iter  70 value 16.071426
## iter  80 value 16.069032
## iter  90 value 15.961898
## iter 100 value 15.572871
## iter 110 value 15.554963
## iter 120 value 13.012659
## iter 130 value 9.193416
## iter 140 value 9.043517
## iter 150 value 9.034106
## iter 160 value 9.029812
## iter 170 value 9.025658
## iter 180 value 9.024717
## iter 190 value 9.022874
## iter 200 value 9.021269
## iter 210 value 8.723658
## iter 220 value 4.960583
## iter 230 value 4.830205
## iter 240 value 4.827606
## iter 250 value 4.795529
## iter 260 value 3.227059
## iter 270 value 3.087056
## iter 280 value 3.085151
## iter 290 value 3.084298
## iter 300 value 3.082954
## iter 310 value 3.082445
## iter 320 value 3.081830
## iter 330 value 3.081508
## iter 340 value 3.081220
## iter 350 value 3.081022
## iter 360 value 3.078973
## iter 370 value 2.848734
## iter 380 value 2.777571
## iter 390 value 2.771553
## iter 400 value 2.739325
## iter 410 value 2.578443
## iter 420 value 2.572175
## iter 430 value 2.561356
## iter 440 value 2.428228
## iter 450 value 2.300792
## iter 460 value 2.043971
## iter 470 value 2.000057
## iter 480 value 1.991338
## iter 490 value 1.989051
## iter 500 value 1.987255
## final  value 1.987255 
## stopped after 500 iterations
## # weights:  61
## initial  value 31.340287 
## iter  10 value 22.707619
## iter  20 value 20.181126
## iter  30 value 20.122966
## iter  40 value 19.177928
## iter  50 value 19.152955
## iter  60 value 19.152145
## iter  70 value 19.151069
## iter  80 value 19.142139
## iter  90 value 18.849373
## iter 100 value 13.783746
## iter 110 value 13.511903
## iter 120 value 13.508477
## iter 130 value 13.507544
## iter 140 value 13.435472
## iter 150 value 13.335753
## iter 160 value 12.546755
## iter 170 value 11.201993
## iter 180 value 10.557429
## iter 190 value 10.524265
## iter 200 value 10.522845
## iter 210 value 10.520490
## iter 220 value 10.518274
## iter 230 value 10.227421
## iter 240 value 8.257900
## iter 250 value 7.392912
## iter 260 value 7.310545
## iter 270 value 7.307546
## iter 280 value 7.299389
## iter 290 value 3.540495
## iter 300 value 3.210617
## iter 310 value 3.160101
## iter 320 value 3.145681
## iter 330 value 3.132546
## iter 340 value 3.130552
## iter 350 value 3.126823
## iter 360 value 3.123847
## iter 370 value 3.120646
## iter 380 value 3.118858
## iter 390 value 3.115710
## iter 400 value 3.113297
## iter 410 value 3.108507
## iter 420 value 2.664567
## iter 430 value 0.617141
## iter 440 value 0.193136
## iter 450 value 0.171578
## iter 460 value 0.165468
## iter 470 value 0.163060
## iter 480 value 0.159242
## iter 490 value 0.155771
## iter 500 value 0.151884
## final  value 0.151884 
## stopped after 500 iterations
## # weights:  71
## initial  value 31.918252 
## iter  10 value 21.651041
## iter  20 value 18.721508
## iter  30 value 15.231800
## iter  40 value 13.255398
## iter  50 value 10.114821
## iter  60 value 9.681097
## iter  70 value 9.676707
## iter  80 value 9.331092
## iter  90 value 8.569375
## iter 100 value 7.518924
## iter 110 value 7.440875
## iter 120 value 7.437567
## iter 130 value 7.436209
## iter 140 value 7.434819
## iter 150 value 7.432230
## iter 160 value 7.430125
## iter 170 value 7.428690
## iter 180 value 7.428061
## iter 190 value 7.426400
## iter 200 value 7.425869
## iter 210 value 7.264508
## iter 220 value 7.258567
## iter 230 value 7.255026
## iter 240 value 7.122170
## iter 250 value 6.870293
## iter 260 value 6.738473
## iter 270 value 6.384482
## iter 280 value 6.157292
## iter 290 value 6.147667
## iter 300 value 6.144866
## iter 310 value 6.143773
## iter 320 value 6.143430
## iter 330 value 6.143339
## iter 340 value 6.142883
## iter 350 value 5.975521
## iter 360 value 5.813034
## iter 370 value 5.808423
## iter 380 value 4.919362
## iter 390 value 4.044098
## iter 400 value 3.982909
## iter 410 value 3.937408
## iter 420 value 2.404352
## iter 430 value 0.291891
## iter 440 value 0.211696
## iter 450 value 0.176621
## iter 460 value 0.171065
## iter 470 value 0.169035
## iter 480 value 0.166714
## iter 490 value 0.163044
## iter 500 value 0.159873
## final  value 0.159873 
## stopped after 500 iterations
## # weights:  81
## initial  value 30.628236 
## iter  10 value 22.228903
## iter  20 value 16.808776
## iter  30 value 16.054504
## iter  40 value 15.674767
## iter  50 value 14.944676
## iter  60 value 14.939474
## iter  70 value 14.934579
## iter  80 value 14.932893
## iter  90 value 14.931820
## iter 100 value 14.912739
## iter 110 value 14.326072
## iter 120 value 14.202754
## iter 130 value 14.171794
## iter 140 value 14.165924
## iter 150 value 14.165805
## iter 160 value 14.165225
## iter 170 value 14.053151
## iter 180 value 12.889715
## iter 190 value 12.658971
## iter 200 value 12.646710
## iter 210 value 12.633970
## iter 220 value 12.405837
## iter 230 value 12.386123
## iter 240 value 11.970267
## iter 250 value 10.234112
## iter 260 value 10.202746
## iter 270 value 9.484705
## iter 280 value 9.183280
## iter 290 value 9.178587
## iter 300 value 9.174090
## iter 310 value 8.490676
## iter 320 value 5.585047
## iter 330 value 2.084550
## iter 340 value 0.847898
## iter 350 value 0.311569
## iter 360 value 0.227405
## iter 370 value 0.198100
## iter 380 value 0.194732
## iter 390 value 0.187634
## iter 400 value 0.172594
## iter 410 value 0.162075
## iter 420 value 0.154290
## iter 430 value 0.149930
## iter 440 value 0.147988
## iter 450 value 0.147147
## iter 460 value 0.143189
## iter 470 value 0.122588
## iter 480 value 0.111714
## iter 490 value 0.106134
## iter 500 value 0.104670
## final  value 0.104670 
## stopped after 500 iterations
head(accuracyANN10,100)
#Function accuracy values per different samples
accuracyANN<-function(trials){
acc <- data.frame(i = integer(),Accuracy= integer())
for(i in 450:trials) {
# random sample
smp_size <- floor(0.80 * nrow(mydata2))



## set the seed to make the partition reproducible
set.seed(i)
train_ind <- sample(seq_len(nrow(mydata2)), size = smp_size)



trainC <- mydata2[train_ind, ]
