HMA_Con_Model_20240308

Introduction

• This file is my working code for modelling conflict in HMA. Analysis began on March 3, 2024.

• Update on April, 8, 2024: Analysis of the data at the administrative boundary 1 level by country (data: hma_df_provinces_20240318.csv)

##Set working directory
##r code is the same level as data
##data has the following subfolders - conflict, IPUMS, NASA HiMAT, population, Suicide, and Water Basins

setwd("~/Desktop/University of Utah PhD /Research/r_code")

## Load applicable libraries

library(mapview) #mapping package
library(raster) #raster data manipulation (Climate Data)
library(RColorBrewer) #color palettes for visualization
library(sf) #simple features for spatial data
library(tmap) #mapping package
library(viridis) #color palette for visualization
library(ncdf4) #working with netCDF files (Climate Data)
library(leaflet) #basemaps for mapview
library(ggplot2) #better figures
library(ggcorrplot) #Load the correlation plot package
library(plotly) #interactive figures
library(maps) #mapping 
library(kableExtra) #creating better tables and outputs
library(dplyr) #count and data functions
library(reshape2) ## Package used to reformat data - wide to long
library(tidyverse) ##Formatting dataframes, merge, and join
library(stargazer) ##Formatting model outputs to tables
library(pscl) ##Used to calculate pseudo r^2 values for log regression models (poisson)
library(janitor) ##Used to count/provide summaries for dataframes
library(jtools) ##Used to produce aesthetically pleasing model output tables
library(huxtable) ##Used in conjunction with jtools to export model outputs
library(flextable) ##Needed to knit. linked to the janitor library
library(geomerge) ##Merges conducts a series of spatial joins to combine geospatial data ##Andrew Linke recommendation!!
library(tidyr) ##reshaping data formats long/wide
library(lubridate) ##Helps dealing with date/time ##Needed for geomerge
library(kohonen) #self organizing maps
library(ggpubr) ##publication ready tables
library(stats) ##Stats functions
library(lme4) ##linear mixed effects model

Data

## Read in the overall model data frame
## this was assembled in excel
## use version 2

hma.con.df = read.csv("../data/conflict/hma_initial_model_df_v3_20240304.csv")


## Check
str(hma.con.df)

## 'data.frame':    12 obs. of  170 variables:
##  $ country       : chr  "Afghanistan" "Bangladesh" "Bhutan" "China" ...
##  $ gdp.2010      : num  1.56e+10 1.15e+11 1.55e+09 6.09e+12 1.68e+12 ...
##  $ gdp.2011      : num  1.82e+10 1.29e+11 1.78e+09 7.55e+12 1.82e+12 ...
##  $ gdp.2012      : num  2.02e+10 1.33e+11 1.78e+09 8.53e+12 1.83e+12 ...
##  $ gdp.2013      : num  2.06e+10 1.50e+11 1.76e+09 9.57e+12 1.86e+12 ...
##  $ gdp.2014      : num  2.06e+10 1.73e+11 1.91e+09 1.05e+13 2.04e+12 ...
##  $ gdp.2015      : num  2.00e+10 1.95e+11 2.00e+09 1.11e+13 2.10e+12 ...
##  $ gdp.2016      : num  1.80e+10 2.65e+11 2.16e+09 1.12e+13 2.29e+12 ...
##  $ gdp.2017      : num  1.89e+10 2.94e+11 2.45e+09 1.23e+13 2.65e+12 ...
##  $ gdp.2018      : num  1.84e+10 3.21e+11 2.45e+09 1.39e+13 2.70e+12 ...
##  $ gdp.2019      : num  1.89e+10 3.51e+11 2.54e+09 1.43e+13 2.84e+12 ...
##  $ gdp.2020      : num  2.01e+10 3.74e+11 2.33e+09 1.47e+13 2.67e+12 ...
##  $ gdp.2021      : num  1.46e+10 4.16e+11 2.54e+09 1.78e+13 3.15e+12 ...
##  $ gdp.2022      : num  9.04e+09 4.60e+11 2.75e+09 1.80e+13 3.39e+12 ...
##  $ pop.2010      : int  28189672 148391139 705516 1337705000 1240613620 5447900 49390988 27161567 194454498 7621779 ...
##  $ pop.2011      : int  29249157 150211005 713331 1345035000 1257621191 5514600 49794522 27266399 198602738 7784819 ...
##  $ pop.2012      : int  30466479 152090649 721145 1354190000 1274487215 5607200 50218185 27330694 202205861 7956382 ...
##  $ pop.2013      : int  31541209 154030139 728889 1363240000 1291132063 5719600 50648334 27381555 205337562 8136610 ...
##  $ pop.2014      : int  32716210 155961299 736357 1371860000 1307246509 5835500 51072436 27462106 208251628 8326348 ...
##  $ pop.2015      : int  33753499 157830000 743274 1379860000 1322866505 5956900 51483949 27610325 210969298 8524063 ...
##  $ pop.2016      : int  34636207 159784568 749761 1387790000 1338636340 6079500 51892349 27861186 213524840 8725318 ...
##  $ pop.2017      : int  35643418 161793964 756121 1396215000 1354195680 6198200 52288341 28183426 216379655 8925525 ...
##  $ pop.2018      : int  36686784 163683958 762096 1402760000 1369003306 6322800 52666014 28506712 219731479 9128132 ...
##  $ pop.2019      : int  37769499 165516222 767459 1407745000 1383112050 6456200 53040212 28832496 223293280 9337003 ...
##  $ pop.2020      : int  38972230 167420951 772506 1411100000 1396387127 6579900 53423198 29348627 227196741 9543207 ...
##  $ pop.2021      : int  40099462 169356251 777486 1412360000 1407563842 6691800 53798084 30034989 231402117 9750064 ...
##  $ pop.2022      : int  41128771 171186372 782455 1412175000 1417173173 6803300 54179306 30547580 235824862 9952787 ...
##  $ temp.2010     : num  1.613 0.768 1.202 0.968 1.129 ...
##  $ temp.2011     : num  1.397 0.144 0.534 0.792 0.365 ...
##  $ temp.2012     : num  0.223 0.235 0.512 0.626 0.516 0.353 0.915 0.402 0.263 -0.032 ...
##  $ temp.2013     : num  1.281 0.23 0.742 1.073 0.451 ...
##  $ temp.2014     : num  0.456 0.482 0.86 1.062 0.53 ...
##  $ temp.2015     : num  1.093 0.722 1.068 1.297 0.711 ...
##  $ temp.2016     : num  1.55 1.34 1.49 1.32 1.09 ...
##  $ temp.2017     : num  1.54 1.124 1.457 1.573 0.966 ...
##  $ temp.2018     : num  1.544 0.881 1.346 1.361 0.874 ...
##  $ temp.2019     : num  0.91 1.136 1.329 1.422 0.802 ...
##  $ temp.2020     : num  0.498 0.898 1.09 1.62 0.52 ...
##  $ temp.2021     : num  1.327 1.3 1.707 1.701 0.733 ...
##  $ temp.2022     : num  2.01 1.22 1.52 1.91 0.79 ...
##  $ cd.2010       : int  4 6 0 21 17 1 2 2 7 2 ...
##  $ cd.2011       : int  4 5 0 13 12 0 1 6 1 1 ...
##  $ cd.2012       : int  10 5 0 22 9 2 1 3 5 2 ...
##  $ cd.2013       : int  5 3 0 34 11 0 2 2 2 1 ...
##  $ cd.2014       : int  3 4 0 33 16 1 2 6 3 2 ...
##  $ cd.2015       : int  5 7 0 31 19 0 6 2 7 3 ...
##  $ cd.2016       : int  4 3 0 30 15 0 5 3 8 1 ...
##  $ cd.2017       : int  5 5 0 26 18 1 2 3 5 2 ...
##  $ cd.2018       : int  5 4 0 20 23 0 4 2 2 1 ...
##  $ cd.2019       : int  7 6 0 13 12 0 3 2 10 1 ...
##  $ cd.2020       : int  7 2 0 11 11 0 2 1 6 1 ...
##  $ cd.2021       : int  4 2 1 12 16 1 1 4 6 2 ...
##  $ cd.2022       : int  6 2 0 7 7 1 0 4 4 0 ...
##  $ ge.2010       : num  -1.48 -0.75 0.6 0.08 0.03 -0.66 -1.62 -0.89 -0.77 -0.93 ...
##  $ ge.2011       : num  -1.48 -0.77 0.68 0.07 0.02 -0.64 -1.6 -0.92 -0.83 -0.96 ...
##  $ ge.2012       : num  -1.38 -0.81 0.55 0 -0.16 -0.65 -1.48 -0.99 -0.78 -0.93 ...
##  $ ge.2013       : num  -1.4 -0.8 0.43 -0.02 -0.16 -0.65 -1.51 -0.93 -0.79 -1.07 ...
##  $ ge.2014       : num  -1.36 -0.77 0.3 0.35 -0.23 -0.87 -1.3 -0.86 -0.76 -0.79 ...
##  $ ge.2015       : num  -1.35 -0.73 0.45 0.44 0.11 -0.92 -1.26 -1.07 -0.67 -0.86 ...
##  $ ge.2016       : num  -1.25 -0.68 0.56 0.38 0.09 -0.91 -0.99 -0.83 -0.65 -1.04 ...
##  $ ge.2017       : num  -1.36 -0.73 0.62 0.44 0.07 -0.71 -1.07 -0.89 -0.6 -1.13 ...
##  $ ge.2018       : num  -1.48 -0.74 0.4 0.52 0.3 -0.61 -1.08 -0.9 -0.63 -1.11 ...
##  $ ge.2019       : num  -1.5 -0.73 0.35 0.56 0.16 -0.69 -1.17 -1.05 -0.68 -1.06 ...
##  $ ge.2020       : num  -1.59 -0.76 0.45 0.68 0.41 -0.53 -1.02 -0.94 -0.54 -0.71 ...
##  $ ge.2021       : num  -1.63 -0.63 0.8 0.84 0.28 -0.73 -1.41 -0.87 -0.4 -0.59 ...
##  $ ge.2022       : num  -1.44 -0.74 0.51 0.36 0.08 -0.71 -1.29 -0.93 -0.68 -0.93 ...
##  $ con.2010      : int  10727 2613 3 2479 17768 358 214 533 5562 31 ...
##  $ con.2011      : int  10727 2319 3 2479 17768 358 532 339 3731 31 ...
##  $ con.2012      : int  10727 1847 3 2479 17768 358 800 536 6975 31 ...
##  $ con.2013      : int  10727 2740 3 2479 17768 358 810 684 5923 31 ...
##  $ con.2014      : int  10727 1123 3 2479 17768 358 898 250 4203 31 ...
##  $ con.2015      : int  10727 1915 3 2479 17768 358 1174 753 4904 31 ...
##  $ con.2016      : int  10727 823 3 2479 13365 358 1107 391 4468 31 ...
##  $ con.2017      : int  13363 572 3 2479 13893 358 1099 616 4750 31 ...
##  $ con.2018      : int  14135 1206 3 3477 18887 194 1111 1986 6613 29 ...
##  $ con.2019      : int  13908 1716 3 3641 24005 284 1818 3248 7692 40 ...
##  $ con.2020      : int  10339 1522 3 2400 18122 341 1501 3226 8779 28 ...
##  $ con.2021      : int  9739 2581 4 1860 17940 568 16259 3303 7900 23 ...
##  $ con.2022      : int  2880 2304 2 1019 18167 402 15510 2986 8084 33 ...
##  $ cpt.2010      : num  -1.65 -1.05 0.94 -0.57 -0.46 -1.18 -1.67 -0.7 -1.09 -1.3 ...
##  $ cpt.2011      : num  -1.6 -1.1 0.85 -0.51 -0.54 -1.23 -1.59 -0.79 -1.08 -1.23 ...
##  $ cpt.2012      : num  -1.43 -0.86 0.95 -0.44 -0.51 -1.15 -1.07 -0.81 -1.07 -1.28 ...
##  $ cpt.2013      : num  -1.45 -0.89 0.91 -0.36 -0.52 -1.16 -1.01 -0.69 -0.96 -1.29 ...
##  $ cpt.2014      : num  -1.36 -0.89 1.31 -0.34 -0.46 -1.13 -0.88 -0.59 -0.84 -1.13 ...
##  $ cpt.2015      : num  -1.35 -0.84 0.99 -0.3 -0.41 -1.18 -0.85 -0.6 -0.83 -1.15 ...
##  $ cpt.2016      : num  -1.54 -0.89 1.09 -0.27 -0.34 -1.1 -0.64 -0.83 -0.9 -1.16 ...
##  $ cpt.2017      : num  -1.53 -0.86 1.53 -0.29 -0.29 -1.08 -0.59 -0.78 -0.8 -1.35 ...
##  $ cpt.2018      : num  -1.5 -0.93 1.59 -0.29 -0.23 -0.96 -0.61 -0.69 -0.8 -1.43 ...
##  $ cpt.2019      : num  -1.42 -1.02 1.57 -0.31 -0.3 -0.96 -0.65 -0.69 -0.88 -1.35 ...
##  $ cpt.2020      : num  -1.49 -1 1.62 -0.07 -0.29 -1.12 -0.68 -0.6 -0.86 -1.34 ...
##  $ cpt.2021      : num  -1.15 -0.99 1.51 0.03 -0.32 -1.15 -1.05 -0.56 -0.81 -1.35 ...
##  $ cpt.2022      : num  -1.18 -1.08 1.51 0.02 -0.32 -1.23 -1.15 -0.53 -0.8 -1.43 ...
##  $ rol.2010      : num  -1.87 -0.8 0.16 -0.47 -0.04 -1.27 -1.55 -0.96 -0.74 -1.21 ...
##  $ rol.2011      : num  -1.92 -0.73 0.21 -0.45 -0.09 -1.2 -1.44 -0.89 -0.91 -1.23 ...
##  $ rol.2012      : num  -1.65 -0.94 0.26 -0.55 -0.06 -1.13 -1.36 -0.74 -0.88 -1.21 ...
##  $ rol.2013      : num  -1.61 -0.87 0.32 -0.53 -0.05 -1.11 -1.24 -0.72 -0.86 -1.26 ...
##  $ rol.2014      : num  -1.44 -0.78 0.42 -0.4 -0.07 -0.94 -1.19 -0.65 -0.75 -1.01 ...
##  $ rol.2015      : num  -1.52 -0.77 0.53 -0.41 -0.07 -1.01 -1.26 -0.69 -0.78 -1.07 ...
##  $ rol.2016      : num  -1.52 -0.67 0.51 -0.32 -0.06 -1.04 -0.9 -0.81 -0.82 -1.17 ...
##   [list output truncated]

## Load the data frame with the provinces

##HMA province dataframe
hma.con.prov = read.csv("../data/conflict/hma_df_provinces_20240318.csv")

##Check
str(hma.con.prov)

