##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/library --timings HPiP_1.5.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2023-01-14 r83615)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
    gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
    GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
* running under: Ubuntu 22.04.1 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.5.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       39.834  0.912  40.748
corr_plot     37.970  0.459  38.432
FSmethod      37.751  0.581  38.332
pred_ensembel 18.026  0.304  15.995
getFASTA       0.848  0.004   8.634
enrichfindP    0.421  0.033  16.104
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
  ‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK
 NONE
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.17-bioc/R/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 109.789517 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.339109 
iter  10 value 88.331805
final  value 87.862820 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.964940 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.240999 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.742329 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.891803 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.829226 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.799285 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.125547 
iter  10 value 94.038442
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.140186 
final  value 94.038251 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.373988 
iter  10 value 91.250977
iter  20 value 89.606791
iter  30 value 89.600055
final  value 89.600000 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.540886 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.685983 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 123.013742 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.451338 
iter  10 value 93.618796
iter  20 value 91.644231
iter  30 value 91.317240
iter  40 value 91.313737
iter  50 value 91.309279
final  value 91.309261 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.593822 
iter  10 value 93.794766
iter  20 value 85.306561
iter  30 value 84.204774
iter  40 value 84.007250
iter  50 value 83.941001
final  value 83.940995 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.223411 
iter  10 value 94.059089
iter  20 value 94.056398
iter  30 value 92.240933
iter  40 value 91.820195
iter  50 value 86.123076
iter  60 value 84.989921
iter  70 value 83.673972
iter  80 value 83.323116
iter  90 value 83.229952
iter 100 value 82.996956
final  value 82.996956 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.359178 
iter  10 value 94.056980
iter  20 value 93.886545
iter  30 value 93.352917
iter  40 value 88.560878
iter  50 value 86.834107
iter  60 value 86.587961
iter  70 value 86.577683
final  value 86.577674 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.642079 
iter  10 value 94.029674
iter  20 value 93.000932
iter  30 value 91.431398
iter  40 value 91.344949
iter  50 value 85.801094
iter  60 value 84.934593
iter  70 value 84.818679
iter  80 value 84.720722
iter  90 value 83.493638
iter 100 value 82.671470
final  value 82.671470 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.666993 
iter  10 value 93.997132
iter  20 value 91.012671
iter  30 value 89.327321
iter  40 value 86.029509
iter  50 value 84.534226
iter  60 value 83.817643
final  value 83.800250 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.358758 
iter  10 value 94.003842
iter  20 value 91.176260
iter  30 value 87.779909
iter  40 value 84.568435
iter  50 value 82.914244
iter  60 value 82.274340
iter  70 value 81.939067
iter  80 value 81.718826
iter  90 value 81.577851
iter 100 value 81.503607
final  value 81.503607 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.046518 
iter  10 value 97.929802
iter  20 value 91.319367
iter  30 value 86.290148
iter  40 value 85.968289
iter  50 value 85.720547
iter  60 value 85.493584
iter  70 value 84.891633
iter  80 value 82.800102
iter  90 value 81.508801
iter 100 value 80.949605
final  value 80.949605 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.309089 
iter  10 value 91.680350
iter  20 value 86.259014
iter  30 value 85.776343
iter  40 value 83.471586
iter  50 value 82.367178
iter  60 value 82.068489
iter  70 value 81.874144
iter  80 value 81.744738
iter  90 value 81.719755
iter 100 value 81.590751
final  value 81.590751 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.766733 
iter  10 value 94.017769
iter  20 value 92.713266
iter  30 value 85.352117
iter  40 value 84.884048
iter  50 value 84.585915
iter  60 value 83.901358
iter  70 value 83.435244
iter  80 value 83.278436
iter  90 value 83.030221
iter 100 value 82.702541
final  value 82.702541 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.094006 
iter  10 value 94.069409
iter  20 value 86.088785
iter  30 value 85.020114
iter  40 value 84.086037
iter  50 value 82.194678
iter  60 value 81.825448
iter  70 value 81.384646
iter  80 value 81.265130
iter  90 value 81.193431
iter 100 value 81.105207
final  value 81.105207 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.960659 
iter  10 value 94.088279
iter  20 value 93.808710
iter  30 value 90.998767
iter  40 value 85.810421
iter  50 value 84.366128
iter  60 value 84.095767
iter  70 value 83.452159
iter  80 value 83.287202
iter  90 value 82.930369
iter 100 value 82.075558
final  value 82.075558 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.154629 
iter  10 value 93.880281
iter  20 value 87.883704
iter  30 value 85.332105
iter  40 value 83.549834
iter  50 value 83.068765
iter  60 value 82.874546
iter  70 value 82.532580
iter  80 value 82.265738
iter  90 value 81.908446
iter 100 value 81.769606
final  value 81.769606 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.995217 
iter  10 value 94.023555
iter  20 value 87.748192
iter  30 value 86.636795
iter  40 value 83.005603
iter  50 value 82.225475
iter  60 value 81.774823
iter  70 value 81.392180
iter  80 value 81.339696
iter  90 value 81.226475
iter 100 value 81.201966
final  value 81.201966 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.221497 