testC <- mydata2[-train_ind, ]
modelANNC<-nnet(popularity~.,data=trainC,size = 3,decay = 0.0001,maxit = 500)
testC$pred_nnet<-predict(modelANNC,testC,type="class")
confmatC<-data.frame(Prediction=testC$pred_nnet,Actual=testC$popularity)
accuracy<-nrow(subset(confmatC,Actual==Prediction))/nrow(confmatC)
trial=i
attempt <- data.frame(Trial = trial, Accuracy = accuracy)
acc <- rbind(acc,attempt)
}



return(acc)
}
accuracyANN30<-accuracyANN(480)
## # weights:  31
## initial  value 29.173358 
## iter  10 value 29.065027
## iter  20 value 29.064997
## iter  30 value 28.749338
## iter  40 value 22.899072
## iter  50 value 22.872827
## iter  60 value 22.852533
## iter  70 value 20.637560
## iter  80 value 19.972234
## iter  90 value 19.916035
## iter 100 value 19.912728
## iter 110 value 19.909756
## iter 120 value 19.909137
## iter 130 value 19.907570
## iter 140 value 17.624796
## iter 150 value 17.347740
## iter 160 value 17.344126
## iter 170 value 17.343884
## iter 180 value 17.343776
## iter 190 value 17.343656
## iter 200 value 17.343211
## iter 210 value 16.187955
## iter 220 value 13.493963
## iter 230 value 12.129025
## iter 240 value 11.761751
## iter 250 value 11.340235
## iter 260 value 10.513398
## iter 270 value 9.512968
## iter 280 value 9.508763
## iter 290 value 9.507775
## iter 300 value 9.504706
## iter 310 value 9.502457
## iter 320 value 9.501573
## iter 330 value 9.500983
## iter 340 value 9.500602
## iter 350 value 9.500435
## iter 360 value 9.500280
## iter 370 value 9.500178
## iter 380 value 9.500169
## iter 390 value 9.500152
## final  value 9.500152 
## converged
## # weights:  31
## initial  value 39.769302 
## iter  10 value 26.905086
## iter  20 value 26.472317
## iter  30 value 26.471306
## iter  40 value 23.344477
## iter  50 value 23.325583
## iter  60 value 22.172889
## iter  70 value 22.170452
## iter  80 value 22.170142
## iter  90 value 22.169662
## iter 100 value 22.169543
## iter 110 value 22.169386
## iter 120 value 20.953974
## iter 130 value 20.951687
## iter 140 value 19.677626
## iter 150 value 19.663355
## iter 160 value 19.662894
## iter 170 value 19.662763
## iter 180 value 19.643598
## iter 190 value 11.733170
## iter 200 value 11.727811
## iter 210 value 11.726620
## iter 220 value 11.726353
## iter 230 value 11.726062
## iter 240 value 11.724568
## iter 250 value 8.795816
## iter 260 value 8.448775
## iter 270 value 8.439474
## iter 280 value 8.437442
## iter 290 value 8.095506
## iter 300 value 7.662121
## iter 310 value 7.655442
## iter 320 value 6.918048
## iter 330 value 5.895756
## iter 340 value 5.756137
## iter 350 value 5.752351
## iter 360 value 5.715430
## iter 370 value 5.490088
## iter 380 value 5.461789
## iter 390 value 5.258953
## iter 400 value 5.208022
## iter 410 value 5.199217
## iter 420 value 5.196833
## iter 430 value 5.194062
## iter 440 value 5.193411
## iter 450 value 5.191499
## iter 460 value 3.997695
## iter 470 value 2.865668
## iter 480 value 2.580778
## iter 490 value 2.393570
## iter 500 value 2.340395
## final  value 2.340395 
## stopped after 500 iterations
## # weights:  31
## initial  value 30.256906 
## iter  10 value 28.682386
## iter  20 value 21.913681
## iter  30 value 16.124142
## iter  40 value 15.036397
## iter  50 value 15.031620
## iter  60 value 15.030337
## iter  70 value 15.028284
## iter  80 value 14.691179
## iter  90 value 13.803299
## iter 100 value 13.677668
## iter 110 value 13.673468
## iter 120 value 13.672511
## iter 130 value 13.671959
## iter 140 value 13.671444
## iter 150 value 13.671250
## iter 160 value 13.671234
## iter 170 value 13.671213
## iter 180 value 13.671196
## iter 190 value 13.671167
## iter 200 value 13.671119
## final  value 13.671110 
## converged
## # weights:  31
## initial  value 38.063645 
## iter  10 value 22.346184
## iter  20 value 17.640715
## iter  30 value 17.331326
## iter  40 value 17.095366
## iter  50 value 17.090501
## iter  60 value 17.088715
## iter  70 value 17.086957
## iter  80 value 17.085121
## iter  90 value 17.083892
## iter 100 value 17.030188
## iter 110 value 16.085058
## iter 120 value 15.967358
## iter 130 value 15.963091
## iter 140 value 15.962178
## iter 150 value 15.420035
## iter 160 value 15.102653
## iter 170 value 13.545911
## iter 180 value 9.420306
## iter 190 value 6.975513
## iter 200 value 6.906543
## iter 210 value 6.897845
## iter 220 value 6.896331
## iter 230 value 6.895558
## iter 240 value 6.894188
## iter 250 value 6.893034
## iter 260 value 6.892741
## iter 270 value 6.892317
## iter 280 value 6.891534
## iter 290 value 6.891070
## iter 300 value 6.888537
## iter 310 value 6.888069
## iter 320 value 6.887818
## iter 330 value 6.886492
## iter 340 value 6.884465
## iter 350 value 6.883602
## iter 360 value 6.882848
## iter 370 value 6.882566
## iter 380 value 6.882350
## iter 390 value 6.882143
## iter 400 value 6.881956
## iter 410 value 6.865867
## iter 420 value 6.437336
## iter 430 value 5.748313
## iter 440 value 5.697114
## iter 450 value 5.695659
## iter 460 value 5.694982
## iter 470 value 5.694232
## iter 480 value 5.693922
## iter 490 value 5.693636
## iter 500 value 5.693416
## final  value 5.693416 
## stopped after 500 iterations
## # weights:  31
## initial  value 28.678200 
## iter  10 value 19.496766
## iter  20 value 14.563015
## iter  30 value 10.980941
## iter  40 value 10.419636
## iter  50 value 10.402799
## iter  60 value 10.400709
## iter  70 value 10.399974
## iter  80 value 10.399346
## iter  90 value 10.399047
## iter 100 value 10.398490
## iter 110 value 10.319122
## iter 120 value 10.027709
## iter 130 value 9.830450
## iter 140 value 9.804618
## iter 150 value 9.803541
## iter 160 value 9.803246
## iter 170 value 9.740393
## iter 180 value 6.614192
## iter 190 value 6.470356
## iter 200 value 6.466650
## iter 210 value 6.460559
## iter 220 value 6.456212
## iter 230 value 6.455179
## iter 240 value 6.455010
## iter 250 value 6.454122
## iter 260 value 6.453864
## iter 270 value 6.453363
## iter 280 value 6.452579
## iter 290 