##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.5
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* 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 ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code 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 ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* 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       18.099  0.618  18.746
FSmethod      17.761  0.605  18.398
corr_plot     16.631  0.501  17.141
pred_ensembel  5.968  0.479   4.553
enrichfindP    0.170  0.027   8.034
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/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 version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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 95.637252 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.917917 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.939241 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.095149 
final  value 94.052914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.965627 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 128.598103 
iter  10 value 94.052912
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.249925 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.392127 
iter  10 value 87.370540
final  value 86.997168 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.009721 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.994754 
iter  10 value 93.950546
iter  20 value 93.915746
iter  20 value 93.915746
iter  20 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.108196 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.110101 
iter  10 value 92.036042
iter  20 value 90.924363
iter  30 value 88.014659
iter  40 value 87.295363
iter  50 value 87.294923
final  value 87.294832 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.452623 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.319918 
iter  10 value 93.691660
iter  20 value 93.604834
iter  30 value 92.181864
iter  40 value 90.553957
iter  50 value 89.673925
iter  60 value 89.672068
final  value 89.672009 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.477744 
iter  10 value 93.604492
final  value 93.486630 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.861882 
iter  10 value 94.055477
iter  20 value 91.175894
iter  30 value 87.648919
iter  40 value 85.344478
iter  50 value 85.203605
iter  60 value 84.165130
iter  70 value 83.759651
iter  80 value 83.222233
iter  90 value 82.828282
final  value 82.826681 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.376517 
iter  10 value 94.057175
iter  20 value 89.315827
iter  30 value 87.667565
iter  40 value 87.263333
iter  50 value 84.011024
iter  60 value 83.878949
iter  70 value 83.867270
final  value 83.866897 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.294247 
iter  10 value 94.055181
iter  20 value 93.995445
iter  30 value 93.899500
iter  40 value 91.099267
iter  50 value 86.652872
iter  60 value 86.250522
iter  70 value 84.553997
iter  80 value 83.490744
iter  90 value 82.827609
final  value 82.826681 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.097365 
iter  10 value 93.095493
iter  20 value 87.746568
iter  30 value 85.880960
iter  40 value 84.588557
iter  50 value 84.329302
iter  60 value 84.321927
final  value 84.313408 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.290016 
iter  10 value 93.357769
iter  20 value 87.934896
iter  30 value 84.211587
iter  40 value 83.781705
iter  50 value 83.073839
iter  60 value 82.813858
iter  70 value 82.717648
iter  80 value 82.649773
final  value 82.649771 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.178562 
iter  10 value 94.614462
iter  20 value 92.733455
iter  30 value 91.718545
iter  40 value 88.676980
iter  50 value 84.476072
iter  60 value 84.344807
iter  70 value 84.233334
iter  80 value 83.646662
iter  90 value 83.547347
iter 100 value 83.105961
final  value 83.105961 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.144751 
iter  10 value 94.089059
iter  20 value 93.917806
iter  30 value 93.283114
iter  40 value 85.750461
iter  50 value 85.248039
iter  60 value 84.498032
iter  70 value 84.187775
iter  80 value 84.040255
iter  90 value 83.653085
iter 100 value 82.750778
final  value 82.750778 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.851488 
iter  10 value 93.440851
iter  20 value 88.339763
iter  30 value 85.573421
iter  40 value 84.627004
iter  50 value 84.561267
iter  60 value 84.483748
iter  70 value 83.651962
iter  80 value 82.676032
iter  90 value 81.904672
iter 100 value 81.503614
final  value 81.503614 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.296865 
iter  10 value 94.012780
iter  20 value 90.929114
iter  30 value 87.277874
iter  40 value 86.120108
iter  50 value 85.458323
iter  60 value 85.335122
iter  70 value 83.678901
iter  80 value 82.280337
iter  90 value 81.806329
iter 100 value 81.306389
final  value 81.306389 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.056366 
iter  10 value 93.895899
iter  20 value 91.683880
iter  30 value 86.317311
iter  40 value 84.615912
iter  50 value 83.367685
iter  60 value 82.790445
iter  70 value 82.400113
iter  80 value 81.937360
iter  90 value 81.698915
iter 100 value 81.667887
final  value 81.667887 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.938809 
iter  10 value 94.428504
iter  20 value 88.572518
iter  30 value 87.526758
iter  40 value 86.372420
iter  50 value 85.095742
iter  60 value 84.714231
iter  70 value 84.473287
iter  80 value 83.659055