iter  10 value 93.955617
iter  20 value 89.316504
iter  30 value 87.590955
iter  40 value 86.119445
iter  50 value 83.973087
iter  60 value 83.601217
iter  70 value 83.386261
iter  80 value 83.219058
iter  90 value 83.128585
iter 100 value 82.746939
final  value 82.746939 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.602549 
iter  10 value 94.166311
iter  20 value 92.960530
iter  30 value 92.127885
iter  40 value 91.277265
iter  50 value 90.096840
iter  60 value 87.646624
iter  70 value 85.342982
iter  80 value 83.874640
iter  90 value 83.209869
iter 100 value 82.654212
final  value 82.654212 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.527169 
iter  10 value 94.054705
final  value 94.052931 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.877053 
final  value 94.054572 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.725059 
final  value 94.054164 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.205434 
final  value 94.054500 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.658430 
iter  10 value 91.945410
iter  20 value 91.927451
iter  30 value 91.927012
iter  40 value 88.568365
iter  50 value 88.557947
iter  60 value 88.556427
iter  70 value 88.395332
iter  80 value 88.394251
iter  90 value 88.383783
iter 100 value 87.617381
final  value 87.617381 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 120.773561 
iter  10 value 94.057762
iter  20 value 94.053147
iter  30 value 93.062120
iter  40 value 93.056967
final  value 93.056962 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.892151 
iter  10 value 94.042955
iter  20 value 93.434230
iter  30 value 87.413639
iter  40 value 85.909069
iter  50 value 85.906281
iter  60 value 85.905712
iter  70 value 85.759633
iter  80 value 82.357405
iter  90 value 82.056391
iter 100 value 81.932979
final  value 81.932979 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.665365 
iter  10 value 94.058002
iter  20 value 93.568754
iter  30 value 88.171978
iter  40 value 88.164947
final  value 88.164901 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.874839 
iter  10 value 92.447781
iter  20 value 91.787193
iter  30 value 91.629283
iter  40 value 91.628569
iter  50 value 91.627824
iter  60 value 87.273676
iter  70 value 85.541968
iter  80 value 85.536058
final  value 85.535956 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.160001 
iter  10 value 94.057606
iter  20 value 93.956408
iter  30 value 90.158621
iter  40 value 89.051179
iter  50 value 87.298496
iter  60 value 87.288661
iter  70 value 85.642030
iter  80 value 85.504982
iter  90 value 85.474091
iter 100 value 85.464843
final  value 85.464843 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.520258 
iter  10 value 94.061479
iter  20 value 94.050162
iter  30 value 94.046390
iter  40 value 92.470734
iter  50 value 85.427018
iter  60 value 85.424170
iter  70 value 85.422754
iter  80 value 84.655034
iter  90 value 84.080841
iter 100 value 83.480333
final  value 83.480333 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.683290 
iter  10 value 93.590836
iter  20 value 90.012722
iter  30 value 86.973025
iter  40 value 83.500551
iter  50 value 81.985793
iter  60 value 81.886747
iter  70 value 81.886383
final  value 81.885427 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.275516 
iter  10 value 94.061566
iter  20 value 93.925726
iter  30 value 91.441808
iter  40 value 86.011529
iter  50 value 85.358692
iter  60 value 85.351255
iter  70 value 85.347847
iter  80 value 85.334014
iter  90 value 82.522886
iter 100 value 81.847292
final  value 81.847292 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.708623 
iter  10 value 86.414618
iter  20 value 85.665091
iter  30 value 85.604283
iter  40 value 85.603071
iter  50 value 85.602253
iter  60 value 85.601315
iter  70 value 85.594748
iter  80 value 85.578065
iter  90 value 85.577850
iter 100 value 85.576400
final  value 85.576400 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.267880 
iter  10 value 93.999333
iter  20 value 93.992062
iter  30 value 93.413757
iter  40 value 91.083530
iter  50 value 91.013296
iter  60 value 90.574058
iter  70 value 90.390900
final  value 90.390654 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.804635 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.052878 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.250774 
iter  10 value 94.485090
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.969390 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.708279 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.726242 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.350178 
iter  10 value 94.354397
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.809853 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.218228 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.896775 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.962900 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.030547 
iter  10 value 94.488339
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 145.280759 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.668032 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.688241 
iter  10 value 86.991906
iter  20 value 81.177827
iter  30 value 80.226816
iter  40 value 80.001237
iter  50 value 79.664035
iter  60 value 79.297616
iter  70 value 79.275713
iter  80 value 79.270308
iter  90 value 79.269573
final  value 79.269532 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.161684 
iter  10 value 94.896006
iter  20 value 94.488414
iter  30 value 94.473692
iter  40 value 92.454871
iter  50 value 82.579604
iter  60 value 82.351776
iter  70 value 81.799440
iter  80 value 81.614824
iter  90 value 81.428418
iter 100 value 81.398982
final  value 81.398982 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.368084 
iter  10 value 93.756477
iter  20 value 86.170371
iter  30 value 84.857155
iter  40 value 82.344743
iter  50 value 80.712071
iter  60 value 80.391520
iter  70 value 79.986053
iter  80 value 79.812018
iter  90 value 79.719925
iter 100 value 79.687218
final  value 79.687218 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 110.468043 
iter  10 value 94.417568
iter  20 value 93.931277
iter  30 value 93.910016
iter  40 value 92.855917
iter  50 value 89.027625