value 6.452371
## iter 300 value 6.452327
## iter 310 value 6.452250
## iter 320 value 6.452193
## iter 330 value 6.452120
## iter 340 value 6.452108
## final  value 6.452107 
## converged
## # weights:  31
## initial  value 29.653225 
## iter  10 value 25.726712
## iter  20 value 25.708908
## iter  30 value 25.708263
## iter  40 value 25.708127
## iter  50 value 24.887091
## iter  60 value 17.187569
## iter  70 value 12.181684
## iter  80 value 11.758354
## iter  90 value 11.674669
## iter 100 value 11.450839
## iter 110 value 11.322990
## iter 120 value 11.197998
## iter 130 value 11.190936
## iter 140 value 11.187014
## iter 150 value 11.186594
## iter 160 value 11.186470
## iter 170 value 11.186208
## iter 180 value 11.186136
## iter 190 value 11.186045
## iter 200 value 11.185877
## iter 210 value 11.165059
## iter 220 value 11.022575
## iter 230 value 10.594903
## iter 240 value 10.416566
## iter 250 value 10.045298
## iter 260 value 10.022489
## iter 270 value 9.981285
## iter 280 value 9.522742
## iter 290 value 9.308787
## iter 300 value 9.303066
## iter 310 value 9.047999
## iter 320 value 8.070987
## iter 330 value 7.034829
## iter 340 value 5.192296
## iter 350 value 1.707593
## iter 360 value 0.204915
## iter 370 value 0.131615
## iter 380 value 0.121092
## iter 390 value 0.116024
## iter 400 value 0.114599
## iter 410 value 0.114023
## iter 420 value 0.112878
## iter 430 value 0.112047
## iter 440 value 0.110084
## iter 450 value 0.107956
## iter 460 value 0.107323
## iter 470 value 0.107308
## iter 480 value 0.107245
## iter 490 value 0.107221
## iter 500 value 0.107211
## final  value 0.107211 
## stopped after 500 iterations
## # weights:  31
## initial  value 32.598518 
## iter  10 value 23.635588
## iter  20 value 20.301554
## iter  30 value 20.296665
## iter  40 value 20.296075
## iter  50 value 20.295673
## iter  60 value 15.894971
## iter  70 value 14.674715
## iter  80 value 11.194213
## iter  90 value 9.934766
## iter 100 value 9.894406
## iter 110 value 9.891676
## iter 120 value 9.891313
## iter 130 value 9.890532
## iter 140 value 9.890143
## iter 150 value 9.889911
## iter 160 value 9.889888
## iter 170 value 9.889878
## iter 180 value 9.889856
## final  value 9.889855 
## converged
## # weights:  31
## initial  value 32.532508 
## iter  10 value 20.934856
## iter  20 value 20.197693
## iter  30 value 19.823181
## iter  40 value 17.113843
## iter  50 value 17.051868
## iter  60 value 17.051737
## iter  70 value 17.051382
## iter  80 value 16.977031
## iter  90 value 14.937775
## iter 100 value 10.904062
## iter 110 value 5.809256
## iter 120 value 5.771751
## iter 130 value 5.761349
## iter 140 value 5.747245
## iter 150 value 5.668633
## iter 160 value 4.751631
## iter 170 value 1.788160
## iter 180 value 0.294491
## iter 190 value 0.122400
## iter 200 value 0.110041
## iter 210 value 0.107958
## iter 220 value 0.101621
## iter 230 value 0.099019
## iter 240 value 0.097910
## iter 250 value 0.097581
## iter 260 value 0.097070
## iter 270 value 0.096423
## iter 280 value 0.095941
## iter 290 value 0.095319
## iter 300 value 0.088160
## iter 310 value 0.083575
## iter 320 value 0.079965
## iter 330 value 0.077434
## iter 340 value 0.075583
## iter 350 value 0.075034
## iter 360 value 0.074445
## iter 370 value 0.073639
## iter 380 value 0.073297
## iter 390 value 0.072553
## iter 400 value 0.072232
## iter 410 value 0.072201
## iter 420 value 0.072131
## iter 430 value 0.072081
## iter 440 value 0.072046
## iter 450 value 0.072004
## iter 460 value 0.071914
## iter 470 value 0.070815
## iter 480 value 0.069534
## iter 490 value 0.069023
## iter 500 value 0.068196
## final  value 0.068196 
## stopped after 500 iterations
## # weights:  31
## initial  value 32.362059 
## iter  10 value 20.689072
## iter  20 value 18.045863
## iter  30 value 18.033932
## iter  40 value 18.033625
## iter  50 value 17.828551
## iter  60 value 13.634336
## iter  70 value 13.599553
## iter  80 value 12.963385
## iter  90 value 12.875547
## iter 100 value 12.842917
## iter 110 value 9.239405
## iter 120 value 7.380335
## iter 130 value 5.218558
## iter 140 value 5.129911
## iter 150 value 5.108502
## iter 160 value 5.105760
## iter 170 value 5.104897
## iter 180 value 5.103763
## iter 190 value 5.102510
## iter 200 value 5.101871
## iter 210 value 5.101090
## iter 220 value 5.100685
## iter 230 value 5.100402
## iter 240 value 5.100278
## iter 250 value 5.100217
## iter 260 value 5.099886
## iter 270 value 5.024391
## iter 280 value 4.628700
## iter 290 value 4.595584
## iter 300 value 4.594476
## iter 310 value 4.594003
## iter 320 value 4.593866
## iter 330 value 4.593757
## iter 340 value 4.593627
## iter 350 value 4.593498
## iter 360 value 4.593439
## iter 370 value 4.593396
## iter 380 value 4.593312
## iter 390 value 4.592796
## iter 400 value 4.452242
## iter 410 value 4.282318
## iter 420 value 4.281610
## iter 430 value 4.281293
## iter 440 value 4.280735
## iter 450 value 4.280355
## iter 460 value 4.280165
## iter 470 value 4.279937
## iter 480 value 4.231728
## iter 490 value 2.745946
## iter 500 value 0.762180
## final  value 0.762180 
## stopped after 500 iterations
## # weights:  31
## initial  value 29.139223 
## iter  10 value 23.258183
## iter  20 value 23.054317
## iter  30 value 22.520239
## iter  40 value 21.747789
## iter  50 value 20.526923
## iter  60 value 20.381047
## iter  70 value 20.378222
## iter  80 value 20.377722
## iter  90 value 20.376992
## iter 100 value 20.376387
## iter 110 value 20.376265
## iter 120 value 20.375852
## iter 130 value 18.756370
## iter 140 value 18.524301
## iter 150 value 18.515749
## iter 160 value 18.266584
## iter 170 value 18.265406
## iter 180 value 17.773999
## iter 190 value 16.851288
## iter 200 value 16.849516
## iter 210 value 16.849034
## iter 220 value 16.848613
## iter 230 value 16.825012
## iter 240 value 16.616641
## iter 250 value 16.583376
## iter 260 value 16.581702
## iter 270 value 16.580314
## iter 280 value 16.577678
## iter 290 value 16.575951
## iter 