iter  90 value 82.858193
iter 100 value 81.546900
final  value 81.546900 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.554849 
iter  10 value 94.078095
iter  20 value 87.902949
iter  30 value 85.046187
iter  40 value 83.758092
iter  50 value 83.065225
iter  60 value 82.494058
iter  70 value 81.705528
iter  80 value 81.297353
iter  90 value 81.193139
iter 100 value 81.054528
final  value 81.054528 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.486506 
iter  10 value 94.086517
iter  20 value 93.686460
iter  30 value 87.268588
iter  40 value 86.578734
iter  50 value 84.832108
iter  60 value 84.010272
iter  70 value 83.978606
iter  80 value 83.861433
iter  90 value 83.647499
iter 100 value 82.921842
final  value 82.921842 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.826255 
iter  10 value 94.408596
iter  20 value 87.502127
iter  30 value 84.868547
iter  40 value 83.213088
iter  50 value 82.195117
iter  60 value 81.877422
iter  70 value 81.285477
iter  80 value 81.225522
iter  90 value 81.156166
iter 100 value 81.065056
final  value 81.065056 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.551902 
iter  10 value 94.171878
iter  20 value 93.539307
iter  30 value 92.205210
iter  40 value 85.376408
iter  50 value 84.998394
iter  60 value 84.362769
iter  70 value 82.941679
iter  80 value 82.099048
iter  90 value 81.704314
iter 100 value 81.681952
final  value 81.681952 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.504006 
final  value 94.054396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.722473 
final  value 94.054664 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.552286 
final  value 94.054499 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.561431 
iter  10 value 94.109956
iter  20 value 94.103585
iter  30 value 94.055358
final  value 94.052918 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.960159 
iter  10 value 94.054679
iter  20 value 94.038477
iter  30 value 84.802224
iter  40 value 84.792249
iter  50 value 84.784187
iter  60 value 84.776096
iter  70 value 84.772446
iter  80 value 84.766829
iter  90 value 84.766492
iter 100 value 84.574607
final  value 84.574607 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.229379 
iter  10 value 93.920881
iter  20 value 93.397243
iter  30 value 84.864520
iter  40 value 84.779163
iter  50 value 84.778458
iter  60 value 84.778204
iter  70 value 84.777145
iter  80 value 84.568821
iter  90 value 82.823833
iter 100 value 80.922928
final  value 80.922928 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.479415 
iter  10 value 94.057959
iter  20 value 94.052941
iter  30 value 93.577263
iter  40 value 90.267136
iter  50 value 89.923228
iter  60 value 85.057143
iter  70 value 84.163445
iter  80 value 83.477416
iter  90 value 82.548635
final  value 82.544501 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.305642 
iter  10 value 93.898853
iter  20 value 93.827058
iter  30 value 93.611598
final  value 93.605262 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.877074 
iter  10 value 94.057279
iter  20 value 93.964768
iter  30 value 93.122015
iter  40 value 92.502594
iter  50 value 84.412785
iter  60 value 83.802650
iter  70 value 83.787152
iter  80 value 83.112263
iter  90 value 82.730635
iter 100 value 82.699240
final  value 82.699240 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.835745 
iter  10 value 93.823774
iter  20 value 93.610002
iter  30 value 92.898058
iter  40 value 89.329783
iter  50 value 82.626429
iter  60 value 82.262671
iter  70 value 82.249654
iter  80 value 82.066321
iter  90 value 81.908309
iter 100 value 81.819800
final  value 81.819800 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.571445 
iter  10 value 84.944036
iter  20 value 84.263801
iter  30 value 84.196049
final  value 84.195369 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.664314 
iter  10 value 93.317462
iter  20 value 93.210506
iter  30 value 93.209294
iter  40 value 93.208314
iter  50 value 93.208011
iter  60 value 93.180569
iter  70 value 92.902295
iter  80 value 86.526922
iter  90 value 85.687708
iter 100 value 85.452145
final  value 85.452145 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.123676 
iter  10 value 93.564143
iter  20 value 92.617347
iter  30 value 92.484927
iter  40 value 92.480406
iter  50 value 85.492529
iter  60 value 84.308509
iter  70 value 84.200010
iter  80 value 83.894874
iter  90 value 83.847353
final  value 83.847243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.727910 
iter  10 value 93.970075
iter  20 value 93.719065
iter  30 value 93.421982
iter  40 value 93.321170
iter  50 value 93.083613
iter  60 value 93.082149
final  value 93.082144 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.584981 
iter  10 value 93.923529
iter  20 value 93.115057
iter  30 value 90.899561
iter  40 value 87.853359
iter  50 value 87.446177
iter  60 value 87.369002
iter  70 value 87.257612
iter  80 value 84.602859
iter  90 value 84.128233
iter 100 value 82.695214
final  value 82.695214 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.862321 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.616541 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.938938 
final  value 94.482478 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.673879 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.473959 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.420039 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.012507 