iter  60 value 87.340033
iter  70 value 87.068886
iter  80 value 81.547366
iter  90 value 81.006360
iter 100 value 80.634456
final  value 80.634456 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.302515 
iter  10 value 94.448718
iter  20 value 87.591993
iter  30 value 83.184799
iter  40 value 82.392658
iter  50 value 81.634548
iter  60 value 81.584035
iter  70 value 81.470466
iter  80 value 81.408300
iter  90 value 81.399750
final  value 81.399530 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.292185 
iter  10 value 94.488493
iter  20 value 93.961043
iter  30 value 93.925819
iter  40 value 93.279931
iter  50 value 87.007467
iter  60 value 84.153107
iter  70 value 83.932829
iter  80 value 83.899830
iter  90 value 83.842028
iter 100 value 83.611831
final  value 83.611831 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.230884 
iter  10 value 94.335595
iter  20 value 88.587596
iter  30 value 86.193974
iter  40 value 85.620340
iter  50 value 82.084150
iter  60 value 81.138576
iter  70 value 80.689507
iter  80 value 80.067281
iter  90 value 78.371874
iter 100 value 78.248634
final  value 78.248634 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 131.284760 
iter  10 value 94.486936
iter  20 value 94.181117
iter  30 value 89.846741
iter  40 value 88.574699
iter  50 value 86.201647
iter  60 value 82.952134
iter  70 value 82.447912
iter  80 value 80.174285
iter  90 value 79.270733
iter 100 value 78.609546
final  value 78.609546 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.266952 
iter  10 value 94.994767
iter  20 value 87.327850
iter  30 value 84.188814
iter  40 value 83.908415
iter  50 value 83.133233
iter  60 value 81.002111
iter  70 value 79.935398
iter  80 value 79.621040
iter  90 value 79.494572
iter 100 value 79.115818
final  value 79.115818 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.243397 
iter  10 value 94.368179
iter  20 value 90.233120
iter  30 value 85.564903
iter  40 value 84.900847
iter  50 value 83.117635
iter  60 value 80.700119
iter  70 value 79.692655
iter  80 value 79.436273
iter  90 value 79.278539
iter 100 value 79.194793
final  value 79.194793 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.967913 
iter  10 value 94.497463
iter  20 value 93.023798
iter  30 value 87.784959
iter  40 value 84.965424
iter  50 value 81.865952
iter  60 value 81.040357
iter  70 value 80.688857
iter  80 value 80.350003
iter  90 value 79.935222
iter 100 value 79.299881
final  value 79.299881 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.770015 
iter  10 value 90.143459
iter  20 value 86.998346
iter  30 value 86.681893
iter  40 value 86.547398
iter  50 value 85.264871
iter  60 value 81.520457
iter  70 value 79.943564
iter  80 value 79.538175
iter  90 value 79.013568
iter 100 value 78.415399
final  value 78.415399 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.796596 
iter  10 value 94.502339
iter  20 value 92.277168
iter  30 value 82.071946
iter  40 value 81.658685
iter  50 value 81.228265
iter  60 value 80.060130
iter  70 value 79.392344
iter  80 value 79.139032
iter  90 value 78.752051
iter 100 value 78.117469
final  value 78.117469 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.691112 
iter  10 value 93.439662
iter  20 value 85.277292
iter  30 value 83.120523
iter  40 value 82.158807
iter  50 value 81.910720
iter  60 value 81.003390
iter  70 value 80.727983
iter  80 value 79.971301
iter  90 value 78.958133
iter 100 value 78.639430
final  value 78.639430 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.897224 
iter  10 value 83.821689
iter  20 value 79.818310
iter  30 value 78.818821
iter  40 value 78.229660
iter  50 value 77.981714
iter  60 value 77.914970
iter  70 value 77.694464
iter  80 value 77.522500
iter  90 value 77.443714
iter 100 value 77.427832
final  value 77.427832 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.713191 
iter  10 value 94.351969
iter  20 value 85.891668
iter  30 value 84.864320
iter  40 value 82.672199
iter  50 value 80.573457
iter  60 value 80.045728
iter  70 value 79.851751
iter  80 value 79.396043
iter  90 value 79.052799
iter 100 value 78.829477
final  value 78.829477 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.139742 
final  value 94.356166 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.783681 
iter  10 value 94.485748
iter  20 value 94.484225
iter  20 value 94.484224
iter  20 value 94.484224
final  value 94.484224 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.803533 
final  value 94.485967 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.241501 
final  value 94.485690 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.844345 
iter  10 value 94.485826
iter  20 value 94.298284
iter  30 value 89.284888
iter  40 value 88.288202
iter  50 value 86.589732
iter  60 value 82.227984
iter  70 value 81.965511
iter  80 value 81.958700
iter  90 value 81.851731
iter 100 value 81.807895
final  value 81.807895 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 95.821219 
iter  10 value 94.488630
iter  20 value 94.466263
iter  30 value 89.066698
iter  40 value 80.660548
iter  50 value 80.576704
iter  60 value 80.553954
iter  70 value 80.547475
iter  80 value 80.539992
iter  90 value 80.528656
iter 100 value 80.520814
final  value 80.520814 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.404992 
iter  10 value 94.489260
iter  20 value 94.469672
iter  30 value 88.230813
iter  40 value 82.168843
iter  50 value 81.057798
iter  60 value 81.052948
final  value 81.052499 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.757408 
iter  10 value 88.755673
iter  20 value 87.623490
iter  30 value 87.596816
iter  40 value 87.511724
iter  50 value 86.996696
iter  60 value 86.987812
final  value 86.987322 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.845498 
iter  10 value 94.489110
iter  20 value 94.475451
iter  30 value 84.116062
iter  40 value 82.512914
iter  50 value 82.086890
iter  60 value 81.990830
iter  70 value 81.987796
iter  80 value 81.987713
final  value 81.987165 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.543167 
iter  10 value 94.358871
iter  20 value 94.202036
iter  30 value 93.873166
iter  40 value 93.871657
iter  40 value 93.871656
iter  40 value 93.871656