300 value 16.004184
## iter 310 value 16.000117
## iter 320 value 15.922014
## iter 330 value 15.695723
## iter 340 value 15.691731
## iter 350 value 15.085610
## iter 360 value 14.336339
## iter 370 value 14.328681
## iter 380 value 14.328229
## iter 390 value 14.327218
## iter 400 value 14.326578
## iter 410 value 14.326326
## iter 420 value 14.326255
## iter 430 value 14.326139
## iter 440 value 14.326021
## iter 450 value 14.325980
## iter 460 value 14.325907
## iter 470 value 14.325852
## iter 480 value 14.325822
## iter 490 value 14.325805
## iter 500 value 14.325795
## final  value 14.325795 
## stopped after 500 iterations
## # weights:  31
## initial  value 33.943818 
## iter  10 value 24.526319
## iter  20 value 24.432520
## iter  30 value 24.428044
## iter  40 value 24.426935
## iter  50 value 24.426093
## iter  60 value 24.423634
## iter  70 value 24.423000
## iter  80 value 24.422417
## iter  90 value 24.421250
## iter 100 value 18.716098
## iter 110 value 17.926073
## iter 120 value 17.850911
## iter 130 value 16.529386
## iter 140 value 11.700683
## iter 150 value 9.692455
## iter 160 value 9.604251
## iter 170 value 9.601418
## iter 180 value 9.599939
## iter 190 value 9.599501
## iter 200 value 9.598378
## iter 210 value 9.598113
## iter 220 value 9.597791
## iter 230 value 9.597511
## iter 240 value 9.597299
## iter 250 value 9.597226
## iter 260 value 9.597176
## iter 270 value 9.597151
## iter 280 value 9.597124
## iter 290 value 9.597083
## iter 300 value 9.597066
## iter 310 value 9.597037
## iter 320 value 9.597015
## final  value 9.597014 
## converged
## # weights:  31
## initial  value 29.974040 
## iter  10 value 25.652063
## iter  20 value 20.249248
## iter  30 value 18.857884
## iter  40 value 17.878822
## iter  50 value 16.461486
## iter  60 value 15.836021
## iter  70 value 14.769872
## iter  80 value 14.665235
## iter  90 value 14.662621
## iter 100 value 14.660422
## iter 110 value 14.660027
## iter 120 value 14.659893
## iter 130 value 14.659853
## iter 140 value 14.659808
## iter 150 value 14.659743
## iter 160 value 14.659627
## iter 170 value 14.659515
## iter 180 value 14.630107
## iter 190 value 12.878347
## iter 200 value 10.002166
## iter 210 value 9.102541
## iter 220 value 8.411624
## iter 230 value 8.407331
## iter 240 value 8.404945
## iter 250 value 8.402020
## iter 260 value 8.397870
## iter 270 value 8.395648
## iter 280 value 8.394500
## iter 290 value 8.393957
## iter 300 value 8.393098
## iter 310 value 8.392380
## iter 320 value 8.392023
## iter 330 value 8.391533
## iter 340 value 8.391367
## iter 350 value 8.391294
## iter 360 value 8.391144
## iter 370 value 8.390946
## iter 380 value 8.390271
## iter 390 value 8.196527
## iter 400 value 7.483139
## iter 410 value 7.199733
## iter 420 value 7.191178
## iter 430 value 7.190692
## iter 440 value 7.190145
## iter 450 value 7.189491
## iter 460 value 7.189289
## iter 470 value 7.189061
## iter 480 value 7.188848
## iter 490 value 7.188624
## iter 500 value 6.734889
## final  value 6.734889 
## stopped after 500 iterations
## # weights:  31
## initial  value 28.823175 
## iter  10 value 23.049124
## iter  20 value 23.003091
## iter  30 value 23.001696
## iter  40 value 22.434780
## iter  50 value 21.820200
## iter  60 value 20.487331
## iter  70 value 20.443150
## iter  80 value 20.441837
## iter  90 value 20.441571
## iter 100 value 20.441431
## iter 110 value 20.441370
## iter 120 value 20.441190
## iter 130 value 20.390362
## iter 140 value 17.097131
## iter 150 value 16.892957
## iter 160 value 16.839451
## iter 170 value 14.222507
## iter 180 value 4.866667
## iter 190 value 2.581108
## iter 200 value 2.409108
## iter 210 value 2.401451
## iter 220 value 2.150027
## iter 230 value 0.280922
## iter 240 value 0.170488
## iter 250 value 0.156852
## iter 260 value 0.152805
## iter 270 value 0.149217
## iter 280 value 0.136006
## iter 290 value 0.134014
## iter 300 value 0.131155
## iter 310 value 0.130322
## iter 320 value 0.128269
## iter 330 value 0.121249
## iter 340 value 0.116457
## iter 350 value 0.115207
## iter 360 value 0.114972
## iter 370 value 0.114884
## iter 380 value 0.114718
## iter 390 value 0.114063
## iter 400 value 0.113368
## iter 410 value 0.113112
## iter 420 value 0.112789
## iter 430 value 0.112531
## iter 440 value 0.112185
## iter 450 value 0.112040
## iter 460 value 0.111806
## iter 470 value 0.111742
## iter 480 value 0.111691
## iter 490 value 0.109939
## iter 500 value 0.106482
## final  value 0.106482 
## stopped after 500 iterations
## # weights:  31
## initial  value 37.296187 
## iter  10 value 28.682321
## iter  20 value 28.664405
## iter  30 value 23.142762
## iter  40 value 21.300792
## iter  50 value 21.293740
## iter  60 value 20.015377
## iter  70 value 20.013147
## iter  80 value 20.011236
## iter  90 value 19.691572
## iter 100 value 17.722264
## iter 110 value 15.273149
## iter 120 value 15.164804
## iter 130 value 13.643757
## iter 140 value 13.098994
## iter 150 value 13.048073
## iter 160 value 13.046342
## iter 170 value 13.045775
## iter 180 value 12.539404
## iter 190 value 11.696778
## iter 200 value 11.010295
## iter 210 value 10.739704
## iter 220 value 10.736627
## iter 230 value 10.735900
## iter 240 value 10.735538
## iter 250 value 10.734742
## iter 260 value 10.734336
## iter 270 value 10.734109
## iter 280 value 10.734017
## iter 290 value 10.733854
## iter 300 value 10.733596
## iter 310 value 7.245466
## iter 320 value 5.391596
## iter 330 value 5.355922
## iter 340 value 5.348696
## iter 350 value 5.346706
## iter 360 value 5.345134
## iter 370 value 5.343050
## iter 380 value 5.342155
## iter 390 value 5.340189
## iter 400 value 5.337572
## iter 410 value 5.336542
## iter 420 value 5.335151
## iter 430 value 5.333353
## iter 440 value 5.332135
## iter 450 value 5.331782
## iter 460 value 5.331624
## iter 470 value 5.331312
## iter 480 value 5.330966
## iter 490 value 5.330728
## iter 500 value 5.330498
## final  value 5.330498 
## stopped after 500 iterations
## # weights:  