final  value 94.430233 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.539959 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.573247 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.397828 
iter  10 value 92.328376
iter  20 value 91.924906
iter  30 value 91.924400
final  value 91.924391 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.995716 
iter  10 value 94.463249
iter  20 value 94.463083
final  value 94.463077 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.926045 
iter  10 value 89.262767
iter  20 value 88.551049
iter  30 value 88.343984
iter  40 value 86.477636
iter  50 value 85.790261
iter  60 value 85.776478
iter  70 value 85.771479
iter  80 value 85.771429
iter  80 value 85.771429
iter  80 value 85.771429
final  value 85.771429 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.518045 
iter  10 value 86.239831
iter  20 value 84.848978
iter  30 value 84.844599
final  value 84.844595 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.768234 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.438805 
final  value 94.449438 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.448762 
iter  10 value 94.479920
iter  20 value 92.581806
iter  30 value 88.323854
iter  40 value 86.520235
iter  50 value 84.696621
iter  60 value 84.194625
iter  70 value 83.820335
iter  80 value 83.679977
iter  90 value 83.305385
iter 100 value 82.657282
final  value 82.657282 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.373707 
iter  10 value 94.484075
iter  20 value 94.292041
iter  30 value 93.520788
iter  40 value 92.506253
iter  50 value 89.806113
iter  60 value 86.945945
iter  70 value 85.854385
iter  80 value 85.235708
iter  90 value 84.471355
iter 100 value 84.231844
final  value 84.231844 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.451398 
iter  10 value 94.497001
iter  20 value 94.469761
iter  30 value 94.089391
iter  40 value 93.934862
iter  50 value 93.436709
iter  60 value 86.817288
iter  70 value 86.256111
iter  80 value 85.708108
iter  90 value 85.417534
iter 100 value 84.409564
final  value 84.409564 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.995413 
iter  10 value 94.503677
iter  20 value 94.221326
iter  30 value 86.555257
iter  40 value 85.121639
iter  50 value 83.486812
iter  60 value 82.665421
iter  70 value 82.520309
final  value 82.516502 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.549211 
iter  10 value 94.486833
iter  20 value 86.351593
iter  30 value 85.045992
iter  40 value 84.837351
iter  50 value 83.352733
iter  60 value 83.139183
iter  70 value 83.021261
iter  80 value 82.974749
iter  90 value 82.823336
final  value 82.822169 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.891892 
iter  10 value 94.516367
iter  20 value 92.783649
iter  30 value 91.674063
iter  40 value 87.089104
iter  50 value 84.587398
iter  60 value 84.179151
iter  70 value 83.778248
iter  80 value 83.378465
iter  90 value 83.257479
iter 100 value 83.253244
final  value 83.253244 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.392127 
iter  10 value 96.346768
iter  20 value 90.830981
iter  30 value 88.701518
iter  40 value 85.621758
iter  50 value 84.893432
iter  60 value 83.921984
iter  70 value 83.298999
iter  80 value 83.121726
iter  90 value 82.679662
iter 100 value 82.541983
final  value 82.541983 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 131.076963 
iter  10 value 94.086425
iter  20 value 92.825440
iter  30 value 91.508658
iter  40 value 85.444789
iter  50 value 84.007967
iter  60 value 83.193892
iter  70 value 82.113587
iter  80 value 82.047281
iter  90 value 81.834605
iter 100 value 81.489881
final  value 81.489881 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.833230 
iter  10 value 94.657722
iter  20 value 87.816099
iter  30 value 86.139655
iter  40 value 84.473854
iter  50 value 82.677820
iter  60 value 81.646742
iter  70 value 81.383748
iter  80 value 81.366120
iter  90 value 81.329409
iter 100 value 81.180415
final  value 81.180415 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.179646 
iter  10 value 94.708221
iter  20 value 92.902213
iter  30 value 87.954288
iter  40 value 86.257856
iter  50 value 85.813132
iter  60 value 85.495057
iter  70 value 84.508037
iter  80 value 83.685641
iter  90 value 82.575510
iter 100 value 82.081807
final  value 82.081807 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.423481 
iter  10 value 94.794733
iter  20 value 88.467581
iter  30 value 86.565506
iter  40 value 85.513780
iter  50 value 84.695803
iter  60 value 83.767396
iter  70 value 83.139009
iter  80 value 82.968647
iter  90 value 82.567548
iter 100 value 82.134791
final  value 82.134791 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.727785 
iter  10 value 94.608885
iter  20 value 94.076528
iter  30 value 90.462991
iter  40 value 86.880167
iter  50 value 85.665147
iter  60 value 84.173705
iter  70 value 82.445366
iter  80 value 81.666135
iter  90 value 81.425648
iter 100 value 81.151144
final  value 81.151144 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.707882 
iter  10 value 94.723680
iter  20 value 94.312458
iter  30 value 86.101841
iter  40 value 85.631076
iter  50 value 84.198417
iter  60 value 83.151778
iter  70 value 82.383253
iter  80 value 81.630701
iter  90 value 81.277953
iter 100 value 81.223109
final  value 81.223109 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.919512 
iter  10 value 94.382863
iter  20 value 89.909360
iter  30 value 88.471803
iter  40 value 87.081807
iter  50 value 85.471429
iter  60 value 83.238780
iter  70 value 82.939576
iter  80 value 82.827571
iter  90 value 82.428700
iter 100 value 81.777275