final  value 93.871656 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.248154 
iter  10 value 94.321177
iter  20 value 94.316408
iter  30 value 94.308082
final  value 94.307592 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.953988 
iter  10 value 94.319807
iter  20 value 90.181180
iter  30 value 87.090098
iter  40 value 87.063057
iter  50 value 86.170888
final  value 86.018947 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.787563 
iter  10 value 94.492092
iter  20 value 94.431033
iter  30 value 93.865271
iter  40 value 93.839129
iter  50 value 93.838975
final  value 93.838960 
converged
Fitting Repeat 4 

# weights:  507
initial  value 149.123773 
iter  10 value 96.406168
iter  20 value 94.012531
iter  30 value 94.005346
iter  40 value 93.010498
iter  50 value 87.479516
iter  60 value 83.534902
iter  70 value 82.808288
iter  80 value 82.805080
final  value 82.805013 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.650866 
iter  10 value 94.155979
iter  20 value 92.227313
iter  30 value 92.205721
iter  40 value 92.005799
iter  50 value 91.978605
iter  60 value 91.972615
iter  60 value 91.972615
final  value 91.972612 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.781615 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.166606 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.023196 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.074782 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.422817 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.628102 
final  value 94.088889 
converged
Fitting Repeat 2 

# weights:  305
initial  value 122.838604 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.329776 
iter  10 value 86.990045
iter  20 value 85.600786
final  value 85.600081 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.166084 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.542245 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.858269 
iter  10 value 87.883525
iter  20 value 86.137182
iter  30 value 86.133349
final  value 86.133335 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.734915 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.544190 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.334169 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.070600 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.172434 
iter  10 value 94.288755
iter  20 value 91.240264
iter  30 value 84.230823
iter  40 value 81.561998
iter  50 value 80.955294
iter  60 value 80.320300
iter  70 value 79.978318
iter  80 value 79.972317
iter  90 value 79.927756
iter 100 value 79.897071
final  value 79.897071 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.689688 
iter  10 value 94.421163
iter  20 value 94.356649
iter  30 value 86.902226
iter  40 value 82.877730
iter  50 value 81.875854
iter  60 value 81.475960
iter  70 value 80.496176
iter  80 value 79.973963
final  value 79.973061 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.674891 
iter  10 value 94.486558
iter  20 value 94.213869
iter  30 value 94.078687
iter  40 value 92.550766
iter  50 value 83.910727
iter  60 value 82.715343
iter  70 value 81.614004
iter  80 value 81.292495
iter  90 value 81.265380
iter 100 value 80.382764
final  value 80.382764 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 110.961813 
iter  10 value 94.440632
iter  20 value 92.689302
iter  30 value 83.884640
iter  40 value 83.516053
iter  50 value 82.280755
iter  60 value 81.738535
iter  70 value 81.492682
iter  80 value 81.369956
iter  90 value 81.342230
iter 100 value 81.278130
final  value 81.278130 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 115.273301 
iter  10 value 94.429359
iter  20 value 93.049299
iter  30 value 91.537487
iter  40 value 85.630254
iter  50 value 84.188297
iter  60 value 81.953552
iter  70 value 80.808959
iter  80 value 80.774365
iter  90 value 80.764204
iter 100 value 80.049626
final  value 80.049626 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.845471 
iter  10 value 94.822860
iter  20 value 94.286102
iter  30 value 88.710383
iter  40 value 85.432836
iter  50 value 83.038736
iter  60 value 82.722054
iter  70 value 81.566324
iter  80 value 79.869802
iter  90 value 79.082945
iter 100 value 78.497669
final  value 78.497669 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.014702 
iter  10 value 94.746723
iter  20 value 83.416683
iter  30 value 81.102103
iter  40 value 80.820070
iter  50 value 80.776735
iter  60 value 80.730995
iter  70 value 80.252772
iter  80 value 80.010604
iter  90 value 79.316195
iter 100 value 78.717664
final  value 78.717664 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.219669 
iter  10 value 93.870025
iter  20 value 86.618206
iter  30 value 81.482082
iter  40 value 80.107658
iter  50 value 79.203088
iter  60 value 78.834169
iter  70 value 78.358516
iter  80 value 78.336954
iter  90 value 78.335661
final  value 78.335137 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.656617 
iter  10 value 94.563000
iter  20 value 94.257172
iter  30 value 83.286441
iter  40 value 82.029151
iter  50 value 81.252264
iter  60 value 80.483336
iter  70 value 80.041211
iter  80 value 78.995353
iter  90 value 78.281737
iter 100 value 78.190993
final  value 78.190993 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.322030 
iter  10 value 94.420234
iter  20 value 87.223467
iter  30 value 85.430947
iter  40 value 82.532812
iter  50 value 81.961929
iter  60 value 80.723320
iter  70 value 80.225155
iter  80 value 79.374561
iter  90 value 78.636662
iter 100 value 78.241737
final  value 78.241737 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.572899 
iter  10 value 94.835470
iter  20 value 92.599615
iter  30 value 87.433463
iter  40 value 83.285709
iter  50 value 81.999680
iter  60 value 80.944519
iter  70 value 80.165144
iter  80 value 79.514665
iter  90 value 78.923948
iter 100 value 78.530683
final  value 78.530683 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.627533 
iter  10 value 94.923941
iter  20 value 91.446058
iter  30 value 86.376481
iter  40 value 82.207171
iter  50 value 80.474635
iter  60 value 78.622867
iter  70 value 78.226560
iter  80 value 77.810384
iter  90 value 77.557504
iter 100 value 77.469012
final  value 77.469012 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 130.480687 
