##############################################################################
##############################################################################
###
### 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       39.809  0.395  40.924
corr_plot     38.342  0.303  40.340
FSmethod      37.033  0.360  38.347
pred_ensembel 18.368  0.208  19.032
getFASTA       0.886  0.004   8.696
enrichfindP    0.427  0.016  15.100
* 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 100.640084 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.146552 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.917484 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.167333 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.444920 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.164832 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 123.391158 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.840247 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.756308 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.237742 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 128.046586 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.623983 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.744049 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.642888 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.047967 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.915608 
iter  10 value 94.490672
iter  20 value 94.436162
iter  30 value 91.872562
iter  40 value 89.257991
iter  50 value 86.843028
iter  60 value 84.974974
iter  70 value 84.766150
iter  80 value 84.659741
iter  90 value 84.276673
iter 100 value 83.913796
final  value 83.913796 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.144031 
iter  10 value 94.526318
iter  20 value 94.477104
iter  30 value 94.222327
iter  40 value 94.100642
iter  50 value 93.395491
iter  60 value 84.912166
iter  70 value 84.540592
iter  80 value 84.224074
iter  90 value 82.495046
iter 100 value 82.258900
final  value 82.258900 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.411982 
iter  10 value 96.347191
iter  20 value 94.488900
iter  30 value 94.414342
iter  40 value 91.416572
iter  50 value 86.885989
iter  60 value 84.130504
iter  70 value 82.587190
iter  80 value 82.353167
iter  90 value 81.922612
final  value 81.904357 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.763009 
iter  10 value 94.475621
iter  20 value 94.015252
iter  30 value 93.140405
iter  40 value 91.407811
iter  50 value 91.070613
iter  60 value 85.584994
iter  70 value 85.174079
iter  80 value 82.606715
iter  90 value 82.265977
iter 100 value 82.079931
final  value 82.079931 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.905256 
iter  10 value 94.374337
iter  20 value 91.018895
iter  30 value 83.122013
iter  40 value 82.732359
iter  50 value 82.254218
iter  60 value 81.908193
final  value 81.904357 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.528626 
iter  10 value 94.475386
iter  20 value 92.262535
iter  30 value 87.885706
iter  40 value 83.112907
iter  50 value 81.474399
iter  60 value 81.191406
iter  70 value 81.178125
iter  80 value 80.911721
iter  90 value 80.768941
iter 100 value 80.684356
final  value 80.684356 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.020902 
iter  10 value 94.518082
iter  20 value 91.576156
iter  30 value 84.155735
iter  40 value 82.081420
iter  50 value 81.953972
iter  60 value 81.930469
iter  70 value 81.825717
iter  80 value 81.669332
iter  90 value 81.565814
iter 100 value 80.865520
final  value 80.865520 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.937915 
iter  10 value 94.559781
iter  20 value 94.472359
iter  30 value 94.297215
iter  40 value 93.393653
iter  50 value 87.438054
iter  60 value 82.362817
iter  70 value 82.107259
iter  80 value 81.374291
iter  90 value 81.118630
iter 100 value 81.048093
final  value 81.048093 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.298992 
iter  10 value 94.672004
iter  20 value 91.647288
iter  30 value 88.753665
iter  40 value 85.303700
iter  50 value 83.995837
iter  60 value 83.013656
iter  70 value 82.581035
iter  80 value 82.261361
iter  90 value 82.097456
iter 100 value 81.991233
final  value 81.991233 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.491916 
iter  10 value 94.671462
iter  20 value 93.135937
iter  30 value 90.797773
iter  40 value 85.185572
iter  50 value 84.594549
iter  60 value 84.104296
iter  70 value 84.007501
iter  80 value 83.842732
iter  90 value 82.493241
iter 100 value 81.638511
final  value 81.638511 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.941446 
iter  10 value 94.556966
iter  20 value 92.928783
iter  30 value 87.364272
iter  40 value 84.680849
iter  50 value 83.859145
iter  60 value 83.118500
iter  70 value 82.626020
iter  80 value 82.497183
iter  90 value 82.299108
iter 100 value 81.764705
final  value 81.764705 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.709915 
iter  10 value 94.393429
iter  20 value 93.214723
iter  30 value 85.871044
iter  40 value 83.115075
iter  50 value 82.401337
iter  60 value 81.356600
iter  70 value 81.274022
iter  80 value 81.145392
iter  90 value 81.110913
iter 100 value 80.905651
final  value 80.905651 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.325081 
iter  10 value 94.254499
iter  20 value 85.083706
iter  30 value 84.596275
iter  40 value 83.873882
iter  50 value 81.944717
iter  60 value 81.664275
iter  70 value 81.031941
iter  80 value 80.632069
iter  90 value 80.364592
iter 100 value 80.242955
final  value 80.242955 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.701579 
iter  10 value 96.353665
iter  20 value 87.137130
iter  30 value 84.591653
iter  40 value 84.194205
iter  50 value 84.176876
iter  60 value 84.140899
iter  70 value 84.045360
iter  80 value 84.007717
iter  90 value 83.969764
iter 100 value 83.868679
final  value 83.868679 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 128.774934 
iter  10 value 94.726328
iter  20 value 94.052243