final  value 81.777275 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.771621 
iter  10 value 94.402328
iter  20 value 88.078715
iter  30 value 86.402246
iter  40 value 84.112189
iter  50 value 83.737342
iter  60 value 83.209643
iter  70 value 82.788301
iter  80 value 82.093231
iter  90 value 81.867777
iter 100 value 81.656562
final  value 81.656562 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.961855 
final  value 94.486033 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.635810 
iter  10 value 94.469109
iter  20 value 94.467516
iter  30 value 90.669063
final  value 90.654954 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.456950 
iter  10 value 94.486147
iter  20 value 94.483195
iter  30 value 92.726626
iter  40 value 91.615920
iter  50 value 86.290660
iter  60 value 85.723197
iter  70 value 85.542686
final  value 85.541678 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.724533 
final  value 94.485732 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.771981 
final  value 94.485932 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.697188 
iter  10 value 94.488952
iter  20 value 94.484289
iter  30 value 94.110663
iter  40 value 91.827241
iter  50 value 85.708551
iter  60 value 85.621997
iter  70 value 85.619612
iter  80 value 85.603994
iter  90 value 85.094654
iter 100 value 84.809680
final  value 84.809680 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.843956 
iter  10 value 94.489397
iter  20 value 94.483416
iter  30 value 91.885157
iter  40 value 91.791410
iter  50 value 91.557020
iter  60 value 91.079686
iter  70 value 91.063653
final  value 91.063633 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.762452 
iter  10 value 94.471992
iter  20 value 94.465099
iter  30 value 89.450327
iter  40 value 89.085754
iter  50 value 89.085481
final  value 89.085476 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.698634 
iter  10 value 94.472215
iter  20 value 94.467845
iter  30 value 92.595261
iter  40 value 92.404647
iter  50 value 92.404599
final  value 92.404598 
converged
Fitting Repeat 5 

# weights:  305
initial  value 128.831952 
iter  10 value 94.488444
iter  20 value 94.431990
iter  30 value 90.979917
iter  40 value 87.310729
iter  50 value 87.090462
iter  60 value 87.083962
iter  70 value 87.083562
iter  80 value 87.062750
iter  90 value 87.052584
final  value 87.052008 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.584242 
iter  10 value 94.475589
iter  20 value 92.980470
iter  30 value 92.170674
iter  40 value 92.017916
iter  50 value 91.953730
iter  60 value 91.892922
iter  70 value 91.891615
iter  80 value 91.318409
iter  90 value 90.542366
iter 100 value 90.541804
final  value 90.541804 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.666394 
iter  10 value 92.743093
iter  20 value 90.014341
iter  30 value 89.681490
iter  40 value 89.613663
iter  50 value 89.611595
iter  60 value 89.608502
iter  70 value 88.726641
final  value 88.556820 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.286349 
iter  10 value 94.491357
iter  20 value 94.450844
iter  30 value 87.186107
iter  40 value 85.708088
iter  50 value 85.692030
iter  60 value 85.455856
iter  70 value 85.411349
final  value 85.411097 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.618977 
iter  10 value 94.475936
iter  20 value 92.945776
iter  30 value 86.690283
iter  40 value 83.722635
iter  50 value 82.656350
iter  60 value 82.585568
iter  70 value 82.579341
iter  80 value 82.579114
iter  90 value 82.578430
iter 100 value 82.578265
final  value 82.578265 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.715326 
iter  10 value 88.808695
iter  20 value 88.479428
iter  30 value 88.473029
iter  40 value 87.402722
iter  50 value 84.374055
iter  60 value 83.178467
iter  70 value 83.163380
iter  80 value 83.162896
iter  90 value 83.162485
iter 100 value 82.964440
final  value 82.964440 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.718733 
iter  10 value 90.731642
iter  20 value 85.389388
iter  30 value 85.161180
iter  40 value 84.978008
iter  50 value 84.964342
final  value 84.964286 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.997981 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.257034 
iter  10 value 93.327590
iter  20 value 93.030295
iter  30 value 93.029479
final  value 93.029459 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.526600 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.669218 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.422325 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.825717 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.071484 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.313109 
iter  10 value 93.324759
final  value 93.324696 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.476015 
final  value 94.035088 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.842607 
iter  10 value 92.213305
iter  20 value 90.376675
iter  30 value 90.310256
iter  30 value 90.310256
iter  30 value 90.310256
final  value 90.310256 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.853500 
iter  10 value 93.328261
iter  10 value 93.328261
iter  10 value 93.328261
final  value 93.328261 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.640990 
iter  10 value 93.328259
iter  10 value 93.328259
iter  10 value 93.328259
final  value 93.328259 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.734241 
iter  10 value 93.328270
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.763063 
iter  10 value 93.328264