iter  10 value 97.060125
iter  20 value 91.977523
iter  30 value 90.942467
iter  40 value 84.777272
iter  50 value 84.101169
iter  60 value 79.297726
iter  70 value 78.093405
iter  80 value 77.811779
iter  90 value 77.686802
iter 100 value 77.593811
final  value 77.593811 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.252886 
iter  10 value 93.632753
iter  20 value 87.601752
iter  30 value 83.917828
iter  40 value 82.574163
iter  50 value 80.169198
iter  60 value 79.298242
iter  70 value 78.555714
iter  80 value 78.291499
iter  90 value 78.117793
iter 100 value 77.953564
final  value 77.953564 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.368723 
iter  10 value 94.066112
iter  20 value 84.290393
iter  30 value 83.098229
iter  40 value 82.687272
iter  50 value 81.396623
iter  60 value 81.090552
iter  70 value 80.984886
iter  80 value 80.644204
iter  90 value 79.903671
iter 100 value 79.628203
final  value 79.628203 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.382907 
final  value 94.485928 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.523006 
final  value 94.485916 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.741175 
final  value 94.485986 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.159246 
final  value 94.485875 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.573820 
iter  10 value 94.090703
iter  20 value 94.089246
iter  30 value 92.076385
iter  40 value 88.677973
iter  50 value 88.675416
iter  60 value 88.350397
iter  70 value 88.342324
iter  80 value 85.238117
iter  90 value 85.237681
iter 100 value 85.237323
final  value 85.237323 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.871790 
iter  10 value 94.280303
iter  20 value 94.275799
iter  30 value 82.865861
iter  40 value 81.904475
iter  50 value 81.653635
final  value 81.653603 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.353187 
iter  10 value 94.489236
iter  20 value 94.401485
final  value 94.112707 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.352840 
iter  10 value 94.487110
iter  20 value 94.426385
iter  30 value 94.053398
iter  40 value 93.666484
iter  50 value 81.913097
iter  60 value 81.657418
iter  70 value 81.653794
final  value 81.653620 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.899286 
iter  10 value 81.026347
iter  20 value 80.507872
iter  30 value 79.494412
iter  40 value 79.138211
iter  50 value 78.968176
iter  60 value 78.964745
iter  70 value 78.926998
iter  80 value 78.874310
iter  90 value 78.845113
iter 100 value 78.844489
final  value 78.844489 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.859617 
iter  10 value 94.489035
iter  20 value 94.479318
iter  30 value 84.926316
final  value 83.229986 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.213442 
iter  10 value 94.482314
iter  20 value 94.468781
iter  30 value 93.593633
iter  40 value 83.390170
iter  50 value 83.266955
iter  60 value 83.266267
final  value 83.266218 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.468749 
iter  10 value 94.492503
iter  20 value 94.470710
iter  30 value 93.125566
iter  40 value 85.330296
iter  50 value 83.248035
iter  60 value 83.247862
iter  70 value 81.882755
iter  80 value 81.634356
iter  90 value 81.633705
iter 100 value 81.633067
final  value 81.633067 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.934527 
iter  10 value 92.941943
iter  20 value 81.885702
iter  30 value 81.737576
iter  40 value 81.639034
iter  50 value 81.638687
iter  60 value 81.174648
iter  70 value 80.984423
iter  80 value 80.980846
iter  90 value 80.757906
final  value 80.673378 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.208668 
iter  10 value 94.314162
iter  20 value 93.879880
iter  30 value 84.094247
iter  40 value 82.848093
iter  50 value 80.961141
iter  60 value 80.726108
final  value 80.721740 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.580766 
iter  10 value 94.414050
iter  20 value 94.298820
iter  30 value 94.280616
iter  40 value 94.267127
iter  50 value 86.227930
iter  60 value 85.242928
iter  70 value 82.173434
iter  80 value 78.312915
iter  90 value 77.866323
iter 100 value 77.794276
final  value 77.794276 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.994333 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.760341 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.245118 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.113768 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.674846 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.273018 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.329382 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.204894 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.055629 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.724211 
iter  10 value 86.095510
iter  20 value 85.988325
final  value 85.988096 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.258384 
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  507
initial  value 126.706139 
final  value 94.400000 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.818276 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.136793 
iter  10 value 94.022728
iter  10 value 94.022727
iter  10 value 94.022727
final  value 94.022727 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.218862 
final  value 94.430233 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.436770 
iter  10 value 94.480123
iter  20 value 90.390015
iter  30 value 89.078612
iter  40 value 87.455972
iter  50 value 84.889153
iter  60 value 84.367160
iter  70 value 84.300746
final  value 84.300744 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.025302 
iter  10 value 91.824736
iter  20 value 86.392032
iter  30 value 85.970593
iter  40 value 85.818347
iter  50 value 84.505822
iter  60 value 83.957212
iter  70 value 83.783441
iter  80 value 83.383895
iter  90 value 83.230721
final  value 83.228844 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.804204 
iter  10 value 94.384081
iter  20 value 88.338945
iter  30 value 86.612869
iter  40 value 85.703813
iter  50 value 84.853667
iter  60 value 84.682738
final  value 84.677997 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.143075 
iter  10 value 94.489467