## 'data.frame':    195 obs. of  145 variables:
##  $ country     : chr  "AFG" "AFG" "AFG" "AFG" ...
##  $ adm1        : chr  "Badakhshan" "Badghis" "Baghlan" "Balkh" ...
##  $ pop.2022    : num  1031700 747800 1258587 2286648 398469 ...
##  $ pop.2021    : num  888742 643219 1082537 1966788 342728 ...
##  $ pop.2020    : num  765594 553264 931112 1691671 294784 ...
##  $ pop.2019    : num  715202 516353 868979 1578783 275113 ...
##  $ pop.2018    : num  600919 546275 795518 1575995 275447 ...
##  $ pop.2017    : num  1186460 618083 1142146 1667964 557900 ...
##  $ pop.2016    : num  1166333 607812 1117998 1632091 548484 ...
##  $ pop.2015    : num  1139796 593826 1092249 1594494 535852 ...
##  $ pop.2014    : num  1117072 581941 1069192 1555764 525200 ...
##  $ pop.2013    : num  1100882 573714 1050830 1519228 517490 ...
##  $ pop.2012    : num  1086179 567174 1035306 1483034 511717 ...
##  $ pop.2011    : num  1064227 554834 1012767 1450774 500586 ...
##  $ pop.2010    : num  1042514 542990 991091 1420042 489884 ...
##  $ temp.2022   : num  2.74 13.22 10.66 17.24 5.41 ...
##  $ temp.2021   : num  2.3 13.24 10.28 16.85 5.09 ...
##  $ temp.2020   : num  1.24 11.63 8.97 15.42 3.69 ...
##  $ temp.2019   : num  1.73 12.6 9.54 16.31 4.32 ...
##  $ temp.2018   : num  2.25 12.84 10.25 16.67 5.03 ...
##  $ temp.2017   : num  1.85 12.44 9.8 16.14 4.56 ...
##  $ temp.2016   : num  2.24 12.92 10.09 16.64 4.89 ...
##  $ temp.2015   : num  1.85 12.53 9.56 16.14 4.3 ...
##  $ temp.2014   : num  1.51 11.89 9.36 15.77 4.11 ...
##  $ temp.2013   : num  2.12 12.79 9.79 16.36 4.54 ...
##  $ temp.2012   : num  1.04 11.75 8.87 15.37 3.58 ...
##  $ temp.2011   : num  1.77 11.99 9.55 15.84 4.25 ...
##  $ temp.2010   : num  1.93 12.97 9.77 16.39 4.56 ...
##  $ precip.2022 : num  52 27.3 43.3 25 33.1 ...
##  $ precip.2021 : num  35 21 32.1 15.1 26.9 ...
##  $ precip.2020 : num  61.8 35.5 59.9 25.4 42 ...
##  $ precip.2019 : num  61 37.3 55.3 28.4 39.1 ...
##  $ precip.2018 : num  44.4 27 42 17.2 33.3 ...
##  $ precip.2017 : num  53.5 29.7 43.5 16.8 31.7 ...
##  $ precip.2016 : num  65.2 29.8 59.6 24.6 45.4 ...
##  $ precip.2015 : num  69.2 34.5 64.6 26.7 44.5 ...
##  $ precip.2014 : num  48.8 27.9 44.7 25.4 36.1 ...
##  $ precip.2013 : num  60.6 25.9 59.7 22 44.1 ...
##  $ precip.2012 : num  59.2 33.3 60.7 29 48.4 ...
##  $ precip.2011 : num  53.7 27.7 45.1 17.7 32.7 ...
##  $ precip.2010 : num  59.3 27 44.2 17.9 33.1 ...
##  $ nlights.2022: logi  NA NA NA NA NA NA ...
##  $ nlights.2021: logi  NA NA NA NA NA NA ...
##  $ nlights.2020: num  0.00162 0.00199 0.02234 0.09353 0.00134 ...
##  $ nlights.2019: num  0.00153 0.00145 0.02183 0.08373 0.0017 ...
##  $ nlights.2018: num  0.0014 0.00114 0.02304 0.08366 0.00179 ...
##  $ nlights.2017: num  0.00167 0.00129 0.02179 0.09394 0.002 ...
##  $ nlights.2016: num  0.001066 0.000732 0.015652 0.09074 0.000976 ...
##  $ nlights.2015: num  0.001193 0.000828 0.015422 0.088452 0.001231 ...
##  $ nlights.2014: num  0.00143 0.0011 0.01562 0.09985 0.00083 ...
##  $ nlights.2013: num  0.001199 0.000955 0.015705 0.094981 0.000982 ...
##  $ nlights.2012: num  0.000922 0.000801 0.013412 0.080119 0.001079 ...
##  $ nlights.2011: logi  NA NA NA NA NA NA ...
##  $ nlights.2010: logi  NA NA NA NA NA NA ...
##  $ ge.2010     : num  -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 ...
##  $ ge.2011     : num  -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 ...
##  $ ge.2012     : num  -1.38 -1.38 -1.38 -1.38 -1.38 -1.38 -1.38 -1.38 -1.38 -1.38 ...
##  $ ge.2013     : num  -1.4 -1.4 -1.4 -1.4 -1.4 -1.4 -1.4 -1.4 -1.4 -1.4 ...
##  $ ge.2014     : num  -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 ...
##  $ ge.2015     : num  -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 ...
##  $ ge.2016     : num  -1.25 -1.25 -1.25 -1.25 -1.25 -1.25 -1.25 -1.25 -1.25 -1.25 ...
##  $ ge.2017     : num  -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 ...
##  $ ge.2018     : num  -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 -1.48 ...
##  $ ge.2019     : num  -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 ...
##  $ ge.2020     : num  -1.59 -1.59 -1.59 -1.59 -1.59 -1.59 -1.59 -1.59 -1.59 -1.59 ...
##  $ ge.2021     : num  -1.63 -1.63 -1.63 -1.63 -1.63 -1.63 -1.63 -1.63 -1.63 -1.63 ...
##  $ ge.2022     : num  -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 ...
##  $ cpt.2010    : num  -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 ...
##  $ cpt.2011    : num  -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 -1.6 ...
##  $ cpt.2012    : num  -1.43 -1.43 -1.43 -1.43 -1.43 -1.43 -1.43 -1.43 -1.43 -1.43 ...
##  $ cpt.2013    : num  -1.45 -1.45 -1.45 -1.45 -1.45 -1.45 -1.45 -1.45 -1.45 -1.45 ...
##  $ cpt.2014    : num  -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 -1.36 ...
##  $ cpt.2015    : num  -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 -1.35 ...
##  $ cpt.2016    : num  -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 ...
##  $ cpt.2017    : num  -1.53 -1.53 -1.53 -1.53 -1.53 -1.53 -1.53 -1.53 -1.53 -1.53 ...
##  $ cpt.2018    : num  -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -1.5 ...
##  $ cpt.2019    : num  -1.42 -1.42 -1.42 -1.42 -1.42 -1.42 -1.42 -1.42 -1.42 -1.42 ...
##  $ cpt.2020    : num  -1.49 -1.49 -1.49 -1.49 -1.49 -1.49 -1.49 -1.49 -1.49 -1.49 ...
##  $ cpt.2021    : num  -1.15 -1.15 -1.15 -1.15 -1.15 -1.15 -1.15 -1.15 -1.15 -1.15 ...
##  $ cpt.2022    : num  -1.18 -1.18 -1.18 -1.18 -1.18 -1.18 -1.18 -1.18 -1.18 -1.18 ...
##  $ rol.2010    : num  -1.87 -1.87 -1.87 -1.87 -1.87 -1.87 -1.87 -1.87 -1.87 -1.87 ...
##  $ rol.2011    : num  -1.92 -1.92 -1.92 -1.92 -1.92 -1.92 -1.92 -1.92 -1.92 -1.92 ...
##  $ rol.2012    : num  -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 -1.65 ...
##  $ rol.2013    : num  -1.61 -1.61 -1.61 -1.61 -1.61 -1.61 -1.61 -1.61 -1.61 -1.61 ...
##  $ rol.2014    : num  -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 -1.44 ...
##  $ rol.2015    : num  -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 ...
##  $ rol.2016    : num  -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 ...
##  $ rol.2017    : num  -1.58 -1.58 -1.58 -1.58 -1.58 -1.58 -1.58 -1.58 -1.58 -1.58 ...
##  $ rol.2018    : num  -1.69 -1.69 -1.69 -1.69 -1.69 -1.69 -1.69 -1.69 -1.69 -1.69 ...
##  $ rol.2019    : num  -1.74 -1.74 -1.74 -1.74 -1.74 -1.74 -1.74 -1.74 -1.74 -1.74 ...
##  $ rol.2020    : num  -1.83 -1.83 -1.83 -1.83 -1.83 -1.83 -1.83 -1.83 -1.83 -1.83 ...
##  $ rol.2021    : num  -1.88 -1.88 -1.88 -1.88 -1.88 -1.88 -1.88 -1.88 -1.88 -1.88 ...
##  $ rol.2022    : num  -1.66 -1.66 -1.66 -1.66 -1.66 -1.66 -1.66 -1.66 -1.66 -1.66 ...
##  $ rq.2010     : num  -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 -1.52 ...
##  $ rq.2011     : num  -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 -1.54 ...
##  $ rq.2012     : num  -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 ...
##  $ rq.2013     : num  -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 -1.19 ...
##  $ rq.2014     : num  -1.12 -1.12 -1.12 -1.12 -1.12 -1.12 -1.12 -1.12 -1.12 -1.12 ...
##  $ rq.2015     : num  -1.02 -1.02 -1.02 -1.02 -1.02 -1.02 -1.02 -1.02 -1.02 -1.02 ...
##   [list output truncated]

Wide to Long Dataframe Pivot

## Tidy up the dataframe
## pivot from wide to long



## Pivot Longer

hma.con.df.long = hma.con.df %>% 
  pivot_longer(
    cols = -c(country),
    names_sep = "\\.",
    names_to = c(".value", "year")
  )


## Check
head(hma.con.df.long)

country	year	gdp	pop	temp	cd	ge	con	cpt	rol	rq	polstab	voice	urbanpop	waterwith
Afghanistan	2010	1.56e+10	28189672	1.61	4	-1.48	10727	-1.65	-1.87	-1.52	-2.58	-1.4	23.7	43
Afghanistan	2011	1.82e+10	29249157	1.4	4	-1.48	10727	-1.6	-1.92	-1.54	-2.5	-1.34	23.9	43
Afghanistan	2012	2.02e+10	30466479	0.223	10	-1.38	10727	-1.43	-1.65	-1.19	-2.42	-1.27	24.2	43
Afghanistan	2013	2.06e+10	31541209	1.28	5	-1.4	10727	-1.45	-1.61	-1.19	-2.52	-1.24	24.4	43
Afghanistan	2014	2.06e+10	32716210	0.456	3	-1.36	10727	-1.36	-1.44	-1.12	-2.41	-1.14	24.6	43
Afghanistan	2015	2e+10	33753499	1.09	5	-1.35	10727	-1.35	-1.52	-1.02	-2.56	-1.12	24.8	43

## Tidy up the dataframe
## pivot from wide to long



## Pivot Longer

hma.con.prov.long = hma.con.prov %>% 
  pivot_longer(
    cols = -c(country, adm1),
    names_sep = "\\.",
    names_to = c(".value", "year")
  )


## Check
head(hma.con.prov.long)

country	adm1	year	pop	temp	precip	nlights	ge	cpt	rol	rq	polstab	voice	con
AFG	Badakhshan	2022	1.03e+06	2.74	52		-1.44	-1.18	-1.66	-1.27	-2.55	-1.75	129
AFG	Badakhshan	2021	8.89e+05	2.3	35		-1.63	-1.15	-1.88	-1.31	-2.52	-1.57	250
AFG	Badakhshan	2020	7.66e+05	1.24	61.8	0.00162	-1.59	-1.49	-1.83	-1.39	-2.7	-1.08	250
AFG	Badakhshan	2019	7.15e+05	1.73	61	0.00153	-1.5	-1.42	-1.74	-1.11	-2.65	-1.01	200
AFG	Badakhshan	2018	6.01e+05	2.25	44.4	0.0014	-1.48	-1.5	-1.69	-1.14	-2.75	-1.01	177
AFG	Badakhshan	2017	1.19e+06	1.85	53.5	0.00167	-1.36	-1.53	-1.58	-1.37	-2.79	-0.99	159

##write the long dataframe to csv
#write.csv(hma.con.df.long, file = "../data/conflict/hma_df_long_20240410.csv")

Standardize Conflict Variable

## Create an empty vector/column

hma.con.df.long[ ,'zscore'] = NA

## Check
view(hma.con.df.long)

## Testing the Z score transform
## in this case we are scaling the conflict counts to a z score
## This is done **by country**

hma.con.df.long[hma.con.df.long$country == 'Afghanistan', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Afghanistan', 'con'], center = TRUE, scale = TRUE)


## Check
hma.con.df.long[hma.con.df.long$country == 'Afghanistan', 'zscore']

zscore
-5.57e-05
-5.57e-05
-5.57e-05
-5.57e-05
-5.57e-05
-5.57e-05
-5.57e-05
0.955
1.23
1.15
-0.141
-0.358
-2.84

## Testing the Z score transform
## in this case we are scaling the conflict counts to a z score
## This is done **by country**

hma.con.df.long[hma.con.df.long$country == 'Bangladesh', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Bangladesh', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'Bhutan', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Bhutan', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'China', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'China', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'India', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'India', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'Kyrgyz Republic', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Kyrgyz Republic', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'Myanmar', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Myanmar', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'Nepal', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Nepal', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'Pakistan', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Pakistan', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'Tajikistan', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Tajikistan', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'Turkmenistan', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Turkmenistan', 'con'], center = TRUE, scale = TRUE)

hma.con.df.long[hma.con.df.long$country == 'Uzbekistan', 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == 'Uzbekistan', 'con'], center = TRUE, scale = TRUE)


## Check
view(hma.con.df.long)

##zcore the conflict variable by the entire dataframe instead of by country
##test

##The error jumped exponentially!!

#hma.con.df.long$zscore = scale(hma.con.df.long$con, center = TRUE, scale = TRUE)

#check
#head(hma.con.df.long$zscore)

##Define the function

#z.transform = function(x){
  #hma.con.df.long[hma.con.df.long$country == x, 'zscore'] = scale(hma.con.df.long[hma.con.df.long$country == x, 'con'], center = TRUE, scale = TRUE)

#}

#countries = c("Afghanistan", "Bhutan")

##use lappy to apply to the rest of the countries
#z.transform("Afghanistan")

##Check
#view(hma.con.df.long)

Impute Missing Values for the Provinces Dataframe

## Check the dataframe for NAs (should be nlights and conflict counts)

summary(hma.con.prov.long)

##    country              adm1               year                pop           
##  Length:2535        Length:2535        Length:2535        Min.   :     2570  
##  Class :character   Class :character   Class :character   1st Qu.:   602546  
##  Mode  :character   Mode  :character   Mode  :character   Median :  2193014  
##                                                           Mean   : 16281126  
##                                                           3rd Qu.: 20816373  
##                                                           Max.   :227005142  
##                                                                              
##       temp            precip           nlights              ge         
##  Min.   :-3.208   Min.   :  1.909   Min.   : 0.0000   Min.   :-1.6300  
##  1st Qu.: 9.758   1st Qu.: 37.107   1st Qu.: 0.0197   1st Qu.:-1.1100  
##  Median :15.930   Median : 75.865   Median : 0.1227   Median :-0.5900  
##  Mean   :16.035   Mean   : 95.111   Mean   : 1.2795   Mean   :-0.4618  
##  3rd Qu.:24.060   3rd Qu.:134.783   3rd Qu.: 0.4921   3rd Qu.: 0.2800  
##  Max.   :29.199   Max.   :378.518   Max.   :88.6181   Max.   : 0.8400  
##                                     NA's   :780                        
##       cpt              rol                rq             polstab       
##  Min.   :-1.670   Min.   :-1.9200   Min.   :-2.2400   Min.   :-2.8100  
##  1st Qu.:-1.190   1st Qu.:-1.3600   1st Qu.:-1.1600   1st Qu.:-1.4000  
##  Median :-0.680   Median :-0.6900   Median :-0.7400   Median :-0.8400  
##  Mean   :-0.626   Mean   :-0.6991   Mean   :-0.8062   Mean   :-0.9822  
##  3rd Qu.:-0.310   3rd Qu.:-0.0700   3rd Qu.:-0.3300   3rd Qu.:-0.4600  
##  Max.   : 1.620   Max.   : 0.6700   Max.   :-0.0500   Max.   : 1.1100  
##                                                                        
##      voice              con        
##  Min.   :-2.2600   Min.   :   0.0  
##  1st Qu.:-1.6200   1st Qu.:  13.0  
##  Median :-1.0100   Median :  79.0  
##  Mean   :-0.8589   Mean   : 266.1  
##  3rd Qu.:-0.0300   3rd Qu.: 307.0  
##  Max.   : 0.4400   Max.   :5564.0  
##                    NA's   :1164

## Confirmed - nlights and conflict

• Experiment using the package missForest to impute missing values

#Load missForest
library(missForest)

##Convert Characters into factors
hma.con.prov.long$country = as.factor(hma.con.prov.long$country)
hma.con.prov.long$adm1 = as.factor(hma.con.prov.long$adm1)
hma.con.prov.long$year = as.numeric(hma.con.prov.long$year)

##Convert to a dataframe for missForest
hma.con.prov.long = as.data.frame(hma.con.prov.long)

##Remove the adm1 levels for missForest to run correctly
hma.prov.ex = subset(hma.con.prov.long, select = -adm1)

##Impute using missForest
hma.prov.imp = missForest(hma.prov.ex)
          


##Check
summary(hma.prov.imp$ximp)

##     country         year           pop                 temp       
##  IND    :481   Min.   :2010   Min.   :     2570   Min.   :-3.208  
##  AFG    :442   1st Qu.:2013   1st Qu.:   602546   1st Qu.: 9.758  
##  CHN    :403   Median :2016   Median :  2193014   Median :15.930  
##  BTN    :260   Mean   :2016   Mean   : 16281126   Mean   :16.035  
##  MMR    :234   3rd Qu.:2019   3rd Qu.: 20816373   3rd Qu.:24.060  
##  UZB    :182   Max.   :2022   Max.   :227005142   Max.   :29.199  
##  (Other):533                                                      
##      precip           nlights               ge               cpt        
##  Min.   :  1.909   Min.   : 0.00000   Min.   :-1.6300   Min.   :-1.670  
##  1st Qu.: 37.107   1st Qu.: 0.03392   1st Qu.:-1.1100   1st Qu.:-1.190  
##  Median : 75.865   Median : 0.24419   Median :-0.5900   Median :-0.680  
##  Mean   : 95.111   Mean   : 1.40410   Mean   :-0.4618   Mean   :-0.626  
##  3rd Qu.:134.783   3rd Qu.: 0.82817   3rd Qu.: 0.2800   3rd Qu.:-0.310  
##  Max.   :378.518   Max.   :88.61808   Max.   : 0.8400   Max.   : 1.620  
##                                                                         
##       rol                rq             polstab            voice        
##  Min.   :-1.9200   Min.   :-2.2400   Min.   :-2.8100   Min.   :-2.2600  
##  1st Qu.:-1.3600   1st Qu.:-1.1600   1st Qu.:-1.4000   1st Qu.:-1.6200  
##  Median :-0.6900   Median :-0.7400   Median :-0.8400   Median :-1.0100  
##  Mean   :-0.6991   Mean   :-0.8062   Mean   :-0.9822   Mean   :-0.8589  
##  3rd Qu.:-0.0700   3rd Qu.:-0.3300   3rd Qu.:-0.4600   3rd Qu.:-0.0300  
##  Max.   : 0.6700   Max.   :-0.0500   Max.   : 1.1100   Max.   : 0.4400  
##                                                                         
##       con         
##  Min.   :   0.00  
##  1st Qu.:  24.02  
##  Median :  91.00  
##  Mean   : 229.30  
##  3rd Qu.: 283.00  
##  Max.   :5564.00  
## 

##Check the imputation to see how well it did
##nlights
plot(density(hma.prov.ex$nlights, na.rm=TRUE))
lines(density(hma.prov.imp$ximp$nlights), col = "red", lty = 2)

##conflict
plot(density(hma.prov.ex$con, na.rm=TRUE))
lines(density(hma.prov.imp$ximp$con), col = "red", lty = 2)

##Create a new dataframe with the imputed values
prov.df = hma.prov.imp$ximp

##Add back in the adm1
prov.df$adm1 = hma.con.prov.long$adm1

##relocate adm1 column after country
# prov.df %>% relocate(adm1, .after = country)

##Check
str(prov.df)

## 'data.frame':    2535 obs. of  14 variables:
##  $ country: Factor w/ 12 levels "AFG","BGD","BTN",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ year   : num  2022 2021 2020 2019 2018 ...
##  $ pop    : num  1031700 888742 765594 715202 600919 ...
##  $ temp   : num  2.74 2.3 1.24 1.73 2.25 ...
##  $ precip : num  52 35 61.8 61 44.4 ...
##  $ nlights: num  0.52352 0.52468 0.00162 0.00153 0.0014 ...
##  $ ge     : num  -1.44 -1.63 -1.59 -1.5 -1.48 -1.36 -1.25 -1.35 -1.36 -1.4 ...
##  $ cpt    : num  -1.18 -1.15 -1.49 -1.42 -1.5 -1.53 -1.54 -1.35 -1.36 -1.45 ...
##  $ rol    : num  -1.66 -1.88 -1.83 -1.74 -1.69 -1.58 -1.52 -1.52 -1.44 -1.61 ...
##  $ rq     : num  -1.27 -1.31 -1.39 -1.11 -1.14 -1.37 -1.34 -1.02 -1.12 -1.19 ...
##  $ polstab: num  -2.55 -2.52 -2.7 -2.65 -2.75 -2.79 -2.66 -2.56 -2.41 -2.52 ...
##  $ voice  : num  -1.75 -1.57 -1.08 -1.01 -1.01 -0.99 -1.04 -1.12 -1.14 -1.24 ...
##  $ con    : num  129 250 250 200 177 ...
##  $ adm1   : Factor w/ 194 levels "Ahal Region",..: 11 11 11 11 11 11 11 11 11 11 ...