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.609402 
iter  10 value 93.640479
iter  20 value 89.206033
iter  30 value 82.640486
iter  40 value 81.123418
iter  50 value 80.805879
iter  60 value 80.679940
iter  70 value 80.270229
iter  80 value 79.849218
iter  90 value 79.335109
iter 100 value 79.296767
final  value 79.296767 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.249994 
iter  10 value 94.126087
iter  20 value 93.407347
iter  30 value 93.155296
iter  40 value 92.650299
iter  50 value 86.067938
iter  60 value 85.128546
iter  70 value 82.902228
iter  80 value 81.566574
iter  90 value 81.398278
iter 100 value 81.393253
final  value 81.393253 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.929794 
iter  10 value 93.967111
iter  20 value 91.067807
iter  30 value 89.359580
iter  40 value 88.809867
iter  50 value 88.793272
iter  60 value 88.784721
iter  70 value 88.713988
final  value 88.709186 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.840509 
iter  10 value 94.058197
iter  20 value 94.056675
iter  30 value 93.924262
iter  40 value 93.643176
iter  50 value 93.594519
iter  60 value 89.821807
iter  70 value 86.489820
iter  80 value 86.059209
iter  90 value 81.878477
iter 100 value 80.268569
final  value 80.268569 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.296520 
iter  10 value 93.986151
iter  20 value 84.919020
iter  30 value 83.109607
iter  40 value 82.091508
iter  50 value 81.692866
iter  60 value 81.449869
iter  70 value 81.394626
iter  80 value 81.392728
final  value 81.392624 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.299014 
iter  10 value 93.970985
iter  20 value 91.711898
iter  30 value 84.289076
iter  40 value 81.009801
iter  50 value 80.722051
iter  60 value 80.174867
iter  70 value 79.593685
iter  80 value 79.099385
iter  90 value 78.436892
iter 100 value 78.136389
final  value 78.136389 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.790278 
iter  10 value 94.052940
iter  20 value 93.687173
iter  30 value 86.919717
iter  40 value 84.275363
iter  50 value 83.126971
iter  60 value 81.542290
iter  70 value 79.581165
iter  80 value 78.802299
iter  90 value 78.319597
iter 100 value 78.215890
final  value 78.215890 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.871772 
iter  10 value 93.699787
iter  20 value 93.449755
iter  30 value 83.356289
iter  40 value 82.896402
iter  50 value 82.534241
iter  60 value 81.866200
iter  70 value 81.487693
iter  80 value 80.224274
iter  90 value 79.945451
iter 100 value 79.477688
final  value 79.477688 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.987662 
iter  10 value 93.956019
iter  20 value 89.671376
iter  30 value 88.427160
iter  40 value 83.246170
iter  50 value 82.772019
iter  60 value 81.674802
iter  70 value 81.034829
iter  80 value 80.266355
iter  90 value 79.920302
iter 100 value 79.719479
final  value 79.719479 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.461953 
iter  10 value 94.089221
iter  20 value 90.837501
iter  30 value 88.066564
iter  40 value 83.978642
iter  50 value 82.641094
iter  60 value 80.552438
iter  70 value 80.182603
iter  80 value 79.920147
iter  90 value 79.586723
iter 100 value 79.399350
final  value 79.399350 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 143.072046 
iter  10 value 94.106767
iter  20 value 87.233211
iter  30 value 83.588789
iter  40 value 81.586556
iter  50 value 80.150700
iter  60 value 79.097520
iter  70 value 78.363852
iter  80 value 78.248607
iter  90 value 78.207850
iter 100 value 78.172674
final  value 78.172674 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.523497 
iter  10 value 94.048903
iter  20 value 90.019999
iter  30 value 86.670956
iter  40 value 84.432059
iter  50 value 81.579860
iter  60 value 81.068036
iter  70 value 80.252275
iter  80 value 79.925177
iter  90 value 79.594929
iter 100 value 79.261244
final  value 79.261244 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.240193 
iter  10 value 93.616687
iter  20 value 91.372837
iter  30 value 82.148962
iter  40 value 80.515955
iter  50 value 78.306656
iter  60 value 77.854707
iter  70 value 77.749704
iter  80 value 77.609536
iter  90 value 77.595524
iter 100 value 77.563486
final  value 77.563486 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.751011 
iter  10 value 93.572397
iter  20 value 87.600911
iter  30 value 86.869537
iter  40 value 81.392521
iter  50 value 80.055798
iter  60 value 79.553280
iter  70 value 79.362653
iter  80 value 79.007589
iter  90 value 78.633796
iter 100 value 78.454445
final  value 78.454445 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.626855 
iter  10 value 94.236266
iter  20 value 84.837643
iter  30 value 83.013704
iter  40 value 79.279125
iter  50 value 78.534732
iter  60 value 78.368143
iter  70 value 78.206627
iter  80 value 78.035272
iter  90 value 77.761000
iter 100 value 77.701121
final  value 77.701121 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.752274 
iter  10 value 93.331446
iter  20 value 93.326514
iter  30 value 93.325082
iter  40 value 93.299338
iter  50 value 93.269146
final  value 93.269141 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.521553 
final  value 94.054570 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.360678 
final  value 94.054638 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.189856 
iter  10 value 83.854950
iter  20 value 82.780435
iter  30 value 82.774111
iter  40 value 82.770014
iter  50 value 82.733008
iter  60 value 82.717332
final  value 82.717255 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.555243 