31
## initial  value 29.396439 
## iter  10 value 27.777043
## iter  20 value 27.059466
## iter  30 value 27.038741
## iter  40 value 27.034119
## iter  50 value 27.032570
## iter  60 value 24.342880
## iter  70 value 21.693619
## iter  80 value 20.636945
## iter  90 value 17.065500
## iter 100 value 16.466417
## iter 110 value 16.432929
## iter 120 value 16.432631
## iter 130 value 16.431874
## iter 140 value 16.425879
## iter 150 value 15.362802
## iter 160 value 15.129811
## iter 170 value 14.248182
## iter 180 value 12.868196
## iter 190 value 12.330551
## iter 200 value 12.322131
## iter 210 value 12.320085
## iter 220 value 12.319573
## iter 230 value 12.319326
## final  value 12.319297 
## converged
## # weights:  31
## initial  value 30.287327 
## iter  10 value 21.952448
## iter  20 value 20.482517
## iter  30 value 20.457602
## iter  40 value 20.456747
## iter  50 value 20.455769
## iter  60 value 18.926390
## iter  70 value 18.921335
## iter  80 value 17.225286
## iter  90 value 17.161303
## iter 100 value 17.160804
## iter 110 value 17.157151
## iter 120 value 15.770294
## iter 130 value 15.640767
## iter 140 value 15.639232
## iter 150 value 15.634816
## iter 160 value 15.633248
## iter 170 value 15.632643
## iter 180 value 15.632301
## iter 190 value 15.632160
## iter 200 value 15.631882
## iter 210 value 15.630823
## iter 220 value 15.258413
## iter 230 value 14.556146
## iter 240 value 14.334635
## iter 250 value 12.993911
## iter 260 value 12.244078
## iter 270 value 12.020389
## iter 280 value 12.016531
## iter 290 value 12.014635
## iter 300 value 12.014276
## iter 310 value 12.013863
## iter 320 value 12.013635
## iter 330 value 12.013519
## iter 340 value 12.013313
## iter 350 value 12.012984
## iter 360 value 12.012867
## iter 370 value 12.012740
## final  value 12.012687 
## converged
## # weights:  31
## initial  value 28.858033 
## iter  10 value 22.233971
## iter  20 value 19.277605
## iter  30 value 17.890121
## iter  40 value 16.901449
## iter  50 value 15.835526
## iter  60 value 15.273673
## iter  70 value 14.658690
## iter  80 value 14.627491
## iter  90 value 14.603139
## iter 100 value 14.600110
## iter 110 value 14.598510
## iter 120 value 14.597901
## iter 130 value 14.597548
## iter 140 value 14.597275
## iter 150 value 14.597008
## iter 160 value 14.596905
## iter 170 value 14.596873
## iter 180 value 14.596850
## iter 190 value 14.596812
## iter 200 value 14.596788
## iter 210 value 14.596762
## iter 220 value 14.596740
## iter 230 value 14.564516
## iter 240 value 14.560800
## iter 250 value 14.560092
## iter 260 value 14.559956
## iter 270 value 13.387468
## iter 280 value 13.238220
## iter 290 value 13.195970
## iter 300 value 13.164377
## iter 310 value 13.141764
## iter 320 value 13.140160
## iter 330 value 13.139510
## iter 340 value 13.139099
## iter 350 value 13.138981
## iter 360 value 13.138904
## iter 370 value 13.138888
## iter 380 value 13.138871
## iter 390 value 13.138860
## iter 400 value 13.138821
## iter 410 value 13.138803
## iter 420 value 13.138793
## final  value 13.138791 
## converged
## # weights:  31
## initial  value 28.517980 
## iter  10 value 26.947310
## iter  20 value 26.934880
## iter  30 value 26.932461
## iter  40 value 23.526995
## iter  50 value 17.787155
## iter  60 value 13.685580
## iter  70 value 11.792820
## iter  80 value 11.658136
## iter  90 value 11.653443
## iter 100 value 11.652395
## iter 110 value 11.648286
## iter 120 value 11.646718
## iter 130 value 11.646392
## iter 140 value 11.645815
## iter 150 value 11.368546
## iter 160 value 11.352212
## iter 170 value 11.350825
## iter 180 value 10.942102
## iter 190 value 10.489968
## iter 200 value 10.414526
## iter 210 value 10.403934
## iter 220 value 10.403093
## iter 230 value 10.401564
## iter 240 value 10.401417
## iter 250 value 10.401274
## iter 260 value 10.401183
## iter 270 value 10.400973
## iter 280 value 10.400864
## iter 290 value 10.400817
## final  value 10.400737 
## converged
## # weights:  31
## initial  value 32.631111 
## iter  10 value 29.065119
## iter  20 value 29.065059
## iter  30 value 29.063629
## iter  40 value 28.933381
## iter  50 value 22.108684
## iter  60 value 22.095215
## iter  70 value 20.989469
## iter  80 value 15.007545
## iter  90 value 13.531253
## iter 100 value 13.497981
## iter 110 value 13.490983
## iter 120 value 13.488850
## iter 130 value 12.976746
## iter 140 value 12.958472
## iter 150 value 12.956283
## iter 160 value 12.913991
## iter 170 value 10.008092
## iter 180 value 3.233007
## iter 190 value 3.161071
## iter 200 value 0.256498
## iter 210 value 0.171944
## iter 220 value 0.163822
## iter 230 value 0.156028
## iter 240 value 0.145274
## iter 250 value 0.132089
## iter 260 value 0.125703
## iter 270 value 0.122058
## iter 280 value 0.119093
## iter 290 value 0.115522
## iter 300 value 0.111716
## iter 310 value 0.107220
## iter 320 value 0.103796
## iter 330 value 0.102411
## iter 340 value 0.101389
## iter 350 value 0.100593
## iter 360 value 0.099500
## iter 370 value 0.098687
## iter 380 value 0.097517
## iter 390 value 0.097322
## iter 400 value 0.097108
## iter 410 value 0.097005
## iter 420 value 0.096958
## iter 430 value 0.096888
## iter 440 value 0.096866
## iter 450 value 0.096855
## iter 460 value 0.096850
## iter 470 value 0.096846
## iter 480 value 0.096842
## iter 490 value 0.096839
## iter 500 value 0.096836
## final  value 0.096836 
## stopped after 500 iterations
## # weights:  31
## initial  value 27.128749 
## iter  10 value 16.827019
## iter  20 value 14.451869
## iter  30 value 14.287784
## iter  40 value 14.284008
## iter  50 value 14.283258
## iter  60 value 14.282666
## iter  70 value 14.266922
## iter  80 value 13.862304
## iter  90 value 13.446459
## iter 100 value 13.257914
## iter 110 value 13.204013
## iter 120 value 13.199328
## iter 130 value 13.010729
## iter 140 value 12.928329
## iter 150 value 12.928072
## iter 160 value 12.927052
## iter 170 value 12.926865
## iter 180 value 12.638880
## iter 190 value 12.631914