##write the finished dataframe to a new csv
#write.csv(prov.df, file = "../davidleydet/Desktop/prov_df.csv")

Histogram Check

## population
h1 = prov.df %>% 
  gghistogram(x = "pop")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## temp
h2 = prov.df %>% 
  gghistogram(x = "temp")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## precip
h3 = prov.df %>% 
  gghistogram(x = "precip")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## nlights
h4 = prov.df %>% 
  gghistogram(x = "nlights")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## ge
h5 = prov.df %>% 
  gghistogram(x = "ge")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## cpt
h6 = prov.df %>% 
  gghistogram(x = "cpt")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## Visualize 
ggarrange(h1, h2, h3, h4, h5, h6)

## rol
h7 = prov.df %>% 
  gghistogram(x = "rol")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## rq
h8 = prov.df %>% 
  gghistogram(x = "rq")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## polstab
h9 = prov.df %>% 
  gghistogram(x = "polstab")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## voice
h10 = prov.df %>% 
  gghistogram(x = "voice")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## conflict
h11 = prov.df %>% 
  gghistogram(x = "con")

## Warning: Using `bins = 30` by default. Pick better value with the argument
## `bins`.

## Visualize 
ggarrange(h7, h8, h9, h10, h11)

Random Forest

Country Level Analysis

#load mlr3
library(mlr3)
library(ranger)
library(mlr3verse)
library(mlr3tuning)
library(paradox)

##Learner (Regression Outcome for conflict counts)
##Think about re-running it with a standardized incidence rate
##May need to log transform some variables

#Define the task
task_con = TaskRegr$new(id = "con",
                        backend = hma.con.df.long,
                        target = "zscore")

# Task details
task_con$col_roles

## $feature
##  [1] "cd"        "con"       "country"   "cpt"       "gdp"       "ge"       
##  [7] "polstab"   "pop"       "rol"       "rq"        "temp"      "urbanpop" 
## [13] "voice"     "waterwith" "year"     
## 
## $target
## [1] "zscore"
## 
## $name
## character(0)
## 
## $order
## character(0)
## 
## $stratum
## character(0)
## 
## $group
## character(0)
## 
## $weight
## character(0)

#if necessary exclude features here
## Exclude country***
task_con$col_roles$feature = setdiff(task_con$col_roles$feature,
                                          c("country", "con", "polstab"))


## Check
task_con$col_roles

## $feature
##  [1] "cd"        "cpt"       "gdp"       "ge"        "pop"       "rol"      
##  [7] "rq"        "temp"      "urbanpop"  "voice"     "waterwith" "year"     
## 
## $target
## [1] "zscore"
## 
## $name
## character(0)
## 
## $order
## character(0)
## 
## $stratum
## character(0)
## 
## $group
## character(0)
## 
## $weight
## character(0)

##Define the performance measure
##Regression Task
##additional measures can be found with msr()

measure = msr("regr.rmse")

#Define the learner
lrn_rf = lrn("regr.ranger",
             predict_type = "response",
             importance = "permutation")

## Define the resampling method
## 1st Run - Simple holdout 0.8
resamp_hout = rsmp("holdout",
                   ratio = 0.8)


## Instantiate the resampling method
resamp_hout$instantiate(task_con)

## Run the resampler/model
##con = conflict

c_rf = resample(task = task_con,
                 learner = lrn_rf,
                 resampling = resamp_hout,
                 store_models = TRUE)

## INFO  [14:32:35.853] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)

## Check the performace measures
c_rf$score(measure)

task	task_id	learner	learner_id	resampling	resampling_id	iteration	prediction	regr.rmse
<environment>	con	<environment>	regr.ranger	<environment>	holdout	1	<environment>	0.965

##Convert the RMSE to a percentage
rmse = c_rf$score(measure)

##Percentage Conversion
rmse = (rmse$regr.rmse / 3.2) * 100

##Show RMSE
print(rmse)

## [1] 30.16976

Random Forest Model Tune

#Show the tuning parameters
lrn_rf$param_set

## <ParamSet>
##                               id    class lower upper nlevels        default
##  1:                        alpha ParamDbl  -Inf   Inf     Inf            0.5
##  2:       always.split.variables ParamUty    NA    NA     Inf <NoDefault[3]>
##  3:                      holdout ParamLgl    NA    NA       2          FALSE
##  4:                   importance ParamFct    NA    NA       4 <NoDefault[3]>
##  5:                   keep.inbag ParamLgl    NA    NA       2          FALSE
##  6:                    max.depth ParamInt     0   Inf     Inf               
##  7:                min.node.size ParamInt     1   Inf     Inf              5
##  8:                     min.prop ParamDbl  -Inf   Inf     Inf            0.1
##  9:                      minprop ParamDbl  -Inf   Inf     Inf            0.1
## 10:                         mtry ParamInt     1   Inf     Inf <NoDefault[3]>
## 11:                   mtry.ratio ParamDbl     0     1     Inf <NoDefault[3]>
## 12:            num.random.splits ParamInt     1   Inf     Inf              1
## 13:                  num.threads ParamInt     1   Inf     Inf              1
## 14:                    num.trees ParamInt     1   Inf     Inf            500
## 15:                    oob.error ParamLgl    NA    NA       2           TRUE
## 16:                     quantreg ParamLgl    NA    NA       2          FALSE
## 17:        regularization.factor ParamUty    NA    NA     Inf              1
## 18:      regularization.usedepth ParamLgl    NA    NA       2          FALSE
## 19:                      replace ParamLgl    NA    NA       2           TRUE
## 20:    respect.unordered.factors ParamFct    NA    NA       3         ignore
## 21:              sample.fraction ParamDbl     0     1     Inf <NoDefault[3]>
## 22:                  save.memory ParamLgl    NA    NA       2          FALSE
## 23: scale.permutation.importance ParamLgl    NA    NA       2          FALSE
## 24:                    se.method ParamFct    NA    NA       2        infjack
## 25:                         seed ParamInt  -Inf   Inf     Inf               
## 26:         split.select.weights ParamUty    NA    NA     Inf               
## 27:                    splitrule ParamFct    NA    NA       3       variance
## 28:                      verbose ParamLgl    NA    NA       2           TRUE
## 29:                 write.forest ParamLgl    NA    NA       2           TRUE
##                               id    class lower upper nlevels        default
##        parents       value
##  1:  splitrule            
##  2:                       
##  3:                       
##  4:            permutation
##  5:                       
##  6:                       
##  7:                       
##  8:                       
##  9:  splitrule            
## 10:                       
## 11:                       
## 12:  splitrule            
## 13:                      1
## 14:                       
## 15:                       
## 16:                       
## 17:                       
## 18:                       
## 19:                       
## 20:                       
## 21:                       
## 22:                       
## 23: importance            
## 24:                       
## 25:                       
## 26:                       
## 27:                       
## 28:                       
## 29:                       
##        parents       value

## Build parameter set for tuning
##mtry = number of variables per split
##num.trees = number of trees built

tune_ps = ParamSet$new(list(
  ParamInt$new("mtry", lower = 1, upper = 8),
  ParamInt$new("num.trees", lower = 100, upper = 1000)
))

## Limit the number of iterations/evaluations to 50
evals = trm("evals",
            n_evals = 50)

## Define the tuner to grid search with 10 steps between the lower and upper bounds
tuner = tnr("grid_search",
            resolution = 10)

## Set up the nested resampling for tuning
## Build the resample for the inner
resampling_inner = rsmp("holdout",
                        ratio = 0.8)

## Build the resample for the outer (in this case 3-fold)
resampling_outer = rsmp("cv", 
                        folds = 3)

## Set up the autotuner

at_rf = AutoTuner$new(learner = lrn_rf,
                      resampling = resampling_inner,
                      measure = measure,
                      search_space = tune_ps,
                      terminator = evals,
                      tuner = tuner)

## Tuning the paramaters using the parameter set/solution

c_rf.2 = resample(task = task_con,
                 learner = at_rf,
                 resampling = resampling_outer,
                 store_models = TRUE)