final  value 94.054517 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.310601 
iter  10 value 94.059518
iter  20 value 93.827702
iter  30 value 91.541754
iter  40 value 90.027570
iter  50 value 82.541194
iter  60 value 82.412008
final  value 82.411820 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.281862 
iter  10 value 91.697121
iter  20 value 91.473425
iter  30 value 91.471243
final  value 91.471082 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.321242 
iter  10 value 94.057139
iter  20 value 93.329577
iter  30 value 93.269633
final  value 93.269345 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.877869 
iter  10 value 93.333382
iter  20 value 93.327415
iter  30 value 93.276877
iter  40 value 93.268993
iter  50 value 93.018849
iter  60 value 84.607341
iter  70 value 83.918875
iter  80 value 83.002688
iter  90 value 82.864953
iter 100 value 82.863880
final  value 82.863880 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.865289 
iter  10 value 94.057962
iter  20 value 94.052893
iter  30 value 93.329184
iter  30 value 93.329183
iter  30 value 93.329183
final  value 93.329183 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.670713 
iter  10 value 94.060492
iter  20 value 94.052937
iter  30 value 92.817358
iter  40 value 84.044256
iter  50 value 82.525363
iter  60 value 81.203261
iter  70 value 78.356789
iter  80 value 77.449123
iter  90 value 77.329284
iter 100 value 77.117019
final  value 77.117019 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.179503 
iter  10 value 93.337591
iter  20 value 93.333524
iter  30 value 91.904642
iter  40 value 91.815890
iter  50 value 91.775606
iter  60 value 91.773857
iter  70 value 91.772850
iter  80 value 89.388356
iter  90 value 88.885577
iter 100 value 87.615959
final  value 87.615959 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.947847 
iter  10 value 94.061462
iter  20 value 93.943672
iter  30 value 88.236032
iter  40 value 81.121771
iter  50 value 80.511218
iter  60 value 80.428131
final  value 80.427886 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.777350 
iter  10 value 93.974985
iter  20 value 93.337749
iter  30 value 93.336311
iter  40 value 93.334961
iter  50 value 93.030530
iter  60 value 82.624086
iter  70 value 79.728585
iter  80 value 77.556722
iter  90 value 77.236102
iter 100 value 77.054669
final  value 77.054669 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.651281 
iter  10 value 94.058624
iter  20 value 86.395279
iter  30 value 85.774306
iter  40 value 85.761722
iter  50 value 85.761110
final  value 85.760852 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.994161 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.596528 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.258770 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.575442 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.792673 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.567714 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.343237 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.044003 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.646522 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.442001 
iter  10 value 94.444296
iter  20 value 94.443245
final  value 94.443244 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.989947 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.097443 
iter  10 value 87.556885
iter  20 value 86.505112
iter  30 value 85.879323
iter  40 value 85.737570
iter  40 value 85.737570
iter  40 value 85.737570
final  value 85.737570 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.905068 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.791513 
iter  10 value 94.288300
iter  10 value 94.288300
iter  10 value 94.288300
final  value 94.288300 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.708567 
final  value 94.129871 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.726635 
iter  10 value 94.487629
iter  20 value 94.395037
iter  30 value 94.280179
iter  40 value 88.380275
iter  50 value 87.677840
iter  60 value 85.107135
iter  70 value 84.631494
iter  80 value 84.446639
iter  90 value 84.119239
iter 100 value 83.866719
final  value 83.866719 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.371177 
iter  10 value 94.492109
iter  20 value 94.427260
iter  30 value 87.240161
iter  40 value 84.432853
iter  50 value 84.133030
iter  60 value 83.885293
iter  70 value 83.851721
iter  80 value 83.827605
iter  90 value 83.757677
iter 100 value 83.748713
final  value 83.748713 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.990419 
iter  10 value 94.487950
iter  20 value 93.677390
iter  30 value 88.855256
iter  40 value 87.890619
iter  50 value 86.884991
iter  60 value 84.612869
iter  70 value 83.201459
iter  80 value 81.726136
iter  90 value 81.484029
iter 100 value 81.181310
final  value 81.181310 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.141926 
iter  10 value 94.127886
iter  20 value 87.508676
iter  30 value 87.053807
iter  40 value 84.338892
iter  50 value 81.791784
iter  60 value 81.683547
iter  70 value 81.336197
iter  80 value 81.179323
iter  90 value 80.782590
iter 100 value 80.735995
final  value 80.735995 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.781919 
iter  10 value 94.513126
iter  20 value 92.941802
iter  30 value 85.605017
iter  40 value 84.765160
iter  50 value 82.630826
iter  60 value 81.830508
iter  70 value 81.662249
iter  80 value 81.451238
iter  90 value 81.313363
iter 100 value 80.843184