iter  30 value 86.893034
iter  40 value 85.598835
iter  50 value 84.245968
iter  60 value 81.984784
iter  70 value 80.710677
iter  80 value 80.547600
iter  90 value 79.871918
iter 100 value 79.763033
final  value 79.763033 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.915120 
final  value 94.485989 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.528989 
final  value 94.485725 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.512913 
final  value 94.486006 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.341765 
final  value 94.468257 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.113180 
iter  10 value 94.468605
iter  20 value 92.023168
final  value 87.334502 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.687563 
iter  10 value 94.489113
iter  20 value 94.484360
iter  30 value 89.271917
iter  40 value 82.904401
iter  50 value 81.862037
iter  60 value 81.679351
iter  70 value 81.668228
iter  80 value 81.668116
final  value 81.668096 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.764507 
iter  10 value 94.489300
iter  20 value 92.287714
iter  30 value 85.790013
iter  40 value 84.029341
iter  50 value 82.263172
iter  60 value 81.337653
iter  70 value 81.304205
iter  80 value 81.303300
iter  90 value 81.169008
iter 100 value 81.032758
final  value 81.032758 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.622207 
iter  10 value 94.446302
iter  20 value 94.442608
iter  30 value 88.510735
iter  40 value 85.313706
iter  50 value 85.313269
iter  60 value 85.312504
iter  70 value 84.693695
iter  80 value 83.461055
iter  90 value 81.858914
iter 100 value 79.283630
final  value 79.283630 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.755268 
iter  10 value 94.472103
iter  20 value 93.752918
iter  30 value 85.532221
iter  40 value 85.519900
iter  50 value 84.881557
iter  60 value 84.214248
iter  70 value 84.210476
iter  80 value 84.208894
iter  90 value 84.206964
final  value 84.206474 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.844894 
iter  10 value 94.425553
iter  20 value 94.304298
iter  30 value 94.212345
iter  40 value 92.744453
iter  50 value 91.080235
iter  60 value 90.659659
iter  70 value 90.657343
iter  80 value 89.939804
iter  80 value 89.939803
iter  80 value 89.939803
final  value 89.939803 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.003460 
iter  10 value 94.319849
iter  20 value 94.310589
iter  30 value 92.635060
iter  40 value 92.421799
iter  50 value 92.421760
final  value 92.421754 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.495666 
iter  10 value 93.438919
iter  20 value 93.433563
iter  30 value 93.425685
iter  40 value 93.087183
iter  50 value 90.905798
iter  60 value 85.619977
iter  70 value 84.330584
final  value 84.328004 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.587430 
iter  10 value 94.492488
iter  20 value 94.455565
iter  30 value 87.113632
iter  40 value 84.133396
iter  50 value 84.050186
final  value 84.049925 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.648467 
iter  10 value 94.474840
iter  20 value 94.318417
iter  30 value 93.426583
iter  40 value 93.423871
final  value 93.423845 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.764173 
iter  10 value 92.189380
iter  20 value 90.797342
iter  30 value 90.790083
iter  40 value 84.245106
iter  50 value 84.183041
iter  60 value 83.877987
iter  70 value 82.266922
iter  80 value 81.440694
iter  90 value 81.011018
iter 100 value 80.826494
final  value 80.826494 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.106648 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.565641 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.948769 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.333480 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.820642 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 92.812273 
iter  10 value 89.579997
final  value 89.579595 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.866612 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.184231 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.096940 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.166627 
iter  10 value 93.808227
iter  20 value 93.778232
final  value 93.778228 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.725342 
iter  10 value 86.297073
iter  20 value 85.837464
final  value 85.837406 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.284486 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.334034 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.185753 
iter  10 value 84.536920
iter  20 value 84.116833
iter  30 value 83.890407
iter  40 value 83.514423
iter  40 value 83.514423
final  value 83.514423 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.241637 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 112.475268 
iter  10 value 97.511738
iter  20 value 94.056775
iter  30 value 94.018784
iter  40 value 93.127233
iter  50 value 93.062809
iter  60 value 90.527731
iter  70 value 87.502705
iter  80 value 87.201244
iter  90 value 86.467351
iter 100 value 85.144678
final  value 85.144678 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.053408 
iter  10 value 93.985922
iter  20 value 85.827725
iter  30 value 84.423869
iter  40 value 84.402334
iter  50 value 84.306792
iter  60 value 84.191624
final  value 84.183500 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.482012 
iter  10 value 94.065597
iter  20 value 94.054358
iter  30 value 93.363295
iter  40 value 92.203587
iter  50 value 88.173827
iter  60 value 87.574599
iter  70 value 85.907867
iter  80 value 84.917086
iter  90 value 84.755265
iter 100 value 84.176099
final  value 84.176099 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 95.697214 
iter  10 value 94.063710
iter  20 value 94.000797
iter  30 value 93.298249
iter  40 value 93.192955
iter  50 value 92.298899
iter  60 value 85.988951
iter  70 value 84.739090
iter  80 value 83.764725
iter  90 value 83.372199
iter 100 value 82.947387
final  value 82.947387 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 110.638061 