## INFO  [14:32:36.040] [mlr3] Applying learner 'regr.ranger.tuned' on task 'con' (iter 1/3)
## INFO  [14:32:36.077] [bbotk] Starting to optimize 2 parameter(s) with '<TunerGridSearch>' and '<TerminatorEvals> [n_evals=50, k=0]'
## INFO  [14:32:36.079] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.090] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.093] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.138] [mlr3] Finished benchmark
## INFO  [14:32:36.149] [bbotk] Result of batch 1:
## INFO  [14:32:36.150] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.150] [bbotk]     3       700 0.8656989        0      0            0.042
## INFO  [14:32:36.150] [bbotk]                                 uhash
## INFO  [14:32:36.150] [bbotk]  a85ad7dc-0c40-485b-a8ac-bdeac8b58ba9
## INFO  [14:32:36.151] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.160] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.163] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.184] [mlr3] Finished benchmark
## INFO  [14:32:36.195] [bbotk] Result of batch 2:
## INFO  [14:32:36.195] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.195] [bbotk]     2       300 0.9131195        0      0            0.017
## INFO  [14:32:36.195] [bbotk]                                 uhash
## INFO  [14:32:36.195] [bbotk]  b53538c7-3e51-45e3-8129-7d7a29e21e34
## INFO  [14:32:36.196] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.206] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.208] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.288] [mlr3] Finished benchmark
## INFO  [14:32:36.298] [bbotk] Result of batch 3:
## INFO  [14:32:36.299] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.299] [bbotk]     8       900 0.8665425        0      0            0.077
## INFO  [14:32:36.299] [bbotk]                                 uhash
## INFO  [14:32:36.299] [bbotk]  7a125cb4-d529-44c2-bce1-2e6083d02ad8
## INFO  [14:32:36.300] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.317] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.319] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.345] [mlr3] Finished benchmark
## INFO  [14:32:36.355] [bbotk] Result of batch 4:
## INFO  [14:32:36.356] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.356] [bbotk]     5       300 0.8798192        0      0            0.022
## INFO  [14:32:36.356] [bbotk]                                 uhash
## INFO  [14:32:36.356] [bbotk]  b3a850f7-2bcf-46f6-b870-4422b1c68932
## INFO  [14:32:36.357] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.366] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.369] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.402] [mlr3] Finished benchmark
## INFO  [14:32:36.413] [bbotk] Result of batch 5:
## INFO  [14:32:36.413] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.413] [bbotk]     5       400 0.8741817        0      0             0.03
## INFO  [14:32:36.413] [bbotk]                                 uhash
## INFO  [14:32:36.413] [bbotk]  db4c5f2b-773c-43bf-bc34-7a66b17a0845
## INFO  [14:32:36.414] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.424] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.426] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.499] [mlr3] Finished benchmark
## INFO  [14:32:36.509] [bbotk] Result of batch 6:
## INFO  [14:32:36.510] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.510] [bbotk]     5      1000 0.8792075        0      0            0.069
## INFO  [14:32:36.510] [bbotk]                                 uhash
## INFO  [14:32:36.510] [bbotk]  046fbc19-2645-432c-839f-0041a8e961f8
## INFO  [14:32:36.511] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.520] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.523] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.535] [mlr3] Finished benchmark
## INFO  [14:32:36.546] [bbotk] Result of batch 7:
## INFO  [14:32:36.546] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.546] [bbotk]     5       100 0.9044951        0      0            0.008
## INFO  [14:32:36.546] [bbotk]                                 uhash
## INFO  [14:32:36.546] [bbotk]  b05a6fe4-9330-45f2-810c-8b8e6361a4ea
## INFO  [14:32:36.547] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.556] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.559] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.616] [mlr3] Finished benchmark
## INFO  [14:32:36.626] [bbotk] Result of batch 8:
## INFO  [14:32:36.627] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.627] [bbotk]     3       900 0.8751083        0      0            0.053
## INFO  [14:32:36.627] [bbotk]                                 uhash
## INFO  [14:32:36.627] [bbotk]  7094fbef-4457-49dd-834c-d43c700331c7
## INFO  [14:32:36.628] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.637] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.640] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.657] [mlr3] Finished benchmark
## INFO  [14:32:36.667] [bbotk] Result of batch 9:
## INFO  [14:32:36.668] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.668] [bbotk]     3       200 0.8706394        0      0            0.014
## INFO  [14:32:36.668] [bbotk]                                 uhash
## INFO  [14:32:36.668] [bbotk]  92245721-bcd9-4e45-b9b6-6b0d9f0aab38
## INFO  [14:32:36.675] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.685] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.687] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.724] [mlr3] Finished benchmark
## INFO  [14:32:36.734] [bbotk] Result of batch 10:
## INFO  [14:32:36.735] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.735] [bbotk]     7       400 0.8809779        0      0            0.034
## INFO  [14:32:36.735] [bbotk]                                 uhash
## INFO  [14:32:36.735] [bbotk]  51aca116-ec51-44bd-af80-d9f862bf849b
## INFO  [14:32:36.735] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.745] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.747] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.785] [mlr3] Finished benchmark
## INFO  [14:32:36.795] [bbotk] Result of batch 11:
## INFO  [14:32:36.796] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.796] [bbotk]     8       400 0.8876452        0      0            0.035
## INFO  [14:32:36.796] [bbotk]                                 uhash
## INFO  [14:32:36.796] [bbotk]  01de1d83-223f-4a10-a3bc-daba6314c979
## INFO  [14:32:36.796] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.806] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.809] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.855] [mlr3] Finished benchmark
## INFO  [14:32:36.865] [bbotk] Result of batch 12:
## INFO  [14:32:36.866] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.866] [bbotk]     1       900 0.9012829        0      0            0.043
## INFO  [14:32:36.866] [bbotk]                                 uhash
## INFO  [14:32:36.866] [bbotk]  9172cf8f-9b46-4152-a206-17d30816aeb3
## INFO  [14:32:36.867] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.876] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.879] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.907] [mlr3] Finished benchmark
## INFO  [14:32:36.918] [bbotk] Result of batch 13:
## INFO  [14:32:36.918] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.918] [bbotk]     1       500 0.8964394        0      0            0.025
## INFO  [14:32:36.918] [bbotk]                                 uhash
## INFO  [14:32:36.918] [bbotk]  59d38b97-4ddd-4667-aa9f-057be205d371
## INFO  [14:32:36.919] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.929] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.931] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:36.950] [mlr3] Finished benchmark
## INFO  [14:32:36.961] [bbotk] Result of batch 14:
## INFO  [14:32:36.962] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:36.962] [bbotk]     5       200 0.8614246        0      0            0.016
## INFO  [14:32:36.962] [bbotk]                                 uhash
## INFO  [14:32:36.962] [bbotk]  3199dad4-6d2a-40a0-ae89-628ffc4df67f
## INFO  [14:32:36.962] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:36.972] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:36.974] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.045] [mlr3] Finished benchmark
## INFO  [14:32:37.057] [bbotk] Result of batch 15:
## INFO  [14:32:37.058] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.058] [bbotk]     6       100 0.8859218        0      0            0.067
## INFO  [14:32:37.058] [bbotk]                                 uhash
## INFO  [14:32:37.058] [bbotk]  63f9c543-5344-41c8-97b3-ccbf84f18ea1
## INFO  [14:32:37.058] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.068] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.070] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.146] [mlr3] Finished benchmark
## INFO  [14:32:37.156] [bbotk] Result of batch 16:
## INFO  [14:32:37.157] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.157] [bbotk]     7       900 0.8574718        0      0            0.072
## INFO  [14:32:37.157] [bbotk]                                 uhash
## INFO  [14:32:37.157] [bbotk]  d7fe147f-f2f6-4ffe-889e-ef6cee9fcc56
## INFO  [14:32:37.157] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.167] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.169] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.222] [mlr3] Finished benchmark
## INFO  [14:32:37.232] [bbotk] Result of batch 17:
## INFO  [14:32:37.233] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.233] [bbotk]     5       700 0.8836189        0      0             0.05
## INFO  [14:32:37.233] [bbotk]                                 uhash
## INFO  [14:32:37.233] [bbotk]  ce69ddcc-fa67-4f4f-a2fd-81821544a4b7
## INFO  [14:32:37.234] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.243] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.246] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.289] [mlr3] Finished benchmark
## INFO  [14:32:37.300] [bbotk] Result of batch 18:
## INFO  [14:32:37.301] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.301] [bbotk]     4       600 0.8701062        0      0            0.039
## INFO  [14:32:37.301] [bbotk]                                 uhash
## INFO  [14:32:37.301] [bbotk]  41474f71-3539-444d-b6d1-ab2509e8bf50
## INFO  [14:32:37.301] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.311] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.313] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.355] [mlr3] Finished benchmark
## INFO  [14:32:37.366] [bbotk] Result of batch 19:
## INFO  [14:32:37.366] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.366] [bbotk]     2       700  0.891969        0      0            0.039
## INFO  [14:32:37.366] [bbotk]                                 uhash
## INFO  [14:32:37.366] [bbotk]  6ff43ca0-0cde-41f8-bd65-b17d1baa61e4
## INFO  [14:32:37.367] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.377] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.379] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.436] [mlr3] Finished benchmark
## INFO  [14:32:37.447] [bbotk] Result of batch 20:
## INFO  [14:32:37.448] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.448] [bbotk]     2      1000  0.882654        0      0            0.054
## INFO  [14:32:37.448] [bbotk]                                 uhash
## INFO  [14:32:37.448] [bbotk]  1b8b558e-92aa-4ac7-9ed3-de63c7d27ef5
## INFO  [14:32:37.448] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.458] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.460] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.529] [mlr3] Finished benchmark
## INFO  [14:32:37.541] [bbotk] Result of batch 21:
## INFO  [14:32:37.541] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.541] [bbotk]     7       700 0.8712492        0      0            0.065
## INFO  [14:32:37.541] [bbotk]                                 uhash
## INFO  [14:32:37.541] [bbotk]  f2d55fcc-cf7f-4ac7-9e93-8c34dadb5165
## INFO  [14:32:37.542] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.551] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.554] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.621] [mlr3] Finished benchmark
## INFO  [14:32:37.632] [bbotk] Result of batch 22:
## INFO  [14:32:37.632] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.632] [bbotk]     4      1000  0.884293        0      0            0.063
## INFO  [14:32:37.632] [bbotk]                                 uhash
## INFO  [14:32:37.632] [bbotk]  aad1a3c1-3fc6-42a7-91d4-9b0a713884a1
## INFO  [14:32:37.633] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.643] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.645] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.701] [mlr3] Finished benchmark
## INFO  [14:32:37.712] [bbotk] Result of batch 23:
## INFO  [14:32:37.712] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.712] [bbotk]     6       700 0.8795641        0      0            0.053
## INFO  [14:32:37.712] [bbotk]                                 uhash
## INFO  [14:32:37.712] [bbotk]  3f19ecdb-6aaa-49a3-b5be-bc11ba3d91de
## INFO  [14:32:37.713] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.723] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.725] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.764] [mlr3] Finished benchmark
## INFO  [14:32:37.775] [bbotk] Result of batch 24:
## INFO  [14:32:37.775] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.775] [bbotk]     5       500  0.863082        0      0            0.036
## INFO  [14:32:37.775] [bbotk]                                 uhash
## INFO  [14:32:37.775] [bbotk]  82e85a49-760d-475f-8597-823a8bc89ce8
## INFO  [14:32:37.776] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.786] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.788] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.828] [mlr3] Finished benchmark
## INFO  [14:32:37.839] [bbotk] Result of batch 25:
## INFO  [14:32:37.840] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.840] [bbotk]     3       600 0.8945471        0      0            0.036
## INFO  [14:32:37.840] [bbotk]                                 uhash
## INFO  [14:32:37.840] [bbotk]  f211313b-822a-4e4b-bc20-c8158ac43fae
## INFO  [14:32:37.840] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.850] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.853] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.903] [mlr3] Finished benchmark
## INFO  [14:32:37.914] [bbotk] Result of batch 26:
## INFO  [14:32:37.914] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.914] [bbotk]     1      1000 0.9072676        0      0            0.047
## INFO  [14:32:37.914] [bbotk]                                 uhash
## INFO  [14:32:37.914] [bbotk]  7e9b1a98-2e6e-452d-8a62-0baf278da7ab
## INFO  [14:32:37.915] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.925] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.935] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:37.971] [mlr3] Finished benchmark
## INFO  [14:32:37.982] [bbotk] Result of batch 27:
## INFO  [14:32:37.982] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:37.982] [bbotk]     6       400  0.853528        0      0            0.032
## INFO  [14:32:37.982] [bbotk]                                 uhash
## INFO  [14:32:37.982] [bbotk]  e14a089e-4fc9-444a-a13c-f3f1fdad2a4a
## INFO  [14:32:37.983] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:37.992] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:37.995] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.013] [mlr3] Finished benchmark
## INFO  [14:32:38.023] [bbotk] Result of batch 28:
## INFO  [14:32:38.024] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.024] [bbotk]     4       200 0.8814159        0      0            0.015
## INFO  [14:32:38.024] [bbotk]                                 uhash
## INFO  [14:32:38.024] [bbotk]  f8bd93fb-966f-4355-a7d8-dc0992509dad
## INFO  [14:32:38.025] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.034] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.037] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.100] [mlr3] Finished benchmark
## INFO  [14:32:38.110] [bbotk] Result of batch 29:
## INFO  [14:32:38.111] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.111] [bbotk]     3      1000 0.8873341        0      0            0.059
## INFO  [14:32:38.111] [bbotk]                                 uhash
## INFO  [14:32:38.111] [bbotk]  9dd786c5-cc23-4344-95bf-54ba8a2ad2f3
## INFO  [14:32:38.111] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.121] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.124] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.145] [mlr3] Finished benchmark
## INFO  [14:32:38.156] [bbotk] Result of batch 30:
## INFO  [14:32:38.156] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.156] [bbotk]     7       200 0.8801223        0      0            0.018
## INFO  [14:32:38.156] [bbotk]                                 uhash
## INFO  [14:32:38.156] [bbotk]  864d50ea-3486-4734-bb6c-5ae29e441005
## INFO  [14:32:38.157] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.167] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.169] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.213] [mlr3] Finished benchmark
## INFO  [14:32:38.223] [bbotk] Result of batch 31:
## INFO  [14:32:38.224] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.224] [bbotk]     7       500 0.8585624        0      0             0.04
## INFO  [14:32:38.224] [bbotk]                                 uhash
## INFO  [14:32:38.224] [bbotk]  a397733d-75c5-418c-84d2-0f092644995d
## INFO  [14:32:38.224] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.235] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.238] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.248] [mlr3] Finished benchmark
## INFO  [14:32:38.258] [bbotk] Result of batch 32:
## INFO  [14:32:38.259] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.259] [bbotk]     1       100  0.908031        0      0            0.008
## INFO  [14:32:38.259] [bbotk]                                 uhash
## INFO  [14:32:38.259] [bbotk]  58d880db-5420-4cf5-96e6-755e6b8f94af
## INFO  [14:32:38.259] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.276] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.279] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.331] [mlr3] Finished benchmark
## INFO  [14:32:38.342] [bbotk] Result of batch 33:
## INFO  [14:32:38.342] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.342] [bbotk]     3       800 0.8918893        0      0            0.047
## INFO  [14:32:38.342] [bbotk]                                 uhash
## INFO  [14:32:38.342] [bbotk]  f8bd2540-dfee-4c44-be1e-2eea7dc427bb
## INFO  [14:32:38.343] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.353] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.355] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.405] [mlr3] Finished benchmark
## INFO  [14:32:38.415] [bbotk] Result of batch 34:
## INFO  [14:32:38.416] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.416] [bbotk]     4       700 0.8812927        0      0            0.046
## INFO  [14:32:38.416] [bbotk]                                 uhash
## INFO  [14:32:38.416] [bbotk]  4aeaf7d4-2b96-47c9-9850-36658c8e681b
## INFO  [14:32:38.416] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.426] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.428] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.492] [mlr3] Finished benchmark
## INFO  [14:32:38.503] [bbotk] Result of batch 35:
## INFO  [14:32:38.503] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.503] [bbotk]     6       800  0.867535        0      0             0.06
## INFO  [14:32:38.503] [bbotk]                                 uhash
## INFO  [14:32:38.503] [bbotk]  7159b137-f5cb-4249-9396-88ba59f667c6
## INFO  [14:32:38.504] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.514] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.516] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.547] [mlr3] Finished benchmark
## INFO  [14:32:38.557] [bbotk] Result of batch 36:
## INFO  [14:32:38.558] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.558] [bbotk]     8       300 0.8832559        0      0            0.028
## INFO  [14:32:38.558] [bbotk]                                 uhash
## INFO  [14:32:38.558] [bbotk]  cbdd856a-c744-411c-81b8-7c7058b69a3f
## INFO  [14:32:38.559] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.568] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.571] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.648] [mlr3] Finished benchmark
## INFO  [14:32:38.659] [bbotk] Result of batch 37:
## INFO  [14:32:38.659] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.659] [bbotk]     6      1000 0.8651744        0      0            0.073
## INFO  [14:32:38.659] [bbotk]                                 uhash
## INFO  [14:32:38.659] [bbotk]  eba8c17c-283b-497d-84ec-91ebcaf3edcd
## INFO  [14:32:38.660] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.670] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.672] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.739] [mlr3] Finished benchmark
## INFO  [14:32:38.758] [bbotk] Result of batch 38:
## INFO  [14:32:38.759] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.759] [bbotk]     5       900  0.868787        0      0            0.064
## INFO  [14:32:38.759] [bbotk]                                 uhash
## INFO  [14:32:38.759] [bbotk]  28947ba3-9bbe-4d05-b25b-6909af6d03f3
## INFO  [14:32:38.759] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.770] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.773] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.802] [mlr3] Finished benchmark
## INFO  [14:32:38.812] [bbotk] Result of batch 39:
## INFO  [14:32:38.813] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.813] [bbotk]     7       300 0.8861987        0      0            0.026
## INFO  [14:32:38.813] [bbotk]                                 uhash
## INFO  [14:32:38.813] [bbotk]  2c8cc27e-5da9-45da-a1bc-c2b135cbbd14
## INFO  [14:32:38.813] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.823] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.825] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.840] [mlr3] Finished benchmark
## INFO  [14:32:38.850] [bbotk] Result of batch 40:
## INFO  [14:32:38.851] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.851] [bbotk]     1       200 0.9185052        0      0            0.012
## INFO  [14:32:38.851] [bbotk]                                 uhash
## INFO  [14:32:38.851] [bbotk]  a4ec35f6-f437-4ce9-b72b-c20f2e5f4540
## INFO  [14:32:38.852] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.861] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.864] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:38.916] [mlr3] Finished benchmark
## INFO  [14:32:38.927] [bbotk] Result of batch 41:
## INFO  [14:32:38.927] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:38.927] [bbotk]     7       600 0.8558836        0      0            0.048
## INFO  [14:32:38.927] [bbotk]                                 uhash
## INFO  [14:32:38.927] [bbotk]  884d6c6a-de77-474b-9f7f-1ec77bbe198e
## INFO  [14:32:38.928] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:38.938] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:38.940] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.011] [mlr3] Finished benchmark
## INFO  [14:32:39.022] [bbotk] Result of batch 42:
## INFO  [14:32:39.023] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.023] [bbotk]     6       900 0.8754255        0      0            0.067
## INFO  [14:32:39.023] [bbotk]                                 uhash
## INFO  [14:32:39.023] [bbotk]  73f1820c-1421-4482-9837-218334f5965b
## INFO  [14:32:39.023] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.033] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.036] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.059] [mlr3] Finished benchmark
## INFO  [14:32:39.070] [bbotk] Result of batch 43:
## INFO  [14:32:39.070] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.070] [bbotk]     3       300 0.8766059        0      0            0.021
## INFO  [14:32:39.070] [bbotk]                                 uhash
## INFO  [14:32:39.070] [bbotk]  e8a5c9e1-7cbe-44f1-8960-d0900da0d9a8
## INFO  [14:32:39.071] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.081] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.083] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.137] [mlr3] Finished benchmark
## INFO  [14:32:39.157] [bbotk] Result of batch 44:
## INFO  [14:32:39.157] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.157] [bbotk]     8       600 0.8534176        0      0             0.05
## INFO  [14:32:39.157] [bbotk]                                 uhash
## INFO  [14:32:39.157] [bbotk]  224611b6-89e7-461d-8362-2c03af8e5068
## INFO  [14:32:39.158] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.167] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.170] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.226] [mlr3] Finished benchmark
## INFO  [14:32:39.236] [bbotk] Result of batch 45:
## INFO  [14:32:39.237] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.237] [bbotk]     4       800 0.8890419        0      0            0.053
## INFO  [14:32:39.237] [bbotk]                                 uhash
## INFO  [14:32:39.237] [bbotk]  1454b86d-2533-4a16-a7e7-a23bc893fb38
## INFO  [14:32:39.237] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.247] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.249] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.275] [mlr3] Finished benchmark
## INFO  [14:32:39.286] [bbotk] Result of batch 46:
## INFO  [14:32:39.287] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.287] [bbotk]     2       400 0.9088053        0      0            0.022
## INFO  [14:32:39.287] [bbotk]                                 uhash
## INFO  [14:32:39.287] [bbotk]  e916c9ad-f4c7-4f53-9401-9b916525d203
## INFO  [14:32:39.287] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.297] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.299] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.328] [mlr3] Finished benchmark
## INFO  [14:32:39.338] [bbotk] Result of batch 47:
## INFO  [14:32:39.339] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.339] [bbotk]     3       400  0.871436        0      0            0.026
## INFO  [14:32:39.339] [bbotk]                                 uhash
## INFO  [14:32:39.339] [bbotk]  93b33c4c-3edc-4320-8740-e6314ac3ca18
## INFO  [14:32:39.340] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.349] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.352] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.376] [mlr3] Finished benchmark
## INFO  [14:32:39.386] [bbotk] Result of batch 48:
## INFO  [14:32:39.387] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.387] [bbotk]     1       400 0.9029087        0      0             0.02
## INFO  [14:32:39.387] [bbotk]                                 uhash
## INFO  [14:32:39.387] [bbotk]  6ae0b5b2-c6ef-424d-b07c-1d130c3db1fa
## INFO  [14:32:39.387] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.397] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.400] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.470] [mlr3] Finished benchmark
## INFO  [14:32:39.481] [bbotk] Result of batch 49:
## INFO  [14:32:39.481] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.481] [bbotk]     8       800 0.8694887        0      0            0.066
## INFO  [14:32:39.481] [bbotk]                                 uhash
## INFO  [14:32:39.481] [bbotk]  2e830be6-7824-4312-8a32-d05d46ce9c5f
## INFO  [14:32:39.482] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.491] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.494] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.521] [mlr3] Finished benchmark
## INFO  [14:32:39.533] [bbotk] Result of batch 50:
## INFO  [14:32:39.534] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.534] [bbotk]     6       200 0.8886558        0      0            0.024
## INFO  [14:32:39.534] [bbotk]                                 uhash
## INFO  [14:32:39.534] [bbotk]  8bab6517-f089-4e3d-afb8-92bda9ebf76d
## INFO  [14:32:39.536] [bbotk] Finished optimizing after 50 evaluation(s)
## INFO  [14:32:39.537] [bbotk] Result:
## INFO  [14:32:39.537] [bbotk]  mtry num.trees learner_param_vals  x_domain regr.rmse
## INFO  [14:32:39.537] [bbotk]     8       600          <list[4]> <list[2]> 0.8534176
## INFO  [14:32:39.617] [mlr3] Applying