final  value 80.843184 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 118.340327 
iter  10 value 94.740076
iter  20 value 94.429977
iter  30 value 92.722178
iter  40 value 84.580537
iter  50 value 82.975633
iter  60 value 82.540939
iter  70 value 81.254541
iter  80 value 80.144854
iter  90 value 79.914498
iter 100 value 79.908203
final  value 79.908203 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.372484 
iter  10 value 94.528123
iter  20 value 94.493260
iter  30 value 93.782507
iter  40 value 86.685284
iter  50 value 85.581914
iter  60 value 85.463753
iter  70 value 84.670613
iter  80 value 83.788654
iter  90 value 83.474575
iter 100 value 83.246853
final  value 83.246853 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.182753 
iter  10 value 93.867680
iter  20 value 90.480054
iter  30 value 85.844710
iter  40 value 84.650652
iter  50 value 83.525525
iter  60 value 83.383919
iter  70 value 83.355108
iter  80 value 83.088416
iter  90 value 82.381037
iter 100 value 81.942952
final  value 81.942952 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.988132 
iter  10 value 90.979738
iter  20 value 85.087974
iter  30 value 84.443248
iter  40 value 83.098834
iter  50 value 81.436692
iter  60 value 80.603892
iter  70 value 80.262155
iter  80 value 79.937846
iter  90 value 79.915894
iter 100 value 79.909595
final  value 79.909595 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.061864 
iter  10 value 94.228338
iter  20 value 85.768704
iter  30 value 82.620716
iter  40 value 82.486628
iter  50 value 81.418117
iter  60 value 80.985660
iter  70 value 79.818984
iter  80 value 78.829851
iter  90 value 78.695217
iter 100 value 78.634966
final  value 78.634966 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.963323 
iter  10 value 94.120924
iter  20 value 88.208641
iter  30 value 87.581224
iter  40 value 86.154164
iter  50 value 85.712313
iter  60 value 84.761400
iter  70 value 82.962400
iter  80 value 80.971569
iter  90 value 80.653740
iter 100 value 80.293234
final  value 80.293234 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 125.627637 
iter  10 value 95.151870
iter  20 value 87.788224
iter  30 value 86.386218
iter  40 value 86.101856
iter  50 value 85.788912
iter  60 value 83.911899
iter  70 value 82.198105
iter  80 value 80.654442
iter  90 value 79.723840
iter 100 value 79.622919
final  value 79.622919 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.875265 
iter  10 value 94.275832
iter  20 value 88.585290
iter  30 value 86.533525
iter  40 value 84.007381
iter  50 value 82.354888
iter  60 value 80.791323
iter  70 value 80.688344
iter  80 value 80.360576
iter  90 value 80.080602
iter 100 value 80.061314
final  value 80.061314 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.193336 
iter  10 value 94.549460
iter  20 value 86.388735
iter  30 value 84.619548
iter  40 value 84.314179
iter  50 value 83.973642
iter  60 value 83.685223
iter  70 value 83.630639
iter  80 value 83.584651
iter  90 value 83.501767
iter 100 value 83.434586
final  value 83.434586 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.504354 
iter  10 value 94.528475
iter  20 value 89.168804
iter  30 value 87.340248
iter  40 value 85.480177
iter  50 value 83.225906
iter  60 value 82.402966
iter  70 value 81.168431
iter  80 value 80.798239
iter  90 value 80.391173
iter 100 value 80.121248
final  value 80.121248 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.853838 
final  value 94.485812 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.740760 
iter  10 value 94.406473
iter  20 value 88.343126
iter  30 value 88.123846
iter  40 value 88.072927
iter  50 value 88.071744
iter  60 value 88.070815
iter  70 value 88.070682
iter  80 value 86.138830
iter  90 value 83.688899
iter 100 value 83.654051
final  value 83.654051 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.723324 
final  value 94.485703 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.380330 
iter  10 value 94.357611
iter  20 value 94.150143
iter  30 value 94.148686
iter  40 value 94.148313
iter  50 value 85.995663
iter  60 value 85.757093
iter  70 value 85.395710
iter  80 value 85.291331
iter  90 value 85.288521
iter 100 value 83.207569
final  value 83.207569 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.197533 
final  value 94.485993 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.285234 
iter  10 value 94.247579
iter  20 value 94.242051
iter  30 value 94.239325
iter  40 value 94.238423
iter  50 value 94.237683
iter  50 value 94.237683
iter  50 value 94.237683
final  value 94.237683 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.192512 
iter  10 value 93.572780
iter  20 value 93.569058
iter  30 value 93.568938
iter  40 value 91.186120
iter  50 value 91.175648
final  value 91.123226 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.118420 
iter  10 value 94.488821
iter  20 value 93.176219
iter  30 value 90.991759
iter  40 value 90.977140
iter  50 value 90.975911
final  value 90.975908 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.032061 
iter  10 value 94.486001
iter  20 value 94.462631
iter  30 value 84.002220
iter  40 value 83.118637
iter  50 value 83.115844
iter  60 value 83.115347
iter  70 value 83.114591
iter  80 value 81.883418
iter  90 value 81.723693
iter 100 value 81.723006
final  value 81.723006 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.940691 
iter  10 value 94.489741
iter  20 value 94.200577
iter  30 value 93.424072
iter  40 value 93.423534
final  value 93.423482 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.031906 