iter  10 value 93.903389
iter  20 value 91.346537
iter  30 value 86.788847
iter  40 value 84.587166
iter  50 value 84.521845
iter  60 value 84.128688
iter  70 value 84.052344
iter  80 value 83.935258
iter  90 value 83.921228
iter  90 value 83.921228
iter  90 value 83.921228
final  value 83.921228 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.130600 
iter  10 value 93.848931
iter  20 value 89.953649
iter  30 value 86.034083
iter  40 value 83.997491
iter  50 value 83.481014
iter  60 value 83.089913
iter  70 value 82.980337
iter  80 value 82.841821
iter  90 value 82.536097
iter 100 value 82.183555
final  value 82.183555 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.495063 
iter  10 value 94.069207
iter  20 value 91.493250
iter  30 value 89.041355
iter  40 value 88.465360
iter  50 value 87.311547
iter  60 value 84.916133
iter  70 value 83.995782
iter  80 value 83.587048
iter  90 value 82.409291
iter 100 value 82.053943
final  value 82.053943 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.684236 
iter  10 value 90.993211
iter  20 value 88.609214
iter  30 value 84.836820
iter  40 value 84.416370
iter  50 value 83.192755
iter  60 value 82.449785
iter  70 value 82.309919
iter  80 value 82.254828
iter  90 value 82.208954
iter 100 value 82.201984
final  value 82.201984 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.835766 
iter  10 value 94.038019
iter  20 value 92.984839
iter  30 value 88.998799
iter  40 value 88.540246
iter  50 value 85.914964
iter  60 value 83.142799
iter  70 value 82.266685
iter  80 value 82.026826
iter  90 value 81.770424
iter 100 value 81.641724
final  value 81.641724 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.171854 
iter  10 value 94.064788
iter  20 value 93.547213
iter  30 value 92.704145
iter  40 value 89.724431
iter  50 value 86.820864
iter  60 value 85.826932
iter  70 value 85.317975
iter  80 value 84.046439
iter  90 value 83.663726
iter 100 value 82.546642
final  value 82.546642 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.033258 
iter  10 value 98.952158
iter  20 value 86.274135
iter  30 value 85.146753
iter  40 value 84.513501
iter  50 value 83.809137
iter  60 value 82.517155
iter  70 value 82.032232
iter  80 value 81.973026
iter  90 value 81.805338
iter 100 value 81.743594
final  value 81.743594 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.197756 
iter  10 value 94.200034
iter  20 value 93.271787
iter  30 value 89.058716
iter  40 value 87.915351
iter  50 value 85.772708
iter  60 value 84.634812
iter  70 value 83.559688
iter  80 value 82.671330
iter  90 value 82.195481
iter 100 value 81.814210
final  value 81.814210 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.720228 
iter  10 value 96.050526
iter  20 value 92.550934
iter  30 value 92.109334
iter  40 value 90.704770
iter  50 value 88.851974
iter  60 value 85.136498
iter  70 value 84.538779
iter  80 value 84.351593
iter  90 value 84.278659
iter 100 value 83.920401
final  value 83.920401 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.223223 
iter  10 value 94.504139
iter  20 value 93.799587
iter  30 value 88.350075
iter  40 value 87.026368
iter  50 value 84.482391
iter  60 value 84.133133
iter  70 value 83.894468
iter  80 value 83.120901
iter  90 value 82.617666
iter 100 value 82.256368
final  value 82.256368 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.375870 
iter  10 value 94.067498
iter  20 value 93.841563
iter  30 value 93.762589
iter  40 value 91.781826
iter  50 value 84.816495
iter  60 value 84.039274
iter  70 value 83.370784
iter  80 value 83.069471
iter  90 value 82.976724
iter 100 value 82.947351
final  value 82.947351 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.597403 
final  value 94.054581 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.567841 
final  value 94.054470 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.989799 
final  value 93.373652 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.914733 
iter  10 value 94.054794
iter  20 value 93.619902
iter  30 value 93.193065
final  value 93.192707 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.419994 
final  value 94.054518 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.084813 
iter  10 value 94.037735
iter  20 value 93.519600
iter  30 value 93.083394
iter  40 value 87.205293
iter  50 value 86.206352
iter  60 value 86.167166
iter  70 value 86.146796
iter  80 value 86.142753
iter  90 value 86.142658
iter 100 value 86.142548
final  value 86.142548 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 94.084977 
iter  10 value 94.056837
iter  20 value 93.764484
final  value 93.666805 
converged
Fitting Repeat 3 

# weights:  305
initial  value 128.220853 
iter  10 value 94.057589
iter  20 value 91.585825
iter  30 value 88.002692
iter  40 value 86.869644
iter  50 value 86.378742
iter  60 value 85.746436
iter  70 value 83.863159
iter  80 value 83.637744
iter  90 value 83.635451
iter 100 value 83.366718
final  value 83.366718 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.603403 
iter  10 value 94.057734
iter  20 value 94.030207
iter  30 value 93.192793
final  value 93.192705 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.462250 
iter  10 value 93.376693
iter  20 value 93.372257
iter  30 value 86.700105
final  value 85.978067 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.427878 
iter  10 value 94.042328
iter  20 value 93.978243
iter  30 value 93.379967
iter  40 value 91.690395
iter  50 value 85.180736
iter  60 value 83.928812
iter  70 value 83.922413
iter  80 value 83.829976
iter  90 value 83.007102
iter 100 value 82.912948
final  value 82.912948 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.967724 
iter  10 value 94.041895
iter  20 value 93.725678
iter  30 value 92.882334
iter  40 value 92.882080
final  value 92.881844 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.851562 
iter  10 value 94.061131
iter  20 value 93.368830
iter  30 value 93.040627
final  value 93.040405 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.464635 