## iter 200 value 12.630132
## iter 210 value 12.629415
## iter 220 value 12.629303
## iter 230 value 12.629236
## iter 240 value 12.629180
## iter 250 value 12.629161
## iter 260 value 12.629148
## iter 270 value 12.629116
## iter 280 value 12.248255
## iter 290 value 9.687621
## iter 300 value 9.590864
## iter 310 value 9.589620
## iter 320 value 9.588296
## iter 330 value 9.587409
## iter 340 value 9.586657
## iter 350 value 9.586460
## iter 360 value 9.586382
## iter 370 value 9.586282
## iter 380 value 9.586101
## iter 390 value 9.586050
## iter 400 value 9.585973
## final  value 9.585965 
## converged
## # weights:  31
## initial  value 30.564961 
## iter  10 value 27.225357
## iter  20 value 19.341900
## iter  30 value 12.862822
## iter  40 value 12.118378
## iter  50 value 10.850944
## iter  60 value 10.493539
## iter  70 value 9.818338
## iter  80 value 9.537715
## iter  90 value 8.435517
## iter 100 value 8.415214
## iter 110 value 8.414309
## iter 120 value 8.412643
## iter 130 value 8.411986
## iter 140 value 8.411128
## iter 150 value 8.410363
## iter 160 value 8.410307
## iter 170 value 8.410248
## iter 180 value 8.410227
## iter 190 value 8.410210
## iter 200 value 8.405357
## iter 210 value 7.285126
## iter 220 value 3.514547
## iter 230 value 3.464645
## iter 240 value 3.458777
## iter 250 value 3.453128
## iter 260 value 3.449269
## iter 270 value 3.446566
## iter 280 value 3.441630
## iter 290 value 3.437365
## iter 300 value 3.427052
## iter 310 value 3.420698
## iter 320 value 3.419657
## iter 330 value 3.417283
## iter 340 value 3.416724
## iter 350 value 3.415509
## iter 360 value 3.415112
## iter 370 value 3.414915
## iter 380 value 3.414746
## iter 390 value 3.414695
## iter 400 value 3.414673
## iter 410 value 3.414637
## iter 420 value 3.414619
## iter 430 value 3.414605
## iter 440 value 3.414600
## iter 450 value 3.414593
## final  value 3.414590 
## converged
## # weights:  31
## initial  value 28.754765 
## iter  10 value 25.031231
## iter  20 value 22.404327
## iter  30 value 22.120913
## iter  40 value 21.705397
## iter  50 value 21.677593
## iter  60 value 21.674810
## iter  70 value 21.533189
## iter  80 value 21.162200
## iter  90 value 20.739684
## iter 100 value 20.735628
## iter 110 value 20.643206
## iter 120 value 20.252851
## iter 130 value 20.242016
## iter 140 value 20.240716
## iter 150 value 20.240311
## iter 160 value 20.239204
## iter 170 value 20.238767
## iter 180 value 20.238288
## iter 190 value 20.237838
## iter 200 value 20.237424
## iter 210 value 20.237131
## iter 220 value 19.318542
## iter 230 value 19.294245
## iter 240 value 18.321803
## iter 250 value 15.181281
## iter 260 value 12.370832
## iter 270 value 12.124357
## iter 280 value 12.122808
## iter 290 value 12.121573
## iter 300 value 12.118956
## iter 310 value 12.118294
## iter 320 value 12.117677
## iter 330 value 12.117275
## iter 340 value 12.116065
## iter 350 value 12.115831
## iter 360 value 12.115654
## iter 370 value 12.115322
## iter 380 value 12.114986
## iter 390 value 12.113629
## iter 400 value 12.106621
## iter 410 value 12.029814
## iter 420 value 11.917502
## iter 430 value 11.860804
## iter 440 value 10.291715
## iter 450 value 9.089169
## iter 460 value 8.030621
## iter 470 value 6.253899
## iter 480 value 5.102790
## iter 490 value 4.845526
## iter 500 value 4.717793
## final  value 4.717793 
## stopped after 500 iterations
## # weights:  31
## initial  value 28.549136 
## iter  10 value 23.196299
## iter  20 value 20.775055
## iter  30 value 19.018203
## iter  40 value 18.852637
## iter  50 value 18.577417
## iter  60 value 16.511428
## iter  70 value 15.070155
## iter  80 value 14.961361
## iter  90 value 14.957831
## iter 100 value 14.957458
## iter 110 value 14.957232
## iter 120 value 14.956638
## iter 130 value 14.956245
## iter 140 value 14.956013
## iter 150 value 14.955918
## iter 160 value 14.437022
## iter 170 value 8.225997
## iter 180 value 7.746454
## iter 190 value 7.586084
## iter 200 value 7.493498
## iter 210 value 7.491698
## iter 220 value 7.490987
## iter 230 value 7.487868
## iter 240 value 7.213984
## iter 250 value 6.840376
## iter 260 value 6.704971
## iter 270 value 5.918392
## iter 280 value 4.544410
## iter 290 value 3.842739
## iter 300 value 2.880175
## iter 310 value 2.641812
## iter 320 value 2.599767
## iter 330 value 2.593873
## iter 340 value 2.591516
## iter 350 value 2.589854
## iter 360 value 2.589138
## iter 370 value 2.588494
## iter 380 value 2.587104
## iter 390 value 2.586491
## iter 400 value 2.585549
## iter 410 value 2.585252
## iter 410 value 2.585252
## final  value 2.585252 
## converged
## # weights:  31
## initial  value 33.720765 
## iter  10 value 17.771298
## iter  20 value 17.164375
## iter  30 value 17.162188
## iter  40 value 17.161982
## iter  50 value 17.161770
## final  value 17.161577 
## converged
## # weights:  31
## initial  value 37.879078 
## iter  10 value 21.787680
## iter  20 value 20.371743
## iter  30 value 20.370939
## iter  40 value 20.369112
## iter  50 value 20.365196
## iter  60 value 20.365010
## iter  70 value 20.364691
## iter  80 value 20.364569
## iter  90 value 20.364402
## iter 100 value 20.364118
## iter 110 value 20.364019
## iter 120 value 20.363985
## final  value 20.363964 
## converged
## # weights:  31
## initial  value 28.587684 
## iter  10 value 22.416292
## iter  20 value 20.340633
## iter  30 value 18.419489
## iter  40 value 18.402728
## iter  50 value 18.394349
## iter  60 value 18.389901
## iter  70 value 18.389125
## iter  80 value 18.388297
## iter  90 value 18.110627
## iter 100 value 17.657222
## iter 110 value 17.291022
## iter 120 value 17.258083
## iter 130 value 17.247397
## iter 140 value 15.160222
## iter 150 value 10.965238
## iter 160 value 9.334166
## iter 170 value 9.259222
## iter 180 value 9.254859
## iter 190 value 9.251797
## iter 200 value 9.249420
## iter 210 value 9.245245
## iter 220 value 9.243686
## iter 230 value 9.240143
## iter 240 value 9.237948
## iter 250 value 9.235488
## iter 