learner 'regr.ranger.tuned' on task 'con' (iter 2/3)
## INFO  [14:32:39.640] [bbotk] Starting to optimize 2 parameter(s) with '<TunerGridSearch>' and '<TerminatorEvals> [n_evals=50, k=0]'
## INFO  [14:32:39.641] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.651] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.654] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.721] [mlr3] Finished benchmark
## INFO  [14:32:39.731] [bbotk] Result of batch 1:
## INFO  [14:32:39.732] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.732] [bbotk]     6       900 0.7176315        0      0            0.063
## INFO  [14:32:39.732] [bbotk]                                 uhash
## INFO  [14:32:39.732] [bbotk]  9a783747-7af5-4d50-a542-dffb4fc3b611
## INFO  [14:32:39.732] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.742] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.745] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.770] [mlr3] Finished benchmark
## INFO  [14:32:39.781] [bbotk] Result of batch 2:
## INFO  [14:32:39.781] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.781] [bbotk]     2       400 0.7319344        0      0            0.022
## INFO  [14:32:39.781] [bbotk]                                 uhash
## INFO  [14:32:39.781] [bbotk]  4b4672ca-25f4-4c59-8db4-3e598ae201a8
## INFO  [14:32:39.782] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.792] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.794] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.815] [mlr3] Finished benchmark
## INFO  [14:32:39.825] [bbotk] Result of batch 3:
## INFO  [14:32:39.826] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.826] [bbotk]     7       200 0.7138458        0      0            0.017
## INFO  [14:32:39.826] [bbotk]                                 uhash
## INFO  [14:32:39.826] [bbotk]  d4c05d50-588d-47f3-b7f5-cbbb264cf93b
## INFO  [14:32:39.827] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.836] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.839] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.864] [mlr3] Finished benchmark
## INFO  [14:32:39.883] [bbotk] Result of batch 4:
## INFO  [14:32:39.884] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.884] [bbotk]     5       300  0.718088        0      0            0.021
## INFO  [14:32:39.884] [bbotk]                                 uhash
## INFO  [14:32:39.884] [bbotk]  3df63a6c-ba26-4eaf-8f02-b01fe0311bb2
## INFO  [14:32:39.885] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.894] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.897] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:39.964] [mlr3] Finished benchmark
## INFO  [14:32:39.974] [bbotk] Result of batch 5:
## INFO  [14:32:39.975] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:39.975] [bbotk]     4      1000  0.719076        0      0            0.064
## INFO  [14:32:39.975] [bbotk]                                 uhash
## INFO  [14:32:39.975] [bbotk]  a01a2103-714a-4683-9fde-23cc2c9ea495
## INFO  [14:32:39.976] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:39.985] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:39.988] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.007] [mlr3] Finished benchmark
## INFO  [14:32:40.017] [bbotk] Result of batch 6:
## INFO  [14:32:40.018] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.018] [bbotk]     5       200 0.7166376        0      0            0.015
## INFO  [14:32:40.018] [bbotk]                                 uhash
## INFO  [14:32:40.018] [bbotk]  297b592a-3a02-4381-b4e9-613b56d49374
## INFO  [14:32:40.018] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.028] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.031] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.042] [mlr3] Finished benchmark
## INFO  [14:32:40.053] [bbotk] Result of batch 7:
## INFO  [14:32:40.054] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.054] [bbotk]     3       100 0.7297843        0      0            0.007
## INFO  [14:32:40.054] [bbotk]                                 uhash
## INFO  [14:32:40.054] [bbotk]  39af26ff-0677-4c84-bf28-6fddb997ed8a
## INFO  [14:32:40.054] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.064] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.066] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.094] [mlr3] Finished benchmark
## INFO  [14:32:40.104] [bbotk] Result of batch 8:
## INFO  [14:32:40.105] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.105] [bbotk]     7       300 0.7103303        0      0            0.024
## INFO  [14:32:40.105] [bbotk]                                 uhash
## INFO  [14:32:40.105] [bbotk]  3416a35c-6f9e-4ca4-80f8-b249929d6186
## INFO  [14:32:40.106] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.115] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.118] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.131] [mlr3] Finished benchmark
## INFO  [14:32:40.141] [bbotk] Result of batch 9:
## INFO  [14:32:40.142] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.142] [bbotk]     7       100 0.7171875        0      0             0.01
## INFO  [14:32:40.142] [bbotk]                                 uhash
## INFO  [14:32:40.142] [bbotk]  32a781b2-0ec0-4fbd-8cf1-ec34a26ff18d
## INFO  [14:32:40.143] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.159] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.162] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.216] [mlr3] Finished benchmark
## INFO  [14:32:40.227] [bbotk] Result of batch 10:
## INFO  [14:32:40.227] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.227] [bbotk]     2       900 0.7371215        0      0             0.05
## INFO  [14:32:40.227] [bbotk]                                 uhash
## INFO  [14:32:40.227] [bbotk]  2231e981-7863-4e73-9f04-27f1be65b276
## INFO  [14:32:40.228] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.237] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.240] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.261] [mlr3] Finished benchmark
## INFO  [14:32:40.271] [bbotk] Result of batch 11:
## INFO  [14:32:40.272] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.272] [bbotk]     2       300 0.7238894        0      0            0.017
## INFO  [14:32:40.272] [bbotk]                                 uhash
## INFO  [14:32:40.272] [bbotk]  7d83f565-57fd-48c1-8ee6-16a29353dd90
## INFO  [14:32:40.272] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.282] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.285] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.306] [mlr3] Finished benchmark
## INFO  [14:32:40.316] [bbotk] Result of batch 12:
## INFO  [14:32:40.317] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.317] [bbotk]     8       200  0.729089        0      0            0.017
## INFO  [14:32:40.317] [bbotk]                                 uhash
## INFO  [14:32:40.317] [bbotk]  ffcee213-c2fc-43c8-b986-d2e3e5e3bbbb
## INFO  [14:32:40.318] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.327] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.330] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.409] [mlr3] Finished benchmark
## INFO  [14:32:40.420] [bbotk] Result of batch 13:
## INFO  [14:32:40.420] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.420] [bbotk]     7      1000 0.7127689        0      0            0.075
## INFO  [14:32:40.420] [bbotk]                                 uhash
## INFO  [14:32:40.420] [bbotk]  268214bd-6ba5-4343-beb7-1935c8aecdff
## INFO  [14:32:40.421] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.430] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.433] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.505] [mlr3] Finished benchmark
## INFO  [14:32:40.516] [bbotk] Result of batch 14:
## INFO  [14:32:40.517] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.517] [bbotk]     7       900 0.7096142        0      0            0.069
## INFO  [14:32:40.517] [bbotk]                                 uhash
## INFO  [14:32:40.517] [bbotk]  c54326a7-d71e-4460-873c-f87ed8631946
## INFO  [14:32:40.517] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.527] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.530] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.605] [mlr3] Finished benchmark
## INFO  [14:32:40.618] [bbotk] Result of batch 15:
## INFO  [14:32:40.619] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.619] [bbotk]     5       700 0.7181864        0      0            0.071
## INFO  [14:32:40.619] [bbotk]                                 uhash
## INFO  [14:32:40.619] [bbotk]  5b90c953-43c5-4809-bfcd-336928708a7a
## INFO  [14:32:40.620] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.629] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.632] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.662] [mlr3] Finished benchmark
## INFO  [14:32:40.673] [bbotk] Result of batch 16:
## INFO  [14:32:40.673] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.673] [bbotk]     4       400   0.73039        0      0            0.026
## INFO  [14:32:40.673] [bbotk]                                 uhash
## INFO  [14:32:40.673] [bbotk]  10759a64-b834-483b-89e7-8beecb26c330
## INFO  [14:32:40.674] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.683] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.686] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.761] [mlr3] Finished benchmark
## INFO  [14:32:40.772] [bbotk] Result of batch 17:
## INFO  [14:32:40.772] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.772] [bbotk]     8       900 0.7183233        0      0            0.071
## INFO  [14:32:40.772] [bbotk]                                 uhash
## INFO  [14:32:40.772] [bbotk]  adc427f8-6e2b-42cb-9d9b-b7a72728831b
## INFO  [14:32:40.773] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.783] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.785] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.804] [mlr3] Finished benchmark
## INFO  [14:32:40.815] [bbotk] Result of batch 18:
## INFO  [14:32:40.815] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.815] [bbotk]     1       300 0.7350476        0      0            0.016
## INFO  [14:32:40.815] [bbotk]                                 uhash
## INFO  [14:32:40.815] [bbotk]  95112855-e93c-4095-8f0d-815346cbb578
## INFO  [14:32:40.816] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.826] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.828] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.870] [mlr3] Finished benchmark
## INFO  [14:32:40.881] [bbotk] Result of batch 19:
## INFO  [14:32:40.882] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.882] [bbotk]     4       600 0.7184602        0      0            0.038
## INFO  [14:32:40.882] [bbotk]                                 uhash
## INFO  [14:32:40.882] [bbotk]  00e7a07b-8f4f-4a39-961c-ba80090627fa
## INFO  [14:32:40.883] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.893] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.895] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.934] [mlr3] Finished benchmark
## INFO  [14:32:40.944] [bbotk] Result of batch 20:
## INFO  [14:32:40.945] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:40.945] [bbotk]     5       500 0.7148469        0      0            0.035
## INFO  [14:32:40.945] [bbotk]                                 uhash
## INFO  [14:32:40.945] [bbotk]  0bae1636-5dcf-4705-b911-7d2773b75f05
## INFO  [14:32:40.946] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:40.955] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:40.966] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:40.988] [mlr3] Finished benchmark
## INFO  [14:32:40.999] [bbotk] Result of batch 21:
## INFO  [14:32:41.000] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.000] [bbotk]     6       200 0.7211701        0      0            0.017
## INFO  [14:32:41.000] [bbotk]                                 uhash
## INFO  [14:32:41.000] [bbotk]  06ce7f89-081d-4f46-887b-77b7e6734101
## INFO  [14:32:41.001] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.010] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.013] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.041] [mlr3] Finished benchmark
## INFO  [14:32:41.052] [bbotk] Result of batch 22:
## INFO  [14:32:41.053] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.053] [bbotk]     1       500 0.7334442        0      0            0.024
## INFO  [14:32:41.053] [bbotk]                                 uhash
## INFO  [14:32:41.053] [bbotk]  d83eb685-71f7-4c41-b93a-577dc55597a6
## INFO  [14:32:41.054] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.063] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.066] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.137] [mlr3] Finished benchmark
## INFO  [14:32:41.147] [bbotk] Result of batch 23:
## INFO  [14:32:41.148] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.148] [bbotk]     5      1000 0.7174425        0      0            0.067
## INFO  [14:32:41.148] [bbotk]                                 uhash
## INFO  [14:32:41.148] [bbotk]  dc0b4259-614c-48b7-8523-3246d664771d
## INFO  [14:32:41.149] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.159] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.161] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.225] [mlr3] Finished benchmark
## INFO  [14:32:41.236] [bbotk] Result of batch 24:
## INFO  [14:32:41.237] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.237] [bbotk]     5       900 0.7196147        0      0             0.06
## INFO  [14:32:41.237] [bbotk]                                 uhash
## INFO  [14:32:41.237] [bbotk]  30e43aee-046c-4c0a-b385-3209b54ff095
## INFO  [14:32:41.237] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.247] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.250] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.261] [mlr3] Finished benchmark
## INFO  [14:32:41.272] [bbotk] Result of batch 25:
## INFO  [14:32:41.272] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.272] [bbotk]     5       100 0.7319934        0      0             0.01
## INFO  [14:32:41.272] [bbotk]                                 uhash
## INFO  [14:32:41.272] [bbotk]  0ddbf239-40eb-4620-9b48-cc1fa737d097
## INFO  [14:32:41.273] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.283] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.285] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.339] [mlr3] Finished benchmark
## INFO  [14:32:41.358] [bbotk] Result of batch 26:
## INFO  [14:32:41.359] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.359] [bbotk]     4       800 0.7282713        0      0             0.05
## INFO  [14:32:41.359] [bbotk]                                 uhash
## INFO  [14:32:41.359] [bbotk]  66eb06ed-3336-46d9-a4ba-972aac937e56
## INFO  [14:32:41.360] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.372] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.375] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.423] [mlr3] Finished benchmark
## INFO  [14:32:41.434] [bbotk] Result of batch 27:
## INFO  [14:32:41.435] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.435] [bbotk]     8       500 0.7238244        0      0            0.043
## INFO  [14:32:41.435] [bbotk]                                 uhash
## INFO  [14:32:41.435] [bbotk]  44dbed11-afba-4b84-9354-a551646a4081
## INFO  [14:32:41.435] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.447] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.450] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.496] [mlr3] Finished benchmark
## INFO  [14:32:41.507] [bbotk] Result of batch 28:
## INFO  [14:32:41.508] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.508] [bbotk]     1       800  0.745543        0      0            0.042
## INFO  [14:32:41.508] [bbotk]                                 uhash
## INFO  [14:32:41.508] [bbotk]  9e187337-023a-4b53-a5cc-c04ffd77696a
## INFO  [14:32:41.509] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.524] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.527] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.566] [mlr3] Finished benchmark
## INFO  [14:32:41.577] [bbotk] Result of batch 29:
## INFO  [14:32:41.578] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.578] [bbotk]     1       600 0.7496199        0      0            0.035
## INFO  [14:32:41.578] [bbotk]                                 uhash
## INFO  [14:32:41.578] [bbotk]  3423cdf8-4388-4165-a966-2c31657d2fd4
## INFO  [14:32:41.578] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.588] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.591] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.634] [mlr3] Finished benchmark
## INFO  [14:32:41.645] [bbotk] Result of batch 30:
## INFO  [14:32:41.646] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.646] [bbotk]     7       500 0.7213873        0      0            0.039
## INFO  [14:32:41.646] [bbotk]                                 uhash
## INFO  [14:32:41.646] [bbotk]  c04d2e13-6657-4c9c-aa67-136a06dc1716
## INFO  [14:32:41.646] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.656] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.659] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.735] [mlr3] Finished benchmark
## INFO  [14:32:41.745] [bbotk] Result of batch 31:
## INFO  [14:32:41.746] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.746] [bbotk]     6      1000 0.7175184        0      0            0.072
## INFO  [14:32:41.746] [bbotk]                                 uhash
## INFO  [14:32:41.746] [bbotk]  54f571cf-3517-44b1-baf4-70f9a967c00f
## INFO  [14:32:41.746] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.756] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.759] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.786] [mlr3] Finished benchmark
## INFO  [14:32:41.808] [bbotk] Result of batch 32:
## INFO  [14:32:41.809] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.809] [bbotk]     6       300 0.7054488        0      0            0.024
## INFO  [14:32:41.809] [bbotk]                                 uhash
## INFO  [14:32:41.809] [bbotk]  4d520dc3-87a4-40bf-8b2c-0baf65696d83
## INFO  [14:32:41.809] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.819] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.822] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.867] [mlr3] Finished benchmark
## INFO  [14:32:41.878] [bbotk] Result of batch 33:
## INFO  [14:32:41.879] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.879] [bbotk]     3       700 0.7240963        0      0            0.042
## INFO  [14:32:41.879] [bbotk]                                 uhash
## INFO  [14:32:41.879] [bbotk]  6aa9e11f-6a6c-45e0-9fb8-c105f920e8a7
## INFO  [14:32:41.879] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.890] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.893] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:41.941] [mlr3] Finished benchmark
## INFO  [14:32:41.952] [bbotk] Result of batch 34:
## INFO  [14:32:41.952] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:41.952] [bbotk]     6       600 0.7164119        0      0            0.046
## INFO  [14:32:41.952] [bbotk]                                 uhash
## INFO  [14:32:41.952] [bbotk]  3b53e876-2ca9-4d2b-aad8-fb2d2d547559
## INFO  [14:32:41.953] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:41.963] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:41.965] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.016] [mlr3] Finished benchmark
## INFO  [14:32:42.027] [bbotk] Result of batch 35:
## INFO  [14:32:42.027] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.027] [bbotk]     1      1000 0.7348732        0      0            0.047
## INFO  [14:32:42.027] [bbotk]                                 uhash
## INFO  [14:32:42.027] [bbotk]  58e3292e-afdb-493b-bda2-4c7235e6f368
## INFO  [14:32:42.028] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.038] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.040] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.098] [mlr3] Finished benchmark
## INFO  [14:32:42.109] [bbotk] Result of batch 36:
## INFO  [14:32:42.109] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.109] [bbotk]     7       700 0.7185566        0      0            0.055
## INFO  [14:32:42.109] [bbotk]                                 uhash
## INFO  [14:32:42.109] [bbotk]  57c9dd35-53d0-4a58-ac0f-b0c847721aa2
## INFO  [14:32:42.110] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.120] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.122] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.159] [mlr3] Finished benchmark
## INFO  [14:32:42.170] [bbotk] Result of batch 37:
## INFO  [14:32:42.178] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.178] [bbotk]     1       700 0.7424947        0      0            0.034
## INFO  [14:32:42.178] [bbotk]                                 uhash
## INFO  [14:32:42.178] [bbotk]  f9d0e971-dcb1-4608-9045-48a3f3d23fd2
## INFO  [14:32:42.179] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.193] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.195] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.213] [mlr3] Finished benchmark
## INFO  [14:32:42.224] [bbotk] Result of batch 38:
## INFO  [14:32:42.224] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.224] [bbotk]     4       200 0.7187816        0      0            0.015
## INFO  [14:32:42.224] [bbotk]                                 uhash
## INFO  [14:32:42.224] [bbotk]  2fc8f814-0928-461a-a499-112627922938
## INFO  [14:32:42.225] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.234] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.237] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.266] [mlr3] Finished benchmark
## INFO  [14:32:42.277] [bbotk] Result of batch 39:
## INFO  [14:32:42.277] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.277] [bbotk]     8       300 0.7113794        0      0            0.025
## INFO  [14:32:42.277] [bbotk]                                 uhash
## INFO  [14:32:42.277] [bbotk]  c3cae716-dc79-430c-9161-91e1f44fd2b0
## INFO  [14:32:42.278] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.289] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.292] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.328] [mlr3] Finished benchmark
## INFO  [14:32:42.343] [bbotk] Result of batch 40:
## INFO  [14:32:42.345] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.345] [bbotk]     4       100 0.7303584        0      0            0.022
## INFO  [14:32:42.345] [bbotk]                                 uhash
## INFO  [14:32:42.345] [bbotk]  9972b28e-1b03-475d-9e47-fe2d1e1b1030
## INFO  [14:32:42.345] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.356] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.359] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.374] [mlr3] Finished benchmark
## INFO  [14:32:42.385] [bbotk] Result of batch 41:
## INFO  [14:32:42.386] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.386] [bbotk]     8       100 0.7009878        0      0             0.01
## INFO  [14:32:42.386] [bbotk]                                 uhash
## INFO  [14:32:42.386] [bbotk]  a6bdce71-5c44-434a-9e22-d0a4ade5fce9
## INFO  [14:32:42.386] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.396] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.399] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.415] [mlr3] Finished benchmark
## INFO  [14:32:42.426] [bbotk] Result of batch 42:
## INFO  [14:32:42.427] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.427] [bbotk]     1       200  0.727032        0      0            0.013
## INFO  [14:32:42.427] [bbotk]                                 uhash
## INFO  [14:32:42.427] [bbotk]  63575ddc-17f8-43cd-abe4-176acb66c020
## INFO  [14:32:42.427] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.437] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.440] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.492] [mlr3] Finished benchmark
## INFO  [14:32:42.520] [bbotk] Result of batch 43:
## INFO  [14:32:42.521] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.521] [bbotk]     8       600 0.7024033        0      0            0.048
## INFO  [14:32:42.521] [bbotk]                                 uhash
## INFO  [14:32:42.521] [bbotk]  d8e61e48-5eac-47f6-8671-e7a76743013a
## INFO  [14:32:42.522] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.533] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.536] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.595] [mlr3] Finished benchmark
## INFO  [14:32:42.606] [bbotk] Result of batch 44:
## INFO  [14:32:42.606] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.606] [bbotk]     2      1000 0.7364565        0      0            0.055
## INFO  [14:32:42.606] [bbotk]                                 uhash
## INFO  [14:32:42.606] [bbotk]  39d62cc9-fa1f-4b58-92ff-72d9164c341a
## INFO  [14:32:42.607] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.617] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.619] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.630] [mlr3] Finished benchmark
## INFO  [14:32:42.640] [bbotk] Result of batch 45:
## INFO  [14:32:42.641] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.641] [bbotk]     2       100 0.7370077        0      0            0.008
## INFO  [14:32:42.641] [bbotk]                                 uhash
## INFO  [14:32:42.641] [bbotk]  068fa4bb-c3eb-4bc1-9ae9-887ab58acf89
## INFO  [14:32:42.642] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.651] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.654] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.692] [mlr3] Finished benchmark
## INFO  [14:32:42.703] [bbotk] Result of batch 46:
## INFO  [14:32:42.703] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.703] [bbotk]     8       400 0.7066496        0      0            0.035
## INFO  [14:32:42.703] [bbotk]                                 uhash
## INFO  [14:32:42.703] [bbotk]  fb3d0ffc-efc7-43a6-b1ad-b72bcf2627d4
## INFO  [14:32:42.704] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.714] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.716] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.739] [mlr3] Finished benchmark
## INFO  [14:32:42.750] [bbotk] Result of batch 47:
## INFO  [14:32:42.750] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.750] [bbotk]     3       300 0.7195623        0      0            0.019
## INFO  [14:32:42.750] [bbotk]                                 uhash
## INFO  [14:32:42.750] [bbotk]  0647aefb-f7fc-4dae-b79c-f15bf3b8d3b9
## INFO  [14:32:42.751] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.760] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.763] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.813] [mlr3] Finished benchmark
## INFO  [14:32:42.824] [bbotk] Result of batch 48:
## INFO  [14:32:42.825] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.825] [bbotk]     3       800 0.7213499        0      0            0.046
## INFO  [14:32:42.825] [bbotk]                                 uhash
## INFO  [14:32:42.825] [bbotk]  3a60d1a6-2d35-4edb-9148-afde7a93a6c1
## INFO  [14:32:42.825] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.835] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.837] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.907] [mlr3] Finished benchmark
## INFO  [14:32:42.923] [bbotk] Result of batch 49:
## INFO  [14:32:42.924] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.924] [bbotk]     4       900 0.7187387        0      0            0.065
## INFO  [14:32:42.924] [bbotk]                                 uhash
## INFO  [14:32:42.924] [bbotk]  ea39f73a-91a9-4710-a9d5-94b3f4511c72
## INFO  [14:32:42.924] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:42.934] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:42.937] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:42.985] [mlr3] Finished benchmark
## INFO  [14:32:42.996] [bbotk] Result of batch 50:
## INFO  [14:32:42.997] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:42.997] [bbotk]     4       700 0.7240584        0      0            0.045
## INFO  [14:32:42.997] [bbotk]                                 uhash
## INFO  [14:32:42.997] [bbotk]  43f55add-240e-4cc1-8017-d832077808a3
## INFO  [14:32:42.999] [bbotk] Finished optimizing after 50 evaluation(s)
## INFO  [14:32:42.999] [bbotk] Result:
## INFO  [14:32:42.999] [bbotk]  mtry num.trees learner_param_vals  x_domain regr.rmse
## INFO  [14:32:42.999] [bbotk]     8       100          <list[4]> <list[2]> 0.7009878
## INFO  [14:32:43.026] [mlr3] Applying learner 