iter  10 value 94.061444
iter  20 value 94.052531
iter  30 value 93.214832
iter  40 value 93.056950
iter  50 value 87.420438
iter  60 value 85.828445
iter  70 value 85.094659
iter  80 value 83.135442
iter  90 value 83.060806
iter 100 value 83.046122
final  value 83.046122 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.523023 
iter  10 value 93.729130
iter  20 value 93.381202
iter  30 value 87.993087
iter  40 value 86.644098
iter  50 value 86.642619
iter  60 value 86.297987
iter  70 value 86.103377
iter  80 value 86.102189
iter  90 value 86.101726
final  value 86.101272 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.169848 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.137868 
iter  10 value 93.394929
iter  10 value 93.394928
iter  10 value 93.394928
final  value 93.394928 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.257338 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.614192 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.616834 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.871668 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.414062 
iter  10 value 86.897811
final  value 86.053792 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.399077 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.580242 
iter  10 value 88.291155
iter  20 value 85.335863
iter  30 value 84.820533
iter  40 value 84.473767
iter  50 value 84.473719
final  value 84.473716 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.869921 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.887583 
iter  10 value 93.396347
iter  20 value 93.394942
final  value 93.394928 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.521198 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.099015 
final  value 94.114232 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.385126 
final  value 94.473118 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.060662 
iter  10 value 93.081436
final  value 93.081395 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.716944 
iter  10 value 94.488754
iter  20 value 92.491110
iter  30 value 91.863888
iter  40 value 89.524171
iter  50 value 86.240018
iter  60 value 85.264233
iter  70 value 84.256235
iter  80 value 83.274873
iter  90 value 82.788369
iter 100 value 82.065238
final  value 82.065238 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.818951 
iter  10 value 94.241336
iter  20 value 92.055622
iter  30 value 91.924721
iter  40 value 90.689563
iter  50 value 85.654551
iter  60 value 83.999898
iter  70 value 82.882196
iter  80 value 82.047797
iter  90 value 82.008159
final  value 82.008097 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.989487 
iter  10 value 94.416956
iter  20 value 88.014044
iter  30 value 87.841466
iter  40 value 87.628521
iter  50 value 87.237569
iter  60 value 87.135370
iter  70 value 85.307845
iter  80 value 83.253516
iter  90 value 82.429077
iter 100 value 81.416187
final  value 81.416187 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 107.483272 
iter  10 value 93.686929
iter  20 value 91.705477
iter  30 value 85.073489
iter  40 value 84.603532
iter  50 value 83.507561
iter  60 value 82.623672
iter  70 value 81.655313
final  value 81.652366 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.128610 
iter  10 value 93.528974
iter  20 value 86.990822
iter  30 value 86.140813
iter  40 value 85.417339
iter  50 value 85.028917
iter  60 value 83.920018
iter  70 value 83.280631
iter  80 value 83.243460
final  value 83.243444 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.563595 
iter  10 value 94.415963
iter  20 value 90.201186
iter  30 value 87.949496
iter  40 value 83.890725
iter  50 value 81.671677
iter  60 value 81.302810
iter  70 value 80.895245
iter  80 value 79.987164
iter  90 value 79.701435
iter 100 value 79.690059
final  value 79.690059 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.813308 
iter  10 value 94.392278
iter  20 value 85.865250
iter  30 value 84.905726
iter  40 value 84.209298
iter  50 value 83.781295
iter  60 value 83.198786
iter  70 value 80.423680
iter  80 value 79.853531
iter  90 value 79.635225
iter 100 value 79.608169
final  value 79.608169 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.613513 
iter  10 value 92.280839
iter  20 value 88.462168
iter  30 value 84.931632
iter  40 value 83.477136
iter  50 value 81.431794
iter  60 value 81.135847
iter  70 value 80.871884
iter  80 value 80.740675
iter  90 value 80.728746
iter 100 value 80.711952
final  value 80.711952 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.434351 
iter  10 value 94.237418
iter  20 value 93.286541
iter  30 value 87.754295
iter  40 value 85.444722
iter  50 value 82.666741
iter  60 value 81.105309
iter  70 value 80.410053
iter  80 value 80.270104
iter  90 value 79.906188
iter 100 value 79.780409
final  value 79.780409 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.000052 
iter  10 value 94.296108
iter  20 value 93.676024
iter  30 value 86.349264
iter  40 value 84.069360
iter  50 value 83.499359
iter  60 value 83.307800
iter  70 value 83.172801
iter  80 value 81.298781
iter  90 value 80.154181
iter 100 value 79.797767
final  value 79.797767 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 148.083642 
iter  10 value 96.778521
iter  20 value 88.351516
iter  30 value 86.568123
iter  40 value 84.055421
iter  50 value 83.649832
iter  60 value 83.456581
iter  70 value 83.379759
iter  80 value 83.154136
iter  90 value 82.308826
iter 100 value 82.162348
final  value 82.162348 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 132.015127 
iter  10 value 94.502528
iter  20 value 92.922002
iter  30 value 83.463723
iter  40 value 81.700555
iter  50 value 81.141933
iter  60 value 81.104212
iter  70 value 79.943257
iter  80 value 79.672112
iter  90 value 79.401801
iter 100 value 79.279861
final  value 79.279861 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.843630 
iter  10 value 92.119286
iter  20 value 88.577974
iter  30 value 86.052678
iter  40 value 84.999820