iter  20 value 93.642341
iter  30 value 87.115730
iter  40 value 84.699273
iter  50 value 83.631137
iter  60 value 83.521220
iter  70 value 83.435108
iter  80 value 83.305832
iter  90 value 83.228862
final  value 83.228844 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.582903 
iter  10 value 91.874894
iter  20 value 91.409952
iter  30 value 90.907885
iter  40 value 90.691137
final  value 90.689153 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.668937 
iter  10 value 94.160108
iter  20 value 89.530944
iter  30 value 85.564545
iter  40 value 84.611674
iter  50 value 83.664862
iter  60 value 82.378357
iter  70 value 81.278475
iter  80 value 80.934222
iter  90 value 80.415589
iter 100 value 80.143832
final  value 80.143832 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.739809 
iter  10 value 94.054341
iter  20 value 91.795486
iter  30 value 91.284502
iter  40 value 90.914236
iter  50 value 90.219405
iter  60 value 85.722713
iter  70 value 83.374237
iter  80 value 81.381389
iter  90 value 81.181780
iter 100 value 80.912965
final  value 80.912965 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.811013 
iter  10 value 94.508467
iter  20 value 94.494111
iter  30 value 92.946610
iter  40 value 89.166965
iter  50 value 87.825229
iter  60 value 87.075965
iter  70 value 85.284892
iter  80 value 84.808964
iter  90 value 82.784420
iter 100 value 82.180151
final  value 82.180151 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.437479 
iter  10 value 94.305065
iter  20 value 89.985563
iter  30 value 89.128088
iter  40 value 85.858005
iter  50 value 84.168152
iter  60 value 82.913205
iter  70 value 81.072399
iter  80 value 80.413392
iter  90 value 80.249136
iter 100 value 80.190487
final  value 80.190487 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 139.265653 
iter  10 value 94.734066
iter  20 value 92.749935
iter  30 value 88.812871
iter  40 value 87.982482
iter  50 value 85.527460
iter  60 value 84.811567
iter  70 value 84.556825
iter  80 value 84.421619
iter  90 value 83.182511
iter 100 value 81.661726
final  value 81.661726 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.530331 
iter  10 value 94.436221
iter  20 value 85.969000
iter  30 value 84.424096
iter  40 value 83.186438
iter  50 value 81.487099
iter  60 value 80.662938
iter  70 value 80.382926
iter  80 value 80.284733
iter  90 value 80.145252
iter 100 value 80.070768
final  value 80.070768 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.040745 
iter  10 value 93.742769
iter  20 value 92.035927
iter  30 value 87.170510
iter  40 value 84.525837
iter  50 value 82.695550
iter  60 value 81.819797
iter  70 value 81.090270
iter  80 value 80.866565
iter  90 value 80.664169
iter 100 value 80.613960
final  value 80.613960 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.446293 
iter  10 value 93.595550
iter  20 value 86.803714
iter  30 value 85.477122
iter  40 value 83.384252
iter  50 value 82.149435
iter  60 value 81.583185
iter  70 value 81.168819
iter  80 value 80.297440
iter  90 value 80.118038
iter 100 value 80.045198
final  value 80.045198 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 141.108606 
iter  10 value 96.156120
iter  20 value 93.581164
iter  30 value 86.708746
iter  40 value 83.559380
iter  50 value 83.259004
iter  60 value 82.477093
iter  70 value 82.464398
iter  80 value 82.087805
iter  90 value 81.280733
iter 100 value 80.825314
final  value 80.825314 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.846825 
iter  10 value 94.415169
iter  20 value 93.848843
iter  30 value 85.648503
iter  40 value 85.299087
iter  50 value 84.511338
iter  60 value 83.361235
iter  70 value 82.234003
iter  80 value 80.967501
iter  90 value 80.478900
iter 100 value 80.237792
final  value 80.237792 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.108487 
final  value 94.485747 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.908643 
iter  10 value 94.485764
iter  20 value 94.484177
iter  30 value 92.265561
iter  40 value 91.948011
iter  50 value 91.946074
iter  60 value 91.944520
iter  70 value 91.944152
iter  80 value 91.795145
iter  90 value 91.209943
iter 100 value 90.945517
final  value 90.945517 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.826808 
iter  10 value 94.486015
final  value 94.484367 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.189813 
iter  10 value 94.485602
iter  20 value 94.484245
iter  30 value 94.235375
iter  40 value 94.113841
final  value 94.113458 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.856701 
iter  10 value 94.486000
final  value 94.484339 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.946393 
iter  10 value 94.489220
iter  20 value 94.484683
iter  30 value 87.880946
iter  40 value 86.984385
iter  50 value 84.493956
iter  60 value 84.468806
iter  70 value 84.189795
iter  80 value 83.233683
iter  90 value 82.548950
iter 100 value 82.547702
final  value 82.547702 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.313413 
iter  10 value 94.434793
iter  20 value 94.406995
iter  30 value 93.713676
iter  40 value 87.957787
iter  50 value 84.107606
iter  60 value 84.056827
iter  70 value 83.208755
iter  80 value 83.157839
final  value 83.157401 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.810273 
iter  10 value 94.471973
iter  20 value 94.306954
iter  30 value 94.043526
iter  40 value 94.037941
iter  50 value 94.023403
final  value 94.023397 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.142633 
iter  10 value 94.454407
iter  20 value 94.449694
iter  30 value 94.108917
iter  40 value 86.137516
iter  50 value 86.111552
iter  60 value 86.111251
iter  70 value 84.639228
iter  80 value 84.622845
final  value 84.622822 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.312264 
iter  10 value 94.489180
iter  20 value 94.470293
iter  30 value 85.039192
final  value 84.884545 
converged
Fitting Repeat 1 

# weights:  507
initial  value 93.900599 
iter  10 value 93.255265
iter  20 value 93.254524
iter  30 value 93.226213
iter  40 value 93.178147
iter  50 value 93.177392
iter  60 value 93.175256
final  value 93.175084 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.543266 
iter  10 value 94.476410
iter  20 value 94.468870