'regr.ranger.tuned' on task 'con' (iter 3/3)
## INFO  [14:32:43.050] [bbotk] Starting to optimize 2 parameter(s) with '<TunerGridSearch>' and '<TerminatorEvals> [n_evals=50, k=0]'
## INFO  [14:32:43.051] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.061] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.064] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.095] [mlr3] Finished benchmark
## INFO  [14:32:43.104] [bbotk] Result of batch 1:
## INFO  [14:32:43.105] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.105] [bbotk]     2       500  1.106376        0      0            0.028
## INFO  [14:32:43.105] [bbotk]                                 uhash
## INFO  [14:32:43.105] [bbotk]  dcb56c13-bf5e-4b5c-ba25-70273f6b6eab
## INFO  [14:32:43.105] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.115] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.118] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.182] [mlr3] Finished benchmark
## INFO  [14:32:43.192] [bbotk] Result of batch 2:
## INFO  [14:32:43.193] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.193] [bbotk]     6       800  1.100087        0      0            0.061
## INFO  [14:32:43.193] [bbotk]                                 uhash
## INFO  [14:32:43.193] [bbotk]  b1afa784-a0bd-4ad8-ac7f-9c663500f052
## INFO  [14:32:43.194] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.204] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.206] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.265] [mlr3] Finished benchmark
## INFO  [14:32:43.280] [bbotk] Result of batch 3:
## INFO  [14:32:43.282] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.282] [bbotk]     1       900  1.103032        0      0            0.043
## INFO  [14:32:43.282] [bbotk]                                 uhash
## INFO  [14:32:43.282] [bbotk]  2ad8d571-8bed-4015-9c94-d51f80bea6d9
## INFO  [14:32:43.283] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.293] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.295] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.314] [mlr3] Finished benchmark
## INFO  [14:32:43.325] [bbotk] Result of batch 4:
## INFO  [14:32:43.326] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.326] [bbotk]     1       300  1.101552        0      0            0.016
## INFO  [14:32:43.326] [bbotk]                                 uhash
## INFO  [14:32:43.326] [bbotk]  42789549-2512-412e-978d-e0570fa53d88
## INFO  [14:32:43.326] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.336] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.339] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.376] [mlr3] Finished benchmark
## INFO  [14:32:43.386] [bbotk] Result of batch 5:
## INFO  [14:32:43.387] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.387] [bbotk]     2       600  1.102727        0      0            0.033
## INFO  [14:32:43.387] [bbotk]                                 uhash
## INFO  [14:32:43.387] [bbotk]  2702299c-930c-4954-b352-df030730daca
## INFO  [14:32:43.388] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.397] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.400] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.460] [mlr3] Finished benchmark
## INFO  [14:32:43.470] [bbotk] Result of batch 6:
## INFO  [14:32:43.471] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.471] [bbotk]     7       700  1.098613        0      0            0.056
## INFO  [14:32:43.471] [bbotk]                                 uhash
## INFO  [14:32:43.471] [bbotk]  33297851-94c8-4f03-81c1-d912f289c4ad
## INFO  [14:32:43.471] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.481] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.484] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.514] [mlr3] Finished benchmark
## INFO  [14:32:43.524] [bbotk] Result of batch 7:
## INFO  [14:32:43.525] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.525] [bbotk]     7       300  1.092679        0      0            0.026
## INFO  [14:32:43.525] [bbotk]                                 uhash
## INFO  [14:32:43.525] [bbotk]  54aa0e45-16bc-4077-8e70-713e3cce7da8
## INFO  [14:32:43.525] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.535] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.538] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.582] [mlr3] Finished benchmark
## INFO  [14:32:43.593] [bbotk] Result of batch 8:
## INFO  [14:32:43.593] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.593] [bbotk]     2       700  1.103477        0      0            0.041
## INFO  [14:32:43.593] [bbotk]                                 uhash
## INFO  [14:32:43.593] [bbotk]  6273705b-9947-4bd0-9d4d-3938258da290
## INFO  [14:32:43.594] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.604] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.614] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.667] [mlr3] Finished benchmark
## INFO  [14:32:43.680] [bbotk] Result of batch 9:
## INFO  [14:32:43.681] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.681] [bbotk]     4       700   1.10224        0      0            0.047
## INFO  [14:32:43.681] [bbotk]                                 uhash
## INFO  [14:32:43.681] [bbotk]  2df047c1-ff39-4006-878d-62d1dd45ac0c
## INFO  [14:32:43.681] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.691] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.694] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.706] [mlr3] Finished benchmark
## INFO  [14:32:43.716] [bbotk] Result of batch 10:
## INFO  [14:32:43.717] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.717] [bbotk]     4       100  1.093353        0      0            0.009
## INFO  [14:32:43.717] [bbotk]                                 uhash
## INFO  [14:32:43.717] [bbotk]  2276bd38-8e5a-445c-a6a1-338fbff8d620
## INFO  [14:32:43.717] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.727] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.729] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.795] [mlr3] Finished benchmark
## INFO  [14:32:43.806] [bbotk] Result of batch 11:
## INFO  [14:32:43.807] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.807] [bbotk]     5       900  1.103731        0      0            0.062
## INFO  [14:32:43.807] [bbotk]                                 uhash
## INFO  [14:32:43.807] [bbotk]  7d645ac7-dc5f-43f3-bec5-f1c49ddf8bdd
## INFO  [14:32:43.807] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.817] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.820] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.839] [mlr3] Finished benchmark
## INFO  [14:32:43.849] [bbotk] Result of batch 12:
## INFO  [14:32:43.850] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.850] [bbotk]     5       200  1.113661        0      0            0.016
## INFO  [14:32:43.850] [bbotk]                                 uhash
## INFO  [14:32:43.850] [bbotk]  84e1893a-acc2-4653-b62f-364b8f5bf533
## INFO  [14:32:43.850] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.860] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.863] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.893] [mlr3] Finished benchmark
## INFO  [14:32:43.904] [bbotk] Result of batch 13:
## INFO  [14:32:43.904] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.904] [bbotk]     4       400  1.105698        0      0            0.027
## INFO  [14:32:43.904] [bbotk]                                 uhash
## INFO  [14:32:43.904] [bbotk]  08cf7184-2c98-4f4a-be32-05045c841a6d
## INFO  [14:32:43.905] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:43.915] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:43.917] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:43.966] [mlr3] Finished benchmark
## INFO  [14:32:43.989] [bbotk] Result of batch 14:
## INFO  [14:32:43.990] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:43.990] [bbotk]     6       600  1.105791        0      0            0.045
## INFO  [14:32:43.990] [bbotk]                                 uhash
## INFO  [14:32:43.990] [bbotk]  ba2c94a5-f279-4c04-8a86-27ae79a9c503
## INFO  [14:32:43.991] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.007] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.010] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.047] [mlr3] Finished benchmark
## INFO  [14:32:44.057] [bbotk] Result of batch 15:
## INFO  [14:32:44.058] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.058] [bbotk]     1       700  1.110738        0      0            0.033
## INFO  [14:32:44.058] [bbotk]                                 uhash
## INFO  [14:32:44.058] [bbotk]  40075bda-21a4-4b85-9a87-0e9a7e1462ae
## INFO  [14:32:44.059] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.068] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.071] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.144] [mlr3] Finished benchmark
## INFO  [14:32:44.154] [bbotk] Result of batch 16:
## INFO  [14:32:44.155] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.155] [bbotk]     5      1000  1.109785        0      0             0.07
## INFO  [14:32:44.155] [bbotk]                                 uhash
## INFO  [14:32:44.155] [bbotk]  067e8734-c2a8-43f1-bfdf-276c9d8da7ca
## INFO  [14:32:44.156] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.165] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.168] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.224] [mlr3] Finished benchmark
## INFO  [14:32:44.235] [bbotk] Result of batch 17:
## INFO  [14:32:44.235] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.235] [bbotk]     3       900  1.102015        0      0            0.053
## INFO  [14:32:44.235] [bbotk]                                 uhash
## INFO  [14:32:44.235] [bbotk]  64bfb2e9-5b0b-42b6-b5f1-40abab5e3b8c
## INFO  [14:32:44.236] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.246] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.248] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.272] [mlr3] Finished benchmark
## INFO  [14:32:44.283] [bbotk] Result of batch 18:
## INFO  [14:32:44.283] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.283] [bbotk]     4       300  1.097695        0      0            0.021
## INFO  [14:32:44.283] [bbotk]                                 uhash
## INFO  [14:32:44.283] [bbotk]  aa6a3c48-bd4e-40b4-a7cc-3e24f3178ac2
## INFO  [14:32:44.284] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.293] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.296] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.314] [mlr3] Finished benchmark
## INFO  [14:32:44.325] [bbotk] Result of batch 19:
## INFO  [14:32:44.325] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.325] [bbotk]     4       200   1.11157        0      0            0.015
## INFO  [14:32:44.325] [bbotk]                                 uhash
## INFO  [14:32:44.325] [bbotk]  d716e261-0fe4-4818-bb8a-28b6d61e9ae3
## INFO  [14:32:44.326] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.336] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.338] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.404] [mlr3] Finished benchmark
## INFO  [14:32:44.420] [bbotk] Result of batch 20:
## INFO  [14:32:44.421] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.421] [bbotk]     2      1000  1.101042        0      0            0.061
## INFO  [14:32:44.421] [bbotk]                                 uhash
## INFO  [14:32:44.421] [bbotk]  2865adab-58b1-4734-97ab-ee71b7a455ef
## INFO  [14:32:44.422] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.432] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.434] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.445] [mlr3] Finished benchmark
## INFO  [14:32:44.455] [bbotk] Result of batch 21:
## INFO  [14:32:44.456] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.456] [bbotk]     2       100  1.087811        0      0            0.007
## INFO  [14:32:44.456] [bbotk]                                 uhash
## INFO  [14:32:44.456] [bbotk]  15d87241-5d34-4ae5-ba9d-d5bb0a650d1c
## INFO  [14:32:44.457] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.466] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.469] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.524] [mlr3] Finished benchmark
## INFO  [14:32:44.535] [bbotk] Result of batch 22:
## INFO  [14:32:44.536] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.536] [bbotk]     4       800  1.100455        0      0            0.052
## INFO  [14:32:44.536] [bbotk]                                 uhash
## INFO  [14:32:44.536] [bbotk]  fca31571-3fc7-46a1-ace3-a583b8ec5f53
## INFO  [14:32:44.536] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.546] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.549] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.616] [mlr3] Finished benchmark
## INFO  [14:32:44.627] [bbotk] Result of batch 23:
## INFO  [14:32:44.628] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.628] [bbotk]     4      1000  1.106259        0      0            0.064
## INFO  [14:32:44.628] [bbotk]                                 uhash
## INFO  [14:32:44.628] [bbotk]  2d7037e5-c31a-4d38-84d8-c77988bdbe20
## INFO  [14:32:44.628] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.638] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.641] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.691] [mlr3] Finished benchmark
## INFO  [14:32:44.702] [bbotk] Result of batch 24:
## INFO  [14:32:44.702] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.702] [bbotk]     1      1000   1.10189        0      0            0.046
## INFO  [14:32:44.702] [bbotk]                                 uhash
## INFO  [14:32:44.702] [bbotk]  32ecad2c-9e92-40cc-a84a-fa8a36b95f8a
## INFO  [14:32:44.703] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.713] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.715] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.785] [mlr3] Finished benchmark
## INFO  [14:32:44.801] [bbotk] Result of batch 25:
## INFO  [14:32:44.802] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.802] [bbotk]     4       900  1.102887        0      0            0.067
## INFO  [14:32:44.802] [bbotk]                                 uhash
## INFO  [14:32:44.802] [bbotk]  468be9b8-68e6-4071-981f-1781ef280df2
## INFO  [14:32:44.803] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.813] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.816] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.878] [mlr3] Finished benchmark
## INFO  [14:32:44.889] [bbotk] Result of batch 26:
## INFO  [14:32:44.889] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.889] [bbotk]     3      1000  1.104363        0      0            0.058
## INFO  [14:32:44.889] [bbotk]                                 uhash
## INFO  [14:32:44.889] [bbotk]  133fe85b-ce70-41e3-a085-61c3134bac9b
## INFO  [14:32:44.890] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.900] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.902] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:44.930] [mlr3] Finished benchmark
## INFO  [14:32:44.940] [bbotk] Result of batch 27:
## INFO  [14:32:44.941] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:44.941] [bbotk]     6       300  1.110621        0      0            0.025
## INFO  [14:32:44.941] [bbotk]                                 uhash
## INFO  [14:32:44.941] [bbotk]  0fad801d-39f1-4e6d-ac58-c4d76e2cbeaa
## INFO  [14:32:44.941] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:44.951] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:44.954] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.032] [mlr3] Finished benchmark
## INFO  [14:32:45.042] [bbotk] Result of batch 28:
## INFO  [14:32:45.043] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.043] [bbotk]     6      1000  1.094507        0      0            0.074
## INFO  [14:32:45.043] [bbotk]                                 uhash
## INFO  [14:32:45.043] [bbotk]  d315c688-f3e4-4efe-89be-a1798792fa59
## INFO  [14:32:45.043] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.053] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.056] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.104] [mlr3] Finished benchmark
## INFO  [14:32:45.115] [bbotk] Result of batch 29:
## INFO  [14:32:45.115] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.115] [bbotk]     2       800  1.102697        0      0            0.044
## INFO  [14:32:45.115] [bbotk]                                 uhash
## INFO  [14:32:45.115] [bbotk]  6769445f-468e-46c4-a1ae-a81b9a50e6d9
## INFO  [14:32:45.116] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.126] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.129] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.400] [mlr3] Finished benchmark
## INFO  [14:32:45.411] [bbotk] Result of batch 30:
## INFO  [14:32:45.411] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.411] [bbotk]     1       800  1.109569        0      0            0.267
## INFO  [14:32:45.411] [bbotk]                                 uhash
## INFO  [14:32:45.411] [bbotk]  d4512b50-3c09-4967-bb0a-4c5ecbd1c67d
## INFO  [14:32:45.412] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.421] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.424] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.509] [mlr3] Finished benchmark
## INFO  [14:32:45.520] [bbotk] Result of batch 31:
## INFO  [14:32:45.520] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.520] [bbotk]     7      1000  1.101085        0      0            0.081
## INFO  [14:32:45.520] [bbotk]                                 uhash
## INFO  [14:32:45.520] [bbotk]  14496597-a7db-4357-8dab-6272a09c297b
## INFO  [14:32:45.521] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.530] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.533] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.621] [mlr3] Finished benchmark
## INFO  [14:32:45.631] [bbotk] Result of batch 32:
## INFO  [14:32:45.632] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.632] [bbotk]     8      1000  1.104422        0      0            0.085
## INFO  [14:32:45.632] [bbotk]                                 uhash
## INFO  [14:32:45.632] [bbotk]  5ab67d9a-917e-4ef9-af3a-d0c0ecf75710
## INFO  [14:32:45.632] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.642] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.644] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.661] [mlr3] Finished benchmark
## INFO  [14:32:45.672] [bbotk] Result of batch 33:
## INFO  [14:32:45.672] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.672] [bbotk]     3       200  1.107225        0      0            0.014
## INFO  [14:32:45.672] [bbotk]                                 uhash
## INFO  [14:32:45.672] [bbotk]  ce8b297e-2ceb-4c27-90c0-34ba3d8bbbb3
## INFO  [14:32:45.673] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.682] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.685] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.747] [mlr3] Finished benchmark
## INFO  [14:32:45.757] [bbotk] Result of batch 34:
## INFO  [14:32:45.758] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.758] [bbotk]     8       700  1.091179        0      0            0.059
## INFO  [14:32:45.758] [bbotk]                                 uhash
## INFO  [14:32:45.758] [bbotk]  330038c9-5587-4ba6-b127-5d54fcc84a8c
## INFO  [14:32:45.759] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.768] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.771] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.791] [mlr3] Finished benchmark
## INFO  [14:32:45.802] [bbotk] Result of batch 35:
## INFO  [14:32:45.803] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.803] [bbotk]     2       300  1.108993        0      0            0.017
## INFO  [14:32:45.803] [bbotk]                                 uhash
## INFO  [14:32:45.803] [bbotk]  31b6d7b7-7405-4d6e-a7e8-ead9a60d555c
## INFO  [14:32:45.803] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.820] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.823] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.897] [mlr3] Finished benchmark
## INFO  [14:32:45.908] [bbotk] Result of batch 36:
## INFO  [14:32:45.908] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.908] [bbotk]     7       900  1.097686        0      0             0.07
## INFO  [14:32:45.908] [bbotk]                                 uhash
## INFO  [14:32:45.908] [bbotk]  20db917e-5259-4ad7-8595-b084af93b90e
## INFO  [14:32:45.909] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.918] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.921] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:45.947] [mlr3] Finished benchmark
## INFO  [14:32:45.957] [bbotk] Result of batch 37:
## INFO  [14:32:45.958] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:45.958] [bbotk]     5       300  1.110051        0      0            0.023
## INFO  [14:32:45.958] [bbotk]                                 uhash
## INFO  [14:32:45.958] [bbotk]  166c3781-0e3b-41bc-8990-a25b409e7d19
## INFO  [14:32:45.958] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:45.968] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:45.970] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.016] [mlr3] Finished benchmark
## INFO  [14:32:46.027] [bbotk] Result of batch 38:
## INFO  [14:32:46.027] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.027] [bbotk]     3       700   1.10818        0      0            0.042
## INFO  [14:32:46.027] [bbotk]                                 uhash
## INFO  [14:32:46.027] [bbotk]  a9cbbabd-8858-4611-9fbd-6447a0fdaf87
## INFO  [14:32:46.028] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.037] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.040] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.078] [mlr3] Finished benchmark
## INFO  [14:32:46.089] [bbotk] Result of batch 39:
## INFO  [14:32:46.089] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.089] [bbotk]     8       400  1.089953        0      0            0.034
## INFO  [14:32:46.089] [bbotk]                                 uhash
## INFO  [14:32:46.089] [bbotk]  687e29ab-793e-47e2-925f-11697eac315f
## INFO  [14:32:46.090] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.099] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.102] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.138] [mlr3] Finished benchmark
## INFO  [14:32:46.148] [bbotk] Result of batch 40:
## INFO  [14:32:46.149] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.149] [bbotk]     7       400  1.105257        0      0            0.033
## INFO  [14:32:46.149] [bbotk]                                 uhash
## INFO  [14:32:46.149] [bbotk]  0d34ab31-655b-4143-b0dd-52d3e970e602
## INFO  [14:32:46.150] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.159] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.162] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.214] [mlr3] Finished benchmark
## INFO  [14:32:46.224] [bbotk] Result of batch 41:
## INFO  [14:32:46.225] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.225] [bbotk]     7       600  1.099824        0      0            0.048
## INFO  [14:32:46.225] [bbotk]                                 uhash
## INFO  [14:32:46.225] [bbotk]  90a074aa-a438-4730-a36f-67ab739572f0
## INFO  [14:32:46.226] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.242] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.244] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.275] [mlr3] Finished benchmark
## INFO  [14:32:46.285] [bbotk] Result of batch 42:
## INFO  [14:32:46.286] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.286] [bbotk]     8       300   1.10567        0      0            0.028
## INFO  [14:32:46.286] [bbotk]                                 uhash
## INFO  [14:32:46.286] [bbotk]  04836c5c-b6a3-48a0-9f67-4e75c40c6c82
## INFO  [14:32:46.286] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.296] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.298] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.332] [mlr3] Finished benchmark
## INFO  [14:32:46.342] [bbotk] Result of batch 43:
## INFO  [14:32:46.343] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.343] [bbotk]     3       500  1.091784        0      0             0.03
## INFO  [14:32:46.343] [bbotk]                                 uhash
## INFO  [14:32:46.343] [bbotk]  f26f7fd6-2c1a-4065-9181-0d4688dde5fc
## INFO  [14:32:46.343] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.353] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.355] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.370] [mlr3] Finished benchmark
## INFO  [14:32:46.380] [bbotk] Result of batch 44:
## INFO  [14:32:46.380] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.380] [bbotk]     1       200  1.112238        0      0            0.011
## INFO  [14:32:46.380] [bbotk]                                 uhash
## INFO  [14:32:46.380] [bbotk]  0d8c10d0-56e4-4bee-92e8-59cf7baec5cd
## INFO  [14:32:46.381] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.390] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.393] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.415] [mlr3] Finished benchmark
## INFO  [14:32:46.426] [bbotk] Result of batch 45:
## INFO  [14:32:46.426] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.426] [bbotk]     3       300  1.133347        0      0            0.019
## INFO  [14:32:46.426] [bbotk]                                 uhash
## INFO  [14:32:46.426] [bbotk]  fbf1a1c4-0a08-449d-a081-20b3ba9de080
## INFO  [14:32:46.427] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.436] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.439] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.466] [mlr3] Finished benchmark
## INFO  [14:32:46.477] [bbotk] Result of batch 46:
## INFO  [14:32:46.478] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.478] [bbotk]     1       500  1.111396        0      0            0.024
## INFO  [14:32:46.478] [bbotk]                                 uhash
## INFO  [14:32:46.478] [bbotk]  7bca6877-0446-47b5-8b0c-1b6b98e6c053
## INFO  [14:32:46.478] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.488] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.491] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.504] [mlr3] Finished benchmark
## INFO  [14:32:46.515] [bbotk] Result of batch 47:
## INFO  [14:32:46.515] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.515] [bbotk]     6       100  1.083011        0      0            0.011
## INFO  [14:32:46.515] [bbotk]                                 uhash
## INFO  [14:32:46.515] [bbotk]  89158315-1fe5-4d2f-8bd8-605d1a8550d5
## INFO  [14:32:46.516] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.531] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.534] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.567] [mlr3] Finished benchmark
## INFO  [14:32:46.577] [bbotk] Result of batch 48:
## INFO  [14:32:46.578] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.578] [bbotk]     1       600  1.100478        0      0             0.03
## INFO  [14:32:46.578] [bbotk]                                 uhash
## INFO  [14:32:46.578] [bbotk]  579eb40b-9dd3-44d3-9ebc-babf9bce7e35
## INFO  [14:32:46.579] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.588] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.591] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.642] [mlr3] Finished benchmark
## INFO  [14:32:46.652] [bbotk] Result of batch 49:
## INFO  [14:32:46.653] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.653] [bbotk]     2       900  1.089838        0      0            0.049
## INFO  [14:32:46.653] [bbotk]                                 uhash
## INFO  [14:32:46.653] [bbotk]  a1d8bbb4-4d31-4cdc-b774-bdb11f9ade64
## INFO  [14:32:46.653] [bbotk] Evaluating 1 configuration(s)
## INFO  [14:32:46.663] [mlr3] Running benchmark with 1 resampling iterations
## INFO  [14:32:46.666] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)
## INFO  [14:32:46.686] [mlr3] Finished benchmark
## INFO  [14:32:46.697] [bbotk] Result of batch 50:
## INFO  [14:32:46.697] [bbotk]  mtry num.trees regr.rmse warnings errors runtime_learners
## INFO  [14:32:46.697] [bbotk]     7       200  1.058964        0      0            0.017
## INFO  [14:32:46.697] [bbotk]                                 uhash
## INFO  [14:32:46.697] [bbotk]  51e036f2-424e-4983-9823-1daa69a5209e
## INFO  [14:32:46.699] [bbotk] Finished optimizing after 50 evaluation(s)
## INFO  [14:32:46.699] [bbotk] Result:
## INFO  [14:32:46.700] [bbotk]  mtry num.trees learner_param_vals  x_domain regr.rmse
## INFO  [14:32:46.700] [bbotk]     7       200          <list[4]> <list[2]>  1.058964