iter  50 value 84.624125
iter  60 value 84.126092
iter  70 value 83.324840
iter  80 value 82.914241
iter  90 value 82.872160
iter 100 value 82.526881
final  value 82.526881 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.004632 
iter  10 value 97.021370
iter  20 value 93.139767
iter  30 value 88.232867
iter  40 value 86.719503
iter  50 value 84.625623
iter  60 value 83.529944
iter  70 value 83.108277
iter  80 value 81.287530
iter  90 value 80.596094
iter 100 value 80.334687
final  value 80.334687 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.853423 
iter  10 value 94.092926
iter  20 value 89.989893
iter  30 value 85.298539
iter  40 value 82.907779
iter  50 value 82.048754
iter  60 value 81.357668
iter  70 value 80.725733
iter  80 value 79.877248
iter  90 value 79.610801
iter 100 value 79.520123
final  value 79.520123 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.080285 
iter  10 value 93.397670
iter  20 value 93.397138
iter  30 value 93.396394
final  value 93.395899 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.711918 
final  value 94.485856 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.749240 
final  value 94.485732 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.412659 
iter  10 value 94.486059
iter  20 value 94.484216
iter  20 value 94.484216
iter  20 value 94.484216
final  value 94.484216 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.534770 
iter  10 value 94.116020
iter  20 value 93.176863
iter  30 value 93.084286
iter  40 value 93.080991
final  value 93.080977 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.248817 
iter  10 value 94.350810
final  value 94.331057 
converged
Fitting Repeat 2 

# weights:  305
initial  value 122.854710 
iter  10 value 94.489304
iter  20 value 94.484499
iter  30 value 94.310890
iter  40 value 93.787749
iter  50 value 87.362327
iter  60 value 87.361056
iter  70 value 87.353210
iter  80 value 83.108940
iter  90 value 82.384747
iter 100 value 82.379643
final  value 82.379643 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.257046 
iter  10 value 94.151919
iter  20 value 89.681869
iter  30 value 84.453417
iter  40 value 84.016915
iter  50 value 83.934247
iter  60 value 83.933893
iter  70 value 83.844726
iter  80 value 83.781888
iter  90 value 83.282012
iter 100 value 82.616233
final  value 82.616233 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.458582 
iter  10 value 87.742468
iter  20 value 84.909943
iter  30 value 84.252740
iter  40 value 84.251909
iter  50 value 84.247928
iter  60 value 83.900804
iter  70 value 82.917791
iter  80 value 81.744741
iter  90 value 81.117219
iter 100 value 80.874084
final  value 80.874084 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.755764 
iter  10 value 94.488412
iter  20 value 94.466094
iter  30 value 93.395767
iter  30 value 93.395767
iter  30 value 93.395767
final  value 93.395767 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.863659 
iter  10 value 94.491810
iter  20 value 94.428874
iter  30 value 85.013227
iter  40 value 83.917462
iter  50 value 83.574694
iter  60 value 83.497210
iter  70 value 83.483655
iter  80 value 83.394161
iter  90 value 82.292194
iter 100 value 82.175106
final  value 82.175106 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.699563 
iter  10 value 94.481575
iter  20 value 87.643996
iter  30 value 86.731825
iter  40 value 86.730571
iter  50 value 86.215505
iter  60 value 84.252609
iter  70 value 83.613188
iter  80 value 83.543246
iter  90 value 83.533640
iter 100 value 83.532893
final  value 83.532893 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.367579 
iter  10 value 94.492560
iter  20 value 94.474230
iter  30 value 93.097470
iter  40 value 93.077823
iter  50 value 92.987679
iter  60 value 92.973596
final  value 92.973567 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.252764 
iter  10 value 94.492476
iter  20 value 91.422072
iter  30 value 88.722367
iter  40 value 88.220571
iter  50 value 87.318114
iter  60 value 87.309746
iter  70 value 87.309682
iter  80 value 87.309254
iter  90 value 85.298034
iter 100 value 85.029841
final  value 85.029841 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.740776 
iter  10 value 94.491502
iter  20 value 92.071421
iter  30 value 85.721966
iter  40 value 85.671418
iter  50 value 85.669534
iter  60 value 84.269862
iter  70 value 83.336324
iter  80 value 79.854010
iter  90 value 78.339960
iter 100 value 78.072614
final  value 78.072614 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.381919 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.778342 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.809795 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.026201 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.531343 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.036538 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.009296 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.092304 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.651044 
final  value 93.079545 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.532364 
iter  10 value 93.111074
final  value 93.109890 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.204007 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.989937 
iter  10 value 94.504537
final  value 94.455556 
converged
Fitting Repeat 3 

# weights:  507
initial  value 139.503387 
iter  10 value 94.585919
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.319964 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.487016 
iter  10 value 94.437038
final  value 94.436782 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.251395 
iter  10 value 94.556234
iter  20 value 94.477868
iter  30 value 94.476597
iter  40 value 94.048990
iter  50 value 87.505439
iter  60 value 82.763856
iter  70 value 81.978983
iter  80 value 81.543051
iter  90 value 81.322316
iter 100 value 81.256700
final  value 81.256700 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.780546 
iter  10 value 94.477630
iter  20 value 93.969980
iter  30 value 92.961340