final  value 94.467635 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.688207 
iter  10 value 91.429752
iter  20 value 91.156844
iter  30 value 91.145272
iter  40 value 91.144657
iter  50 value 90.852030
iter  60 value 84.277383
iter  70 value 83.504450
iter  80 value 83.503551
iter  90 value 82.907500
iter 100 value 82.248125
final  value 82.248125 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.397076 
iter  10 value 94.054648
iter  20 value 90.094828
iter  30 value 86.556841
iter  40 value 86.479271
iter  50 value 86.475886
iter  60 value 86.475405
iter  70 value 84.669378
iter  80 value 84.024846
iter  90 value 83.997023
iter 100 value 83.980001
final  value 83.980001 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.212568 
iter  10 value 94.067293
iter  20 value 94.052930
iter  30 value 94.051709
iter  40 value 86.715213
iter  50 value 86.703178
iter  60 value 86.693724
iter  70 value 84.624622
iter  80 value 83.940847
iter  90 value 83.774828
final  value 83.771526 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.594140 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.423722 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.651824 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.365821 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.446829 
final  value 93.912644 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.973568 
final  value 94.052908 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.150436 
iter  10 value 92.724020
final  value 92.696797 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.433494 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.313065 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.458331 
iter  10 value 93.226191
iter  10 value 93.226190
iter  10 value 93.226190
final  value 93.226190 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.783189 
iter  10 value 92.945415
final  value 92.945355 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.145649 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.924442 
iter  10 value 92.945501
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.631115 
final  value 92.945356 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.461049 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.922140 
iter  10 value 94.055311
iter  20 value 93.590101
iter  30 value 93.242049
iter  40 value 93.236073
iter  50 value 92.681814
iter  60 value 85.235786
iter  70 value 84.910411
iter  80 value 84.374783
iter  90 value 84.098018
iter 100 value 83.908019
final  value 83.908019 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.810435 
iter  10 value 93.985097
iter  20 value 93.237902
iter  30 value 93.231096
iter  40 value 92.856376
iter  50 value 90.653607
iter  60 value 89.320958
iter  70 value 89.209601
iter  80 value 87.459854
iter  90 value 86.304214
iter 100 value 84.500199
final  value 84.500199 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.034067 
iter  10 value 94.056735
iter  20 value 88.486472
iter  30 value 86.866371
iter  40 value 86.089564
iter  50 value 85.759139
iter  60 value 85.728721
iter  70 value 85.722588
iter  80 value 85.720188
iter  90 value 85.621363
final  value 85.619739 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.906849 
iter  10 value 87.517728
iter  20 value 86.020562
iter  30 value 85.832961
iter  40 value 85.797299
iter  50 value 85.629588
iter  60 value 85.619761
final  value 85.619742 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.223970 
iter  10 value 94.072499
iter  20 value 93.670269
iter  30 value 93.245552
iter  40 value 92.178192
iter  50 value 85.890340
iter  60 value 84.952650
iter  70 value 84.416780
iter  80 value 84.269654
iter  90 value 84.129987
iter 100 value 84.007624
final  value 84.007624 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.066108 
iter  10 value 93.076097
iter  20 value 89.017538
iter  30 value 86.530354
iter  40 value 85.674691
iter  50 value 85.006496
iter  60 value 84.954948
iter  70 value 84.905583
iter  80 value 84.466018
iter  90 value 83.530877
iter 100 value 82.584960
final  value 82.584960 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.449740 
iter  10 value 92.849131
iter  20 value 88.855225
iter  30 value 87.458583
iter  40 value 87.072923
iter  50 value 86.682631
iter  60 value 85.926273
iter  70 value 84.092782
iter  80 value 83.630342
iter  90 value 83.469657
iter 100 value 83.282548
final  value 83.282548 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.307706 
iter  10 value 94.023195
iter  20 value 86.582251
iter  30 value 84.900819
iter  40 value 84.410177
iter  50 value 84.055014
iter  60 value 83.433147
iter  70 value 83.074347
iter  80 value 82.971102
iter  90 value 82.609859
iter 100 value 82.305272
final  value 82.305272 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.624018 
iter  10 value 93.518715
iter  20 value 89.677224
iter  30 value 83.863509
iter  40 value 83.295250
iter  50 value 82.793890
iter  60 value 82.665675
iter  70 value 82.592496
iter  80 value 82.579745
iter  90 value 82.572568
iter 100 value 82.552148
final  value 82.552148 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.384233 
iter  10 value 94.068156
iter  20 value 88.851059
iter  30 value 86.316769
iter  40 value 85.756608
iter  50 value 85.318148
iter  60 value 85.105847
iter  70 value 84.844337
iter  80 value 84.768377
iter  90 value 84.766216
iter 100 value 84.764536
final  value 84.764536 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.539754 
iter  10 value 93.542772
iter  20 value 92.677785
iter  30 value 90.476765
iter  40 value 90.126283
iter  50 value 89.099598
iter  60 value 88.972790
iter  70 value 88.518493
iter  80 value 86.319617
iter  90 value 84.805242
iter 100 value 84.545405
final  value 84.545405 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.402545 
iter  10 value 96.020160
iter  20 value 91.807984
iter  30 value 89.979111
iter  40 value 85.333400
iter  50 value 84.677068
iter  60 value 84.329968
iter  70 value 84.202423
iter  80 value 83.789775
iter  90 value 83.068426
iter 100 value 82.615727
final  value 82.615727 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.160501 
iter  10 value 93.940901
iter  20 value 89.088261
iter  30 value 87.815627
iter  40 value 86.536777
iter  50 value 85.669700