260 value 9.234313
## iter 270 value 9.233808
## iter 280 value 9.232281
## iter 290 value 9.230764
## iter 300 value 9.226503
## iter 310 value 8.739076
## iter 320 value 8.152399
## iter 330 value 8.136966
## iter 340 value 8.135613
## iter 350 value 8.134910
## iter 360 value 8.134442
## iter 370 value 8.134364
## iter 380 value 8.134322
## iter 390 value 8.134191
## iter 400 value 8.134002
## iter 410 value 8.133845
## iter 420 value 7.445128
## iter 430 value 5.503879
## iter 440 value 5.326070
## iter 450 value 5.325153
## iter 460 value 5.324311
## iter 470 value 5.323993
## iter 480 value 5.323721
## iter 490 value 5.323411
## iter 500 value 5.323124
## final  value 5.323124 
## stopped after 500 iterations
## # weights:  31
## initial  value 30.426204 
## iter  10 value 19.363091
## iter  20 value 19.151524
## iter  30 value 19.149008
## iter  40 value 19.148286
## iter  50 value 19.147958
## iter  60 value 19.147122
## iter  70 value 17.285024
## iter  80 value 15.326716
## iter  90 value 15.297351
## iter 100 value 15.295904
## iter 110 value 15.295528
## iter 120 value 15.293973
## iter 130 value 15.293804
## iter 140 value 15.293514
## iter 150 value 15.293443
## iter 160 value 15.293375
## iter 170 value 15.293236
## iter 180 value 15.293174
## iter 190 value 15.293103
## iter 200 value 15.293066
## iter 210 value 15.293051
## iter 220 value 15.293040
## iter 230 value 15.293029
## iter 240 value 15.293013
## final  value 15.293013 
## converged
## # weights:  31
## initial  value 29.362485 
## iter  10 value 23.930685
## iter  20 value 19.910267
## iter  30 value 16.933245
## iter  40 value 15.432189
## iter  50 value 11.579232
## iter  60 value 8.015249
## iter  70 value 4.147298
## iter  80 value 3.578932
## iter  90 value 3.558801
## iter 100 value 3.557475
## iter 110 value 3.555786
## iter 120 value 3.554013
## iter 130 value 3.552560
## iter 140 value 3.551939
## iter 150 value 3.551346
## iter 160 value 3.549210
## iter 170 value 3.548246
## iter 180 value 3.502526
## iter 190 value 3.469232
## iter 200 value 3.462886
## iter 210 value 3.460657
## iter 220 value 3.441136
## iter 230 value 0.326417
## iter 240 value 0.247504
## iter 250 value 0.200514
## iter 260 value 0.185842
## iter 270 value 0.182340
## iter 280 value 0.181352
## iter 290 value 0.179060
## iter 300 value 0.177076
## iter 310 value 0.176310
## iter 320 value 0.175978
## iter 330 value 0.175338
## iter 340 value 0.174415
## iter 350 value 0.173589
## iter 360 value 0.173399
## iter 370 value 0.173366
## iter 380 value 0.173330
## iter 390 value 0.173251
## iter 400 value 0.173209
## iter 410 value 0.173197
## iter 420 value 0.173178
## iter 430 value 0.173161
## iter 440 value 0.173143
## iter 450 value 0.173062
## iter 460 value 0.172956
## iter 470 value 0.172922
## iter 480 value 0.172906
## iter 490 value 0.172897
## iter 500 value 0.172892
## final  value 0.172892 
## stopped after 500 iterations
## # weights:  31
## initial  value 30.382550 
## iter  10 value 25.877088
## iter  20 value 16.986234
## iter  30 value 15.705578
## iter  40 value 15.703279
## iter  50 value 15.702575
## iter  60 value 15.701672
## iter  70 value 15.700730
## iter  80 value 15.699988
## iter  90 value 15.699827
## iter 100 value 15.699527
## iter 110 value 15.699030
## iter 120 value 15.698870
## iter 130 value 15.698805
## iter 140 value 15.622398
## iter 150 value 13.096258
## iter 160 value 13.086641
## iter 170 value 13.086170
## iter 180 value 13.085847
## iter 190 value 13.085665
## iter 200 value 13.085593
## iter 210 value 13.085453
## iter 220 value 13.085328
## iter 230 value 13.085246
## iter 240 value 13.084975
## iter 250 value 13.084958
## iter 260 value 13.079253
## iter 270 value 11.211118
## iter 280 value 11.152104
## iter 290 value 11.144298
## iter 300 value 11.143701
## iter 310 value 11.142711
## iter 320 value 11.141586
## iter 330 value 11.141275
## iter 340 value 11.141213
## iter 350 value 11.141180
## iter 360 value 11.141141
## final  value 11.141119 
## converged
## # weights:  31
## initial  value 28.804852 
## iter  10 value 21.920223
## iter  20 value 20.450303
## iter  30 value 18.329607
## iter  40 value 18.304860
## iter  50 value 18.303659
## iter  60 value 18.303384
## iter  70 value 18.302561
## iter  80 value 17.343395
## iter  90 value 15.688980
## iter 100 value 14.309705
## iter 110 value 13.544871
## iter 120 value 13.488438
## iter 130 value 13.487801
## iter 140 value 13.487341
## iter 150 value 13.369567
## iter 160 value 9.674135
## iter 170 value 9.346756
## iter 180 value 9.340969
## iter 190 value 9.333116
## iter 200 value 9.319163
## iter 210 value 9.315800
## iter 220 value 9.314938
## iter 230 value 9.313062
## iter 240 value 9.311294
## iter 250 value 9.310167
## iter 260 value 9.309548
## iter 270 value 9.298179
## iter 280 value 9.250902
## iter 290 value 9.248682
## iter 300 value 9.185605
## iter 310 value 9.120011
## iter 320 value 9.114979
## iter 330 value 9.044765
## iter 340 value 8.928872
## iter 350 value 8.735615
## iter 360 value 8.696988
## iter 370 value 8.696176
## iter 380 value 8.695455
## iter 390 value 8.694546
## iter 400 value 8.694113
## iter 410 value 8.693819
## iter 420 value 8.693658
## iter 430 value 8.693528
## iter 440 value 8.693343
## iter 450 value 8.693203
## iter 460 value 8.693140
## iter 470 value 8.693085
## iter 480 value 8.693059
## iter 490 value 8.693045
## iter 500 value 8.693020
## final  value 8.693020 
## stopped after 500 iterations
## # weights:  31
## initial  value 31.618705 
## iter  10 value 27.328765
## iter  20 value 23.136182
## iter  30 value 18.148821
## iter  40 value 14.788108
## iter  50 value 14.604788
## iter  60 value 14.227352
## iter  70 value 13.152320
## iter  80 value 12.850129
## iter  90 value 12.848037
## iter 100 value 12.770729
## iter 110 value 12.605021
## iter 120 value 12.374118
## iter 130 value 12.368608
## iter 140 value 12.366921
## iter 150 value 12.365577
## iter 160 value 12.363785
## iter 170 value 12.363413
## iter 180 value 12.162944
## iter 190 value 12.095353
## iter 200 value 12.094738
## iter 210 value 12.094549
## iter 220 value 12.094442
## iter 230 value 12.094318
## iter 240 value 12.094256
## iter 250 value 12.094223
## iter 260 value 12.094185
## iter 270 value 12.094151
## iter 280 value 12.094124
## iter 290 value 12.094095
## final  value 12.094095 
## converged
head(accuracyANN30,31)