iter  40 value 87.079180
iter  50 value 85.767971
iter  60 value 82.666847
iter  70 value 82.293666
iter  80 value 81.616233
iter  90 value 81.411526
final  value 81.410259 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.830887 
iter  10 value 94.248424
iter  20 value 86.915336
iter  30 value 85.096874
iter  40 value 83.733121
iter  50 value 81.976164
iter  60 value 81.428267
iter  70 value 81.410270
final  value 81.410259 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.225878 
iter  10 value 89.382771
iter  20 value 84.829620
iter  30 value 83.742134
iter  40 value 83.352186
iter  50 value 83.322070
iter  60 value 83.216211
iter  70 value 83.178212
final  value 83.178136 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.192549 
iter  10 value 94.488438
iter  20 value 94.437686
iter  30 value 86.900526
iter  40 value 86.356322
iter  50 value 86.200574
iter  60 value 86.071362
iter  70 value 86.062081
iter  80 value 84.977637
iter  90 value 83.958779
iter 100 value 83.851239
final  value 83.851239 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.276296 
iter  10 value 89.587403
iter  20 value 82.901215
iter  30 value 82.330492
iter  40 value 81.200650
iter  50 value 80.843951
iter  60 value 80.419118
iter  70 value 80.074523
iter  80 value 79.372904
iter  90 value 78.189416
iter 100 value 78.057028
final  value 78.057028 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.643409 
iter  10 value 95.103917
iter  20 value 94.477855
iter  30 value 86.371813
iter  40 value 86.199799
iter  50 value 86.064083
iter  60 value 81.762418
iter  70 value 81.049017
iter  80 value 79.594926
iter  90 value 78.883992
iter 100 value 78.700426
final  value 78.700426 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.765464 
iter  10 value 94.383730
iter  20 value 84.757487
iter  30 value 83.837386
iter  40 value 83.579043
iter  50 value 80.685856
iter  60 value 80.221928
iter  70 value 79.795769
iter  80 value 78.963388
iter  90 value 78.490224
iter 100 value 78.310787
final  value 78.310787 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.878713 
iter  10 value 94.444146
iter  20 value 87.318439
iter  30 value 84.933041
iter  40 value 84.061113
iter  50 value 83.521580
iter  60 value 82.225764
iter  70 value 79.079249
iter  80 value 78.810901
iter  90 value 78.454311
iter 100 value 78.346256
final  value 78.346256 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.265748 
iter  10 value 94.531953
iter  20 value 91.801986
iter  30 value 90.551744
iter  40 value 82.829816
iter  50 value 82.122877
iter  60 value 81.723742
iter  70 value 81.574012
iter  80 value 81.419160
iter  90 value 81.079826
iter 100 value 80.977809
final  value 80.977809 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.299973 
iter  10 value 94.720386
iter  20 value 93.653463
iter  30 value 87.328255
iter  40 value 86.410661
iter  50 value 85.755662
iter  60 value 81.711178
iter  70 value 79.840234
iter  80 value 79.324073
iter  90 value 78.633623
iter 100 value 78.184157
final  value 78.184157 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.781953 
iter  10 value 96.359723
iter  20 value 84.552083
iter  30 value 82.333385
iter  40 value 82.105176
iter  50 value 81.389542
iter  60 value 81.196451
iter  70 value 80.984823
iter  80 value 78.815433
iter  90 value 78.373405
iter 100 value 78.026094
final  value 78.026094 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.822758 
iter  10 value 95.238369
iter  20 value 92.852412
iter  30 value 91.134066
iter  40 value 91.061150
iter  50 value 88.802210
iter  60 value 81.458014
iter  70 value 81.067664
iter  80 value 80.851039
iter  90 value 80.547878
iter 100 value 79.619486
final  value 79.619486 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.368247 
iter  10 value 94.271720
iter  20 value 90.965192
iter  30 value 85.676594
iter  40 value 83.331964
iter  50 value 80.158170
iter  60 value 79.323723
iter  70 value 79.147080
iter  80 value 79.134023
iter  90 value 79.086690
iter 100 value 78.671369
final  value 78.671369 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.612388 
iter  10 value 94.978412
iter  20 value 93.257864
iter  30 value 84.703690
iter  40 value 83.409651
iter  50 value 80.965447
iter  60 value 80.079551
iter  70 value 79.346599
iter  80 value 79.142091
iter  90 value 78.677435
iter 100 value 78.580374
final  value 78.580374 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.022525 
final  value 94.485961 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.475951 
final  value 94.485937 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.304355 
final  value 94.485862 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.376570 
iter  10 value 94.486088
iter  20 value 94.383097
iter  30 value 86.962021
iter  40 value 86.955541
iter  50 value 86.955208
final  value 86.955058 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.084206 
final  value 94.485902 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.295025 
iter  10 value 94.489391
iter  20 value 94.484334
iter  30 value 89.187193
iter  40 value 83.324813
iter  50 value 82.359727
iter  60 value 82.029059
iter  70 value 82.027582
iter  80 value 82.011921
iter  90 value 81.819062
iter 100 value 81.610088
final  value 81.610088 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.873538 
iter  10 value 94.489144
iter  20 value 94.480782
iter  30 value 93.923578
iter  40 value 83.370926
iter  50 value 83.266005
final  value 83.257749 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.598877 
iter  10 value 94.472518
iter  20 value 94.467529
iter  30 value 90.231988
final  value 89.897817 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.124092 
iter  10 value 91.167230
iter  20 value 90.999891
iter  30 value 90.999122
iter  40 value 90.997354
final  value 90.996999 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.675437 
iter  10 value 91.044466
iter  20 value 91.033970
iter  30 value 91.032047
iter  40 value 91.029337
iter  50 value 91.028295
iter  60 value 90.840045