iter  60 value 84.011820
iter  70 value 83.709969
iter  80 value 82.917777
iter  90 value 82.698560
iter 100 value 82.632465
final  value 82.632465 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.738857 
iter  10 value 93.657877
iter  20 value 92.386009
iter  30 value 87.751285
iter  40 value 86.054992
iter  50 value 85.395390
iter  60 value 84.649158
iter  70 value 83.387350
iter  80 value 82.755008
iter  90 value 82.435745
iter 100 value 82.284665
final  value 82.284665 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.227869 
iter  10 value 93.935947
iter  20 value 89.278491
iter  30 value 86.911262
iter  40 value 86.288134
iter  50 value 84.642012
iter  60 value 84.055534
iter  70 value 83.935070
iter  80 value 83.690584
iter  90 value 83.115439
iter 100 value 82.635693
final  value 82.635693 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.457346 
final  value 94.054551 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.135449 
iter  10 value 92.947465
iter  20 value 92.946435
final  value 92.945830 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.312733 
iter  10 value 92.925596
iter  20 value 92.761609
iter  30 value 92.760435
final  value 92.760033 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.752543 
final  value 94.054487 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.334134 
final  value 94.054700 
converged
Fitting Repeat 1 

# weights:  305
initial  value 128.303986 
iter  10 value 94.061708
iter  20 value 94.055566
iter  30 value 92.700708
iter  40 value 89.013639
iter  50 value 88.157000
iter  60 value 88.154339
iter  70 value 86.046331
iter  80 value 86.021846
iter  90 value 86.016187
iter 100 value 86.015274
final  value 86.015274 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.288419 
iter  10 value 94.058050
iter  20 value 94.052927
final  value 94.052924 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.746335 
iter  10 value 94.057877
iter  20 value 94.011329
iter  30 value 89.090420
iter  40 value 89.084328
iter  50 value 88.518839
iter  60 value 88.421647
iter  70 value 85.871963
iter  80 value 85.484864
iter  90 value 85.482849
final  value 85.481814 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.533944 
iter  10 value 92.950621
iter  20 value 92.947476
iter  30 value 92.760296
final  value 92.760132 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.098393 
iter  10 value 92.951654
iter  20 value 92.950721
iter  30 value 92.946388
iter  40 value 92.762589
final  value 92.760578 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.931311 
iter  10 value 92.968945
iter  20 value 92.963917
iter  30 value 92.679916
iter  40 value 90.998734
iter  50 value 86.538393
iter  60 value 86.497240
iter  70 value 86.492655
iter  80 value 86.489703
iter  90 value 86.488241
iter 100 value 86.485231
final  value 86.485231 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.553256 
iter  10 value 92.954570
iter  20 value 92.950275
iter  30 value 91.989750
iter  40 value 85.783655
iter  50 value 84.926916
iter  60 value 84.923999
iter  70 value 84.923043
iter  80 value 84.154534
iter  90 value 83.968694
iter 100 value 83.528301
final  value 83.528301 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.192225 
iter  10 value 94.061547
iter  20 value 94.035819
iter  30 value 93.502344
iter  40 value 89.902351
iter  50 value 89.836947
iter  60 value 89.833956
iter  70 value 89.831016
iter  80 value 89.821943
iter  90 value 89.821268
iter 100 value 89.690854
final  value 89.690854 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.098900 
iter  10 value 94.062405
iter  20 value 92.950032
iter  30 value 92.949310
iter  40 value 92.945843
iter  50 value 91.272037
iter  60 value 88.249152
iter  70 value 87.212916
iter  80 value 86.679129
iter  90 value 85.710961
iter 100 value 82.923815
final  value 82.923815 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.830148 
iter  10 value 93.099433
iter  20 value 92.953734
iter  30 value 92.938381
iter  40 value 92.246203
iter  50 value 90.222149
iter  60 value 90.192584
iter  70 value 90.192261
iter  80 value 88.690126
iter  90 value 88.504064
iter 100 value 88.470456
final  value 88.470456 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.685006 
iter  10 value 117.892282
iter  20 value 117.702004
iter  30 value 117.534237
iter  40 value 107.723857
iter  50 value 107.186241
iter  60 value 107.183718
final  value 107.183493 
converged
Fitting Repeat 2 

# weights:  507
initial  value 134.203461 
iter  10 value 117.767214
iter  20 value 117.745091
iter  30 value 107.443720
iter  40 value 106.806547
iter  50 value 106.794717
iter  60 value 106.764299
final  value 106.764215 
converged
Fitting Repeat 3 

# weights:  507
initial  value 150.578481 
iter  10 value 117.874219
iter  20 value 117.615569
iter  30 value 109.122525
iter  40 value 106.481194
iter  50 value 102.445448
iter  60 value 102.412027
iter  70 value 102.148967
iter  80 value 102.090807
iter  90 value 102.046774
iter 100 value 100.878130
final  value 100.878130 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 135.839554 
iter  10 value 117.551781
iter  20 value 117.507890
iter  30 value 117.501912
iter  40 value 116.489708
iter  50 value 106.492062
iter  60 value 103.047426
iter  70 value 102.986368
iter  80 value 102.982244
iter  90 value 102.981801
iter 100 value 102.981693
final  value 102.981693 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.608030 
iter  10 value 117.619267
iter  20 value 117.614482
iter  30 value 117.609540
iter  40 value 117.552836
final  value 117.551453 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Feb 28 05:56:02 2023 
*********************************************** 
Number of test functions: 8 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures
Number of test functions: 8 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: The `.data` argument of `add_column()` must have unique names as of tibble
3.0.0.
ℹ Use `.name_repair = "minimal"`.
ℹ The deprecated feature was likely used in the tibble package.
  Please report the issue at <https://github.com/tidyverse/tibble/issues>. 
2: `repeats` has no meaning for this resampling method. 
3: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 53.827   1.459  66.745