##Check performance measures
c_rf.2$score(measure)

task	task_id	learner	learner_id	resampling	resampling_id	iteration	prediction	regr.rmse
<environment>	con	<environment>	regr.ranger.tuned	<environment>	cv	1	<environment>	0.887
<environment>	con	<environment>	regr.ranger.tuned	<environment>	cv	2	<environment>	1.14
<environment>	con	<environment>	regr.ranger.tuned	<environment>	cv	3	<environment>	1.14

c_rf.2$aggregate(measure)

## regr.rmse 
##  1.056213

##Goes from under predicting to over predicting.

Variable Importance and Partial Dependency Plots

##Load libraries
library(vip)
library(pdp)

##Visualize the un-tuned model - since it performed better
vip(c_rf$learners[[1]]$model)

**PDP Plots

## Define a helper function to plot


pdp.plot = function(x){
  partial(c_rf$learners[[1]]$model, 
        pred.var = x, prob = TRUE, 
        train = hma.con.df.long, plot = TRUE, which.class = 2)
}

## Define a loop to plot all of the variables
## pdp.plot is the helper function
## This plot the relative weights? in the SOM?

lapply(names(hma.con.df.long[,2:15]), pdp.plot)

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partial(c_rf$learners[[1]]$model, 
        pred.var = "polstab", prob = TRUE, 
        train = hma.con.df.long, plot = TRUE, which.class = 2)

Mixed Effects Model

##Set countries as a factor
hma.con.df.long$country = as.factor(hma.con.df.long$country)

##Set year as a number
hma.con.df.long$year = as.numeric(hma.con.df.long$year)

##Check
str(hma.con.df.long)

## tibble [156 × 16] (S3: tbl_df/tbl/data.frame)
##  $ country  : Factor w/ 12 levels "Afghanistan",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ year     : num [1:156] 2010 2011 2012 2013 2014 ...
##  $ gdp      : num [1:156] 1.56e+10 1.82e+10 2.02e+10 2.06e+10 2.06e+10 ...
##  $ pop      : int [1:156] 28189672 29249157 30466479 31541209 32716210 33753499 34636207 35643418 36686784 37769499 ...
##  $ temp     : num [1:156] 1.613 1.397 0.223 1.281 0.456 ...
##  $ cd       : int [1:156] 4 4 10 5 3 5 4 5 5 7 ...
##  $ ge       : num [1:156] -1.48 -1.48 -1.38 -1.4 -1.36 -1.35 -1.25 -1.36 -1.48 -1.5 ...
##  $ con      : int [1:156] 10727 10727 10727 10727 10727 10727 10727 13363 14135 13908 ...
##  $ cpt      : num [1:156] -1.65 -1.6 -1.43 -1.45 -1.36 -1.35 -1.54 -1.53 -1.5 -1.42 ...
##  $ rol      : num [1:156] -1.87 -1.92 -1.65 -1.61 -1.44 -1.52 -1.52 -1.58 -1.69 -1.74 ...
##  $ rq       : num [1:156] -1.52 -1.54 -1.19 -1.19 -1.12 -1.02 -1.34 -1.37 -1.14 -1.11 ...
##  $ polstab  : num [1:156] -2.58 -2.5 -2.42 -2.52 -2.41 -2.56 -2.66 -2.79 -2.75 -2.65 ...
##  $ voice    : num [1:156] -1.4 -1.34 -1.27 -1.24 -1.14 -1.12 -1.04 -0.99 -1.01 -1.01 ...
##  $ urbanpop : num [1:156] 23.7 23.9 24.2 24.4 24.6 ...
##  $ waterwith: num [1:156] 43 43 43 43 43 ...
##  $ zscore   : num [1:156] -5.57e-05 -5.57e-05 -5.57e-05 -5.57e-05 -5.57e-05 ...