iter  70 value 89.450991
iter  80 value 89.438265
iter  90 value 89.437893
final  value 89.437794 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.017158 
iter  10 value 94.475709
iter  20 value 88.210303
iter  30 value 86.370173
final  value 86.370041 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.866367 
iter  10 value 94.492349
iter  20 value 94.406989
iter  30 value 84.263700
iter  40 value 83.849521
iter  50 value 83.583763
iter  60 value 80.399941
iter  70 value 80.138120
iter  80 value 80.096782
iter  90 value 79.934320
final  value 79.928334 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.482956 
iter  10 value 94.491350
iter  20 value 94.462087
iter  30 value 92.387091
iter  40 value 88.390371
iter  50 value 88.384877
iter  60 value 88.383990
iter  70 value 87.290396
iter  80 value 87.282928
iter  90 value 87.281335
iter 100 value 87.281017
final  value 87.281017 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.800779 
iter  10 value 94.492293
iter  20 value 94.439240
iter  30 value 87.542809
iter  40 value 87.406260
iter  50 value 85.963608
iter  60 value 85.963395
iter  70 value 85.043926
iter  80 value 83.187847
iter  90 value 82.367751
iter 100 value 81.979781
final  value 81.979781 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.149145 
iter  10 value 94.491860
iter  20 value 94.477106
iter  30 value 92.289706
iter  40 value 82.741106
iter  50 value 81.905335
iter  60 value 81.892088
iter  70 value 81.891741
iter  80 value 81.841292
iter  90 value 81.826866
final  value 81.826741 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.588521 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.552146 
final  value 93.356725 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.351779 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.829074 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.275190 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.445297 
iter  10 value 90.194469
iter  20 value 88.157418
iter  30 value 86.994684
iter  40 value 86.470727
iter  50 value 86.298122
final  value 86.297847 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.914928 
iter  10 value 93.086920
final  value 93.086891 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.753233 
iter  10 value 93.656850
iter  20 value 93.307911
iter  30 value 93.305807
iter  30 value 93.305806
iter  30 value 93.305806
final  value 93.305806 
converged
Fitting Repeat 4 

# weights:  305
initial  value 91.853000 
iter  10 value 84.159480
iter  20 value 84.157880
iter  20 value 84.157880
final  value 84.157880 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.272893 
iter  10 value 93.183870
final  value 93.183866 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.773042 
iter  10 value 93.525212
final  value 93.523811 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.943182 
iter  10 value 87.668057
iter  20 value 85.684112
final  value 85.651213 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.371122 
iter  10 value 93.173409
final  value 93.173405 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.625723 
final  value 93.551913 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.957623 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.027750 
iter  10 value 94.055382
iter  20 value 93.708572
iter  30 value 92.794637
iter  40 value 83.612738
iter  50 value 82.323598
iter  60 value 81.773552
iter  70 value 81.399254
iter  80 value 79.583914
iter  90 value 79.159418
iter 100 value 79.029549
final  value 79.029549 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 114.649193 
iter  10 value 94.055578
iter  20 value 93.985163
iter  30 value 93.889021
iter  40 value 92.893077
iter  50 value 92.823798
iter  60 value 92.804401
iter  70 value 91.227017
iter  80 value 82.261834
iter  90 value 80.391313
iter 100 value 80.105530
final  value 80.105530 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.017504 
iter  10 value 93.856014
iter  20 value 87.265369
iter  30 value 85.498462
iter  40 value 85.302114
iter  50 value 84.797788
iter  60 value 84.677418
iter  70 value 80.152144
iter  80 value 79.732327
iter  90 value 79.287411
iter 100 value 78.948052
final  value 78.948052 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.328455 
iter  10 value 94.421743
iter  20 value 92.196412
iter  30 value 86.357497
iter  40 value 84.848585
iter  50 value 83.541443
iter  60 value 83.299274
iter  70 value 82.979594
iter  80 value 80.387328
iter  90 value 80.180109
iter 100 value 79.299084
final  value 79.299084 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.466159 
iter  10 value 94.139113
iter  20 value 94.055616
iter  30 value 92.925211
iter  40 value 92.811354
iter  50 value 88.533611
iter  60 value 83.516560
iter  70 value 83.273102
iter  80 value 82.809128
iter  90 value 79.580704
iter 100 value 78.977286
final  value 78.977286 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.959045 
iter  10 value 94.140490
iter  20 value 92.849646
iter  30 value 92.743444
iter  40 value 92.318801
iter  50 value 84.579354
iter  60 value 83.150942
iter  70 value 82.810520
iter  80 value 82.104498
iter  90 value 81.810015
iter 100 value 81.684231
final  value 81.684231 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.005693 
iter  10 value 93.035509
iter  20 value 92.666738
iter  30 value 89.709649
iter  40 value 86.574349
iter  50 value 84.116079
iter  60 value 83.533231
iter  70 value 83.122580
iter  80 value 82.475899
iter  90 value 80.208498
iter 100 value 79.011434
final  value 79.011434 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.773891 
iter  10 value 93.917420
iter  20 value 84.664225
iter  30 value 83.932663
iter  40 value 82.649046
iter  50 value 81.759098
iter  60 value 80.240102
iter  70 value 79.408872
iter  80 value 79.303448
iter  90 value 79.201837
iter 100 value 78.970265
final  value 78.970265 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.384159 
iter  10 value 93.720693
iter  20 value 91.355151
iter  30 value 83.068691
iter  40 value 82.035981