#Function accuracy values per different samples
accuracyNB<-function(trials){
acc <- data.frame(i = integer(),Accuracy= integer())
for(i in 450:trials) {
# random sample
smp_size <- floor(0.80 * nrow(mydata2))



## set the seed to make the partition reproducible
set.seed(i)
train_ind <- sample(seq_len(nrow(mydata2)), size = smp_size)



trainC <- mydata2[train_ind, ]
testC <- mydata2[-train_ind, ]
NaivemodelC<-naiveBayes(popularity~.,data=trainC, laplace=1)
laplace_prediction1C<-predict(NaivemodelC,testC,type="class")
confumatNaiveC<-data.frame(Actual=testC$popularity,Prediction=laplace_prediction1C)
accuracy<-nrow(subset(confumatNaiveC,Actual==Prediction))/nrow(confumatNaiveC)
trial=i
attempt <- data.frame(Trial = trial, Accuracy = accuracy)
acc <- rbind(acc,attempt)
}



return(acc)
}
accuracyNB30<-accuracyNB(480)
head(accuracyNB30,31)
#Function accuracy values per different samples
accuracyRF<-function(trials){
acc <- data.frame(i = integer(),Accuracy= integer())
for(i in 450:trials) {
# random sample
smp_size <- floor(0.80 * nrow(mydata2))



## set the seed to make the partition reproducible
set.seed(i)
train_ind <- sample(seq_len(nrow(mydata2)), size = smp_size)



trainC <- mydata2[train_ind, ]
testC <- mydata2[-train_ind, ]
RFmodelC<-rpart(popularity~.,data=trainC, method="class")
RF_prediction1C<-predict(RFmodelC,testC,type="class")
confumatRF<-data.frame(Actual=testC$popularity,Prediction=RF_prediction1C)
accuracy<-nrow(subset(confumatRF,Actual==Prediction))/nrow(confumatRF)
trial=i
attempt <- data.frame(Trial = trial, Accuracy = accuracy)
acc <- rbind(acc,attempt)
}



return(acc)
}
accuracyRF30<-accuracyRF(480)
head(accuracyRF30,31)
#Function accuracy values per different samples
accuracyRF1<-function(trials){
acc <- data.frame(i = integer(),Accuracy= integer())
for(i in 450:trials) {
# random sample
smp_size <- floor(0.80 * nrow(mydata2))



## set the seed to make the partition reproducible
set.seed(i)
train_ind <- sample(seq_len(nrow(mydata2)), size = smp_size)



trainC <- mydata2[train_ind, ]
testC <- mydata2[-train_ind, ]
RFmodelC<-randomForest(popularity~.,data=trainC, method="class")
RF_prediction1C2<-predict(RFmodelC,testC,type="class")
confumatRF<-data.frame(Actual=testC$popularity,Prediction=RF_prediction1C2)
accuracy<-nrow(subset(confumatRF,Actual==Prediction))/nrow(confumatRF)
trial=i
attempt <- data.frame(Trial = trial, Accuracy = accuracy)
acc <- rbind(acc,attempt)
}



return(acc)
}
accuracyRF130<-accuracyRF1(480)
head(accuracyRF130,31)
library("dplyr")
## 
## Attaching package: 'dplyr'
## The following object is masked from 'package:xgboost':
## 
##     slice
## The following object is masked from 'package:randomForest':
## 
##     combine
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
#Putting all the accuracy values together
accuracyANN30$model<-"ANN"
accuracyNB30$model<-"Naive Bayes"
accuracyRF30$model<-"Class. & Reg. Trees"
accuracyRF130$model<-"Random Forest"
#accuracyGLM30$model<-"Logistic Reg."
bestAccuracy<-rbind(accuracyANN30,accuracyRF30,accuracyRF130,accuracyNB30)
#accuracyGLM30)
byModel<-group_by(bestAccuracy,model)
byModelAvg<-summarize(byModel,Avg=mean(Accuracy))
byModelAvg
p<-ggplot(byModelAvg, aes(model,Avg,fill=model))+geom_bar(position="dodge",stat="identity") + geom_text(aes(label = round(Avg,digits=2)),size = 3, hjust = 0.2, vjust = 2, position = "stack")+labs(title = "Comparison Avg Accuracy per Model (31 Trials)",x="Model", y="Avg Accuracy")+theme(axis.text.x = element_text(angle = 45,size=8))
p

#install.packages("svglite")
library(svglite)
ggsave(file="Class spotify2.svg") 
## Saving 7 x 5 in image
#Running Anova for the variables using previous match
AnovaModel<-aov(bestAccuracy$Accuracy~bestAccuracy$model)
summary(AnovaModel)
##                     Df Sum Sq Mean Sq F value   Pr(>F)    
## bestAccuracy$model   3  1.037  0.3457   33.83 6.46e-16 ***
## Residuals          120  1.226  0.0102                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TUKEY <- TukeyHSD(AnovaModel)
TUKEY
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = bestAccuracy$Accuracy ~ bestAccuracy$model)
## 
## $`bestAccuracy$model`
##                                          diff         lwr        upr     p adj
## Class. & Reg. Trees-ANN            0.18181818  0.11491868 0.24871769 0.0000000
## Naive Bayes-ANN                    0.23167155  0.16477205 0.29857106 0.0000000
## Random Forest-ANN                  0.20821114  0.14131164 0.27511065 0.0000000
## Naive Bayes-Class. & Reg. Trees    0.04985337 -0.01704613 0.11675288 0.2163997
## Random Forest-Class. & Reg. Trees  0.02639296 -0.04050654 0.09329247 0.7334683
## Random Forest-Naive Bayes         -0.02346041 -0.09035992 0.04343910 0.7976023
TUKEY <- TukeyHSD(x=AnovaModel, conf.level=0.95)
TUKEY
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = bestAccuracy$Accuracy ~ bestAccuracy$model)
## 
## $`bestAccuracy$model`
##                                          diff         lwr        upr     p adj
## Class. & Reg. Trees-ANN            0.18181818  0.11491868 0.24871769 0.0000000
## Naive Bayes-ANN                    0.23167155  0.16477205 0.29857106 0.0000000
## Random Forest-ANN                  0.20821114  0.14131164 0.27511065 0.0000000
## Naive Bayes-Class. & Reg. Trees    0.04985337 -0.01704613 0.11675288 0.2163997
## Random Forest-Class. & Reg. Trees  0.02639296 -0.04050654 0.09329247 0.7334683
## Random Forest-Naive Bayes         -0.02346041 -0.09035992 0.04343910 0.7976023
RFmodelC<-randomForest(popularity~.,data=train1, method="class")
varImpPlot(RFmodelC)

Our model indicates that hip hop is the most important feature in this classification problem.