##Use the orignal dataframe
con.df.sub = subset(hma.con.df.long, select = -c(country, year))

##Correlation Matrix

ggcorrplot(cor(con.df.sub), 
           method = "square",
           type = "full",
           lab = TRUE,
           colors = c("blue", "darksalmon", "firebrick"))

##Intercept model
fit0 = lm(zscore ~ 1, data = hma.con.df.long)

##Summary
summary(fit0)

## 
## Call:
## lm(formula = zscore ~ 1, data = hma.con.df.long)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.84360 -0.39078  0.00000  0.04863  2.59412 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.291e-17  7.717e-02       0        1
## 
## Residual standard error: 0.9639 on 155 degrees of freedom

#load nlme and lme4 library
library(nlme)
library(lme4)

## glm mixed effects model
fit1 = lme(zscore ~ gdp + pop + temp + cd + urbanpop + ge + cpt + voice + waterwith + rol + rq,
           random = ~1|country,
            data = hma.con.df.long)

## summary 
summary(fit1)

## Linear mixed-effects model fit by REML
##   Data: hma.con.df.long 
##        AIC      BIC    logLik
##   597.3038 638.8812 -284.6519
## 
## Random effects:
##  Formula: ~1 | country
##          (Intercept)  Residual
## StdDev: 5.073436e-05 0.9955829
## 
## Fixed effects:  zscore ~ gdp + pop + temp + cd + urbanpop + ge + cpt + voice +      waterwith + rol + rq 
##                   Value Std.Error  DF    t-value p-value
## (Intercept)  0.03990625 0.6541843 133  0.0610015  0.9514
## gdp          0.00000000 0.0000000 133 -0.5271065  0.5990
## pop          0.00000000 0.0000000 133 -0.1790470  0.8582
## temp        -0.07117989 0.1854714 133 -0.3837782  0.7018
## cd           0.00669958 0.0240325 133  0.2787720  0.7809
## urbanpop     0.00432436 0.0165255 133  0.2616779  0.7940
## ge           0.14446610 0.4339839 133  0.3328835  0.7397
## cpt         -0.10593215 0.3449181 133 -0.3071226  0.7592
## voice       -0.02617580 0.3059048 133 -0.0855684  0.9319
## waterwith    0.00001343 0.0002532 133  0.0530599  0.9578
## rol         -0.04618158 0.5928863 133 -0.0778928  0.9380
## rq           0.16164701 0.3424619 133  0.4720146  0.6377
##  Correlation: 
##           (Intr) gdp    pop    temp   cd     urbnpp ge     cpt    voice  wtrwth
## gdp        0.133                                                               
## pop       -0.147 -0.506                                                        
## temp      -0.095 -0.029 -0.023                                                 
## cd        -0.124 -0.040 -0.647  0.181                                          
## urbanpop  -0.860 -0.141  0.015 -0.250  0.061                                   
## ge         0.397  0.111 -0.218  0.010  0.029 -0.440                            
## cpt       -0.168 -0.169  0.483 -0.210 -0.232  0.136 -0.228                     
## voice     -0.453  0.515 -0.245  0.015  0.074  0.400  0.166  0.021              
## waterwith  0.593  0.168 -0.104 -0.033  0.002 -0.498  0.072  0.076 -0.160       
## rol        0.127 -0.074 -0.239  0.233  0.215 -0.078 -0.420 -0.658 -0.451 -0.024
## rq         0.403 -0.305  0.126 -0.167 -0.157 -0.127 -0.221  0.203 -0.558  0.500
##           rol   
## gdp             
## pop             
## temp            
## cd              
## urbanpop        
## ge              
## cpt             
## voice           
## waterwith       
## rol             
## rq         0.029
## 
## Standardized Within-Group Residuals:
##         Min          Q1         Med          Q3         Max 
## -2.73863380 -0.33399965 -0.03054631  0.10928850  2.51871516 
## 
## Number of Observations: 156
## Number of Groups: 12

Re-Analysis without imputed year

This section of code drops observations that use estimated conflict counts for countries without data in ACLED. The list below denotes when data collection began: - Afghanistan: 2017 - Bangladesh: 2010 - Bhutan: 2020 - China: 2018 - India: 2016 - Kyrgyz Republic: 2018 - Nepal: 2010 - Pakistan: 2010 - Myanmar: 2010 - Tajikistan: 2018 - Turkmenistan: 2018 - Uzbekistan: 2018

## Duplicate the long dataframe
con2 = hma.con.df.long

##Test 
##subset dataframe based on Afghanistan and years 2017 and on
afg = subset(con2, con2$country == 'Afghanistan' & con2$year >= 2017)

##check
view(afg)

##Subset all of the other countries
##subset dataframe based on Bangladesh and years 2010 and on
ban = subset(con2, con2$country == 'Bangladesh' & con2$year >= 2010)

##subset dataframe based on Bangladesh and years 2020 and on
bhu = subset(con2, con2$country == 'Bhutan' & con2$year >= 2020)

##subset dataframe based on China and years 2018 and on
chi = subset(con2, con2$country == 'China' & con2$year >= 2018)

##subset dataframe based on India and years 2016 and on
ind = subset(con2, con2$country == 'India' & con2$year >= 2016)

##subset dataframe based on Kyrgyz Republic and years 2018 and on
kyr = subset(con2, con2$country == 'Kyrgyz Republic' & con2$year >= 2018)

##subset dataframe based on Nepal and years 2010 and on
nep = subset(con2, con2$country == 'Nepal' & con2$year >= 2010)

##subset dataframe based on Pakistan and years 2010 and on
pak = subset(con2, con2$country == 'Pakistan' & con2$year >= 2010)

##subset dataframe based on Myanmar and years 2010 and on
mya = subset(con2, con2$country == 'Myanmar' & con2$year >= 2010)

##subset dataframe based on Tajikistan and years 2010 and on
taj = subset(con2, con2$country == 'Tajikistan' & con2$year >= 2018)

##subset dataframe based on Turkmenistan and years 2010 and on
tur = subset(con2, con2$country == 'Turkmenistan' & con2$year >= 2018)

##subset dataframe based on Uzbekistan and years 2010 and on
uzb = subset(con2, con2$country == 'Uzbekistan' & con2$year >= 2018)

##Merge all of the countries back together into one dataframe

##Merge by rows using rbind
con.reduced = rbind(afg, ban, bhu, chi, ind, kyr, nep, pak, mya, taj, tur, uzb)

##Check
view(con.reduced)

##Zero out the zscore column
con.reduced$zscore = NA

##Recalculate Z scores
con.reduced[con.reduced$country == 'Afghanistan', 'zscore'] = scale(con.reduced[con.reduced$country == 'Afghanistan', 'con'], center = TRUE, scale = TRUE)


## Check
con.reduced[con.reduced$country == 'Afghanistan', 'zscore']

zscore
0.617
0.797
0.744
-0.0908
-0.231
-1.84

## recalculate

con.reduced[con.reduced$country == 'Bangladesh', 'zscore'] = scale(con.reduced[con.reduced$country == 'Bangladesh', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'Bhutan', 'zscore'] = scale(con.reduced[con.reduced$country == 'Bhutan', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'China', 'zscore'] = scale(con.reduced[con.reduced$country == 'China', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'India', 'zscore'] = scale(con.reduced[con.reduced$country == 'India', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'Kyrgyz Republic', 'zscore'] = scale(con.reduced[con.reduced$country == 'Kyrgyz Republic', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'Myanmar', 'zscore'] = scale(con.reduced[con.reduced$country == 'Myanmar', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'Nepal', 'zscore'] = scale(con.reduced[con.reduced$country == 'Nepal', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'Pakistan', 'zscore'] = scale(con.reduced[con.reduced$country == 'Pakistan', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'Tajikistan', 'zscore'] = scale(con.reduced[con.reduced$country == 'Tajikistan', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'Turkmenistan', 'zscore'] = scale(con.reduced[con.reduced$country == 'Turkmenistan', 'con'], center = TRUE, scale = TRUE)

con.reduced[con.reduced$country == 'Uzbekistan', 'zscore'] = scale(con.reduced[con.reduced$country == 'Uzbekistan', 'con'], center = TRUE, scale = TRUE)


## Check
view(con.reduced)

Random Forest Redo

#Define the task
task_con2 = TaskRegr$new(id = "con2",
                        backend = con.reduced,
                        target = "zscore")

# Task details
task_con2$col_roles

## $feature
##  [1] "cd"        "con"       "country"   "cpt"       "gdp"       "ge"       
##  [7] "polstab"   "pop"       "rol"       "rq"        "temp"      "urbanpop" 
## [13] "voice"     "waterwith" "year"     
## 
## $target
## [1] "zscore"
## 
## $name
## character(0)
## 
## $order
## character(0)
## 
## $stratum
## character(0)
## 
## $group
## character(0)
## 
## $weight
## character(0)

#if necessary exclude features here
## Exclude country***
task_con2$col_roles$feature = setdiff(task_con2$col_roles$feature,
                                          c("country", "con", "polstab"))


## Check
task_con2$col_roles

## $feature
##  [1] "cd"        "cpt"       "gdp"       "ge"        "pop"       "rol"      
##  [7] "rq"        "temp"      "urbanpop"  "voice"     "waterwith" "year"     
## 
## $target
## [1] "zscore"
## 
## $name
## character(0)
## 
## $order
## character(0)
## 
## $stratum
## character(0)
## 
## $group
## character(0)
## 
## $weight
## character(0)

##Define the performance measure
##Regression Task
##additional measures can be found with msr()

measure2 = msr("regr.rmse")

#Define the learner
lrn_rf2 = lrn("regr.ranger",
             predict_type = "response",
             importance = "permutation")

## Define the resampling method
## 1st Run - Simple holdout 0.8
resamp_hout2 = rsmp("holdout",
                   ratio = 0.8)


## Instantiate the resampling method
resamp_hout2$instantiate(task_con2)

## Run the resampler/model
##con = conflict

c_rf2 = resample(task = task_con2,
                 learner = lrn_rf2,
                 resampling = resamp_hout2,
                 store_models = TRUE)

## INFO  [14:32:50.678] [mlr3] Applying learner 'regr.ranger' on task 'con2' (iter 1/1)

## Check the performace measures
c_rf2$score(measure2)

task	task_id	learner	learner_id	resampling	resampling_id	iteration	prediction	regr.rmse
<environment>	con2	<environment>	regr.ranger	<environment>	holdout	1	<environment>	0.943

##Convert the RMSE to a percentage
rmse2 = c_rf2$score(measure2)

##Percentage Conversion
rmse2 = (rmse2$regr.rmse / mean(con.reduced$zscore)) * 100

##Show RMSE
print(rmse2)

## [1] -7.824179e+17

##Visualize the un-tuned model - since it performed better
vip(c_rf2$learners[[1]]$model)

## Define a loop to plot all of the variables
## pdp.plot is the helper function
## This plot the relative weights? in the SOM?

lapply(names(con.reduced[,2:15]), pdp.plot)

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Administrative Level 1 Analysis

The code below conducts a data analysis of conflict by country at the administrative level 1 boundary.

This analysis uses the province dataframe (prov.df) which already has missing values for nlights (night time lights) and conflict imputed using missForest.

##Use the orignal dataframe
prov.sub = subset(prov.df, select = -c(country, year, adm1))

##Correlation Matrix

ggcorrplot(cor(prov.sub), 
           method = "square",
           type = "full",
           lab = TRUE,
           colors = c("blue", "darksalmon", "firebrick"))

#Define the task
task_prov = TaskRegr$new(id = "con",
                        backend = prov.df,
                        target = "con")

# Task details
task_prov$col_roles

## $feature
##  [1] "adm1"    "country" "cpt"     "ge"      "nlights" "polstab" "pop"    
##  [8] "precip"  "rol"     "rq"      "temp"    "voice"   "year"   
## 
## $target
## [1] "con"
## 
## $name
## character(0)
## 
## $order
## character(0)
## 
## $stratum
## character(0)
## 
## $group
## character(0)
## 
## $weight
## character(0)

#if necessary exclude features here
## 
task_prov$col_roles$feature = setdiff(task_prov$col_roles$feature,
                                          c("country", "year"))


## Check
task_prov$col_roles

## $feature
##  [1] "adm1"    "cpt"     "ge"      "nlights" "polstab" "pop"     "precip" 
##  [8] "rol"     "rq"      "temp"    "voice"  
## 
## $target
## [1] "con"
## 
## $name
## character(0)
## 
## $order
## character(0)
## 
## $stratum
## character(0)
## 
## $group
## character(0)
## 
## $weight
## character(0)

##Define the performance measure
##Regression Task
##additional measures can be found with msr()

measure = msr("regr.rmse")

#Define the learner
lrn_rf = lrn("regr.ranger",
             predict_type = "response",
             importance = "permutation")

## Define the resampling method
## 1st Run - Simple holdout 0.8
resamp_hout = rsmp("holdout",
                   ratio = 0.8)


## Instantiate the resampling method
resamp_hout$instantiate(task_prov)

## Run the resampler/model
##con = conflict

prov_rf = resample(task = task_prov,
                 learner = lrn_rf,
                 resampling = resamp_hout,
                 store_models = TRUE)

## INFO  [14:32:54.123] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)

## Check the performace measures
prov_rf$score(measure)

task	task_id	learner	learner_id	resampling	resampling_id	iteration	prediction	regr.rmse
<environment>	con	<environment>	regr.ranger	<environment>	holdout	1	<environment>	304

##Convert the RMSE to a percentage
rmse_prov = prov_rf$score(measure)

##Percentage Conversion
rmse_prov = (rmse_prov$regr.rmse / mean(prov.df$con)) * 100

##Show RMSE
print(rmse_prov)

## [1] 132.7068

##Visualize the model
vip(prov_rf$learners[[1]]$model)

##PDP plot function
## Define a helper function to plot


prov.pdp.plot = function(x){
  partial(prov_rf$learners[[1]]$model, 
        pred.var = x, prob = TRUE, 
        train = prov.df, plot = TRUE, which.class = 2)
}

## Define a loop to plot all of the variables
## pdp.plot is the helper function
## This plot the relative weights? in the SOM?

lapply(names(prov.df[,2:13]), prov.pdp.plot)

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Adm 1 Analysis using z-scores

##Zero out the zscore column
prov.df$zscore = NA

##Calculate Z scores
prov.df$zscore = scale(prov.df$con, center = TRUE, scale = TRUE)

## Check
head(prov.df)

country	year	pop	temp	precip	nlights	ge	cpt	rol	rq	polstab	voice	con	adm1	zscore
AFG	2.02e+03	1.03e+06	2.74	52	0.524	-1.44	-1.18	-1.66	-1.27	-2.55	-1.75	129	Badakhshan	-0.248349938946131
AFG	2.02e+03	8.89e+05	2.3	35	0.525	-1.63	-1.15	-1.88	-1.31	-2.52	-1.57	250	Badakhshan	0.0512548448532559
AFG	2.02e+03	7.66e+05	1.24	61.8	0.00162	-1.59	-1.49	-1.83	-1.39	-2.7	-1.08	250	Badakhshan	0.0512548448532559
AFG	2.02e+03	7.15e+05	1.73	61	0.00153	-1.5	-1.42	-1.74	-1.11	-2.65	-1.01	200	Badakhshan	-0.0725487848159122
AFG	2.02e+03	6.01e+05	2.25	44.4	0.0014	-1.48	-1.5	-1.69	-1.14	-2.75	-1.01	177	Badakhshan	-0.12949845446373
AFG	2.02e+03	1.19e+06	1.85	53.5	0.00167	-1.36	-1.53	-1.58	-1.37	-2.79	-0.99	159	Badakhshan	-0.17406776114463

tail(prov.df)

country	year	pop	temp	precip	nlights	ge	cpt	rol	rq	polstab	voice	con	adm1	zscore
UZB	2.02e+03	1.61e+06	15.2	11.1	0.147	-0.67	-1.29	-1.14	-1.69	-0.37	-1.96	16.8	Xorazm Region	-0.526211857670144
UZB	2.01e+03	1.59e+06	13.9	9.64	0.18	-0.62	-1.19	-1.13	-1.73	-0.27	-1.91	15.5	Xorazm Region	-0.529298989607109
UZB	2.01e+03	1.58e+06	15.5	10.8	0.132	-0.92	-1.27	-1.24	-1.6	-0.54	-1.97	23.3	Xorazm Region	-0.510106950935794
UZB	2.01e+03	1.52e+06	14.2	6.86	0.121	-0.91	-1.31	-1.3	-1.58	-0.52	-2.03	23.2	Xorazm Region	-0.510197465145041
UZB	2.01e+03	1.51e+06	14.1	8.39	6.65	-0.68	-1.39	-1.45	-1.56	-0.6	-2.12	31.4	Xorazm Region	-0.489951297521203
UZB	2.01e+03	1.49e+06	15.4	5.35	1.51	-0.72	-1.31	-1.42	-1.54	-0.72	-2.09	31.2	Xorazm Region	-0.490437845785803

#Define the task
task_prov2 = TaskRegr$new(id = "con",
                        backend = prov.df,
                        target = "zscore")

# Task details
task_prov2$col_roles

## $feature
##  [1] "adm1"    "con"     "country" "cpt"     "ge"      "nlights" "polstab"
##  [8] "pop"     "precip"  "rol"     "rq"      "temp"    "voice"   "year"   
## 
## $target
## [1] "zscore"
## 
## $name
## character(0)
## 
## $order
## character(0)
## 
## $stratum
## character(0)
## 
## $group
## character(0)
## 
## $weight
## character(0)

#if necessary exclude features here
## 
task_prov2$col_roles$feature = setdiff(task_prov2$col_roles$feature,
                                          c("country", "year", "con"))


## Check
task_prov2$col_roles

## $feature
##  [1] "adm1"    "cpt"     "ge"      "nlights" "polstab" "pop"     "precip" 
##  [8] "rol"     "rq"      "temp"    "voice"  
## 
## $target
## [1] "zscore"
## 
## $name
## character(0)
## 
## $order
## character(0)
## 
## $stratum
## character(0)
## 
## $group
## character(0)
## 
## $weight
## character(0)

##Define the performance measure
##Regression Task
##additional measures can be found with msr()

measure = msr("regr.rmse")

#Define the learner
lrn_rf = lrn("regr.ranger",
             predict_type = "response",
             importance = "permutation")

## Define the resampling method
## 1st Run - Simple holdout 0.8
resamp_hout = rsmp("holdout",
                   ratio = 0.8)


## Instantiate the resampling method
resamp_hout$instantiate(task_prov2)

## Run the resampler/model
##con = conflict

prov_rf2 = resample(task = task_prov2,
                 learner = lrn_rf,
                 resampling = resamp_hout,
                 store_models = TRUE)

## INFO  [14:33:11.232] [mlr3] Applying learner 'regr.ranger' on task 'con' (iter 1/1)

## Check the performace measures
prov_rf2$score(measure)

task	task_id	learner	learner_id	resampling	resampling_id	iteration	prediction	regr.rmse
<environment>	con	<environment>	regr.ranger	<environment>	holdout	1	<environment>	0.466

##Convert the RMSE to a percentage
## Compare it against the range of zscores as opposed to the mean zscore
rmse_prov2 = prov_rf2$score(measure)

##Percentage Conversion
rmse_prov2 = (rmse_prov2$regr.rmse / diff(range(prov.df$zscore))) * 100



##Show RMSE
print(rmse_prov2)

## [1] 3.385705

##Visualize the model
vip(prov_rf2$learners[[1]]$model)

##PDP plot function
## Define a helper function to plot


prov.pdp.plot2 = function(x){
  partial(prov_rf2$learners[[1]]$model, 
        pred.var = x, prob = TRUE, 
        train = prov.df, plot = TRUE, which.class = 2)
}

## Define a loop to plot all of the variables
## pdp.plot is the helper function
## This plot the relative weights? in the SOM?

lapply(names(prov.df[,2:13]), prov.pdp.plot2)

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