iter  50 value 80.524623
iter  60 value 80.379267
iter  70 value 78.874642
iter  80 value 78.031028
iter  90 value 77.869516
iter 100 value 77.849980
final  value 77.849980 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.325092 
iter  10 value 94.065474
iter  20 value 93.234966
iter  30 value 92.845353
iter  40 value 90.349893
iter  50 value 83.620226
iter  60 value 82.099922
iter  70 value 79.680920
iter  80 value 79.095615
iter  90 value 78.713790
iter 100 value 78.487161
final  value 78.487161 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.799840 
iter  10 value 94.903277
iter  20 value 93.477577
iter  30 value 92.103376
iter  40 value 86.623563
iter  50 value 84.917034
iter  60 value 82.924763
iter  70 value 82.290706
iter  80 value 81.526839
iter  90 value 81.316503
iter 100 value 80.601474
final  value 80.601474 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.637257 
iter  10 value 95.460497
iter  20 value 93.832542
iter  30 value 87.910418
iter  40 value 86.303041
iter  50 value 82.359986
iter  60 value 80.865492
iter  70 value 79.762969
iter  80 value 78.503977
iter  90 value 77.744276
iter 100 value 77.219151
final  value 77.219151 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.349019 
iter  10 value 92.292562
iter  20 value 85.506360
iter  30 value 85.289359
iter  40 value 83.086606
iter  50 value 82.361892
iter  60 value 81.608051
iter  70 value 81.209885
iter  80 value 79.096369
iter  90 value 78.437325
iter 100 value 78.202899
final  value 78.202899 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.490614 
iter  10 value 96.318779
iter  20 value 90.563378
iter  30 value 86.620459
iter  40 value 86.394850
iter  50 value 85.305975
iter  60 value 80.133328
iter  70 value 79.434514
iter  80 value 78.094692
iter  90 value 77.642229
iter 100 value 77.430274
final  value 77.430274 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.925057 
iter  10 value 97.134112
iter  20 value 83.065012
iter  30 value 82.167494
iter  40 value 79.928888
iter  50 value 79.303176
iter  60 value 78.084357
iter  70 value 77.424816
iter  80 value 77.248418
iter  90 value 77.165468
iter 100 value 77.070032
final  value 77.070032 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.391020 
final  value 94.054349 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.831853 
final  value 94.054497 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.217804 
final  value 94.054478 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.784390 
iter  10 value 93.837798
iter  20 value 93.836438
iter  30 value 92.691463
iter  40 value 92.691325
final  value 92.691318 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.167207 
final  value 94.054559 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.673920 
iter  10 value 94.057292
iter  20 value 93.280781
iter  30 value 83.974165
iter  40 value 83.516558
iter  50 value 82.516988
iter  60 value 82.045417
final  value 82.045407 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.613356 
iter  10 value 94.057563
iter  20 value 94.051909
iter  30 value 93.357180
final  value 93.357178 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.774114 
iter  10 value 93.879129
iter  20 value 93.841343
iter  30 value 93.836426
final  value 93.836375 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.519917 
iter  10 value 94.056766
iter  20 value 94.049020
iter  30 value 87.851547
iter  40 value 87.188518
iter  50 value 86.780192
iter  60 value 85.012995
iter  70 value 82.495938
iter  80 value 82.446066
iter  90 value 82.443646
final  value 82.442996 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.877531 
iter  10 value 93.840347
iter  20 value 92.832217
iter  30 value 92.691199
iter  40 value 92.567767
iter  50 value 88.923583
iter  60 value 88.914761
iter  70 value 88.712208
iter  80 value 87.462541
iter  90 value 78.451737
iter 100 value 76.626194
final  value 76.626194 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.240750 
iter  10 value 93.844728
iter  20 value 93.838375
final  value 93.837849 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.262005 
iter  10 value 94.030976
iter  20 value 93.273732
iter  30 value 82.053101
iter  40 value 78.695136
iter  50 value 78.096664
iter  60 value 78.039567
iter  70 value 77.962917
iter  80 value 77.961971
iter  90 value 77.960703
iter 100 value 77.960561
final  value 77.960561 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.785552 
iter  10 value 94.060806
iter  20 value 94.052628
iter  30 value 92.954011
iter  40 value 87.288766
iter  50 value 86.045997
iter  60 value 85.752909
iter  70 value 83.975135
iter  80 value 81.186183
iter  90 value 80.650784
iter 100 value 80.222994
final  value 80.222994 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.471729 
iter  10 value 94.060489
iter  20 value 94.052934
iter  30 value 93.877744
iter  40 value 93.357655
iter  50 value 93.269915
iter  60 value 92.282347
iter  70 value 92.281614
iter  80 value 92.281099
iter  90 value 92.281055
iter 100 value 83.723381
final  value 83.723381 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.612832 
iter  10 value 92.698641
iter  20 value 92.684864
iter  30 value 92.679486
iter  40 value 92.577810
iter  50 value 92.556466
iter  60 value 92.556357
iter  70 value 92.547927
iter  80 value 87.344200
iter  90 value 84.482712
iter 100 value 82.611061
final  value 82.611061 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 125.436861 
final  value 117.890295 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.452681 
iter  10 value 112.019169
iter  20 value 111.641459
final  value 111.641314 
converged
Fitting Repeat 3 

# weights:  305
initial  value 122.554990 
final  value 117.890295 
converged
Fitting Repeat 4 

# weights:  305
initial  value 131.921100 
final  value 117.890295 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.495730 
final  value 117.890295 
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 -- Thu Feb  2 10:05:33 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 
 53.688   0.749  78.066