iter  10 value 94.474807
iter  20 value 94.468466
final  value 94.467400 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.974292 
iter  10 value 92.773449
iter  20 value 92.713606
iter  30 value 92.707856
iter  40 value 92.692627
iter  50 value 92.632442
iter  60 value 92.588991
iter  70 value 92.588394
iter  80 value 92.586923
iter  90 value 92.586407
iter 100 value 91.590379
final  value 91.590379 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.745382 
iter  10 value 94.492822
iter  20 value 94.476589
iter  30 value 91.418329
iter  40 value 82.396519
iter  50 value 81.562632
iter  60 value 81.412392
iter  70 value 81.412018
iter  80 value 80.834141
iter  90 value 80.667175
iter 100 value 80.662981
final  value 80.662981 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.203454 
iter  10 value 94.474923
iter  20 value 94.467481
final  value 94.467065 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.185452 
final  value 94.492226 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.420106 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.478979 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.205472 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.470441 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.157122 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.603534 
final  value 93.523810 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.486271 
iter  10 value 94.347316
iter  20 value 94.097559
iter  30 value 92.705175
iter  40 value 92.596994
iter  50 value 92.596215
final  value 92.596211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.063136 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.097856 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.600337 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.220857 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.305603 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.068461 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.129601 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.127952 
iter  10 value 94.244149
final  value 94.244048 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.376177 
iter  10 value 94.488646
iter  20 value 93.644801
iter  30 value 86.299335
iter  40 value 85.178039
iter  50 value 84.265566
iter  60 value 84.110221
iter  70 value 82.363434
iter  80 value 81.726733
iter  90 value 81.613052
iter 100 value 81.611925
final  value 81.611925 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 127.640818 
iter  10 value 94.486518
iter  20 value 93.965623
iter  30 value 93.594076
iter  40 value 86.362996
iter  50 value 86.040692
iter  60 value 85.462003
iter  70 value 84.217791
iter  80 value 81.804069
iter  90 value 81.613964
final  value 81.611616 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.897015 
iter  10 value 94.488083
iter  20 value 93.881205
iter  30 value 89.289469
iter  40 value 86.569229
iter  50 value 85.276352
iter  60 value 83.891105
iter  70 value 82.466641
iter  80 value 81.749996
iter  90 value 81.638071
iter 100 value 81.611638
final  value 81.611638 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.344919 
iter  10 value 94.486579
iter  20 value 94.067348
iter  30 value 93.978916
iter  40 value 86.750675
iter  50 value 86.338944
iter  60 value 84.386893
iter  70 value 83.995988
final  value 83.994992 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.029242 
iter  10 value 94.206500
iter  20 value 93.842308
iter  30 value 84.876936
iter  40 value 84.149861
iter  50 value 83.952845
iter  60 value 83.889112
iter  70 value 83.684860
iter  80 value 83.600177
iter  90 value 82.701162
iter 100 value 81.446826
final  value 81.446826 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.048664 
iter  10 value 94.425261
iter  20 value 94.073840
iter  30 value 86.892138
iter  40 value 85.401043
iter  50 value 83.360392
iter  60 value 82.292869
iter  70 value 81.291723
iter  80 value 80.735209
iter  90 value 80.377278
iter 100 value 80.343624
final  value 80.343624 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.876789 
iter  10 value 87.991854
iter  20 value 84.812825
iter  30 value 84.300286
iter  40 value 83.726161
iter  50 value 83.281383
iter  60 value 83.102685
iter  70 value 83.080448
iter  80 value 83.044068
iter  90 value 82.927135
iter 100 value 82.257299
final  value 82.257299 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.978816 
iter  10 value 94.492323
iter  20 value 93.746359
iter  30 value 86.653495
iter  40 value 85.263746
iter  50 value 82.171029
iter  60 value 81.435253
iter  70 value 81.298116
iter  80 value 81.003450
iter  90 value 80.906345
iter 100 value 80.562507
final  value 80.562507 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.970846 
iter  10 value 94.491128
iter  20 value 94.026091
iter  30 value 87.363390
iter  40 value 86.212474
iter  50 value 84.865437
iter  60 value 84.313334
iter  70 value 82.261113
iter  80 value 81.610114
iter  90 value 81.528611
iter 100 value 81.408419
final  value 81.408419 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.634522 
iter  10 value 94.662283
iter  20 value 90.096067
iter  30 value 88.327043
iter  40 value 88.196930
iter  50 value 84.557655
iter  60 value 81.498035
iter  70 value 80.608154
iter  80 value 80.499667
iter  90 value 80.229691
iter 100 value 79.896258
final  value 79.896258 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.566212 
iter  10 value 94.281026
iter  20 value 87.087456
iter  30 value 84.687085
iter  40 value 83.849949
iter  50 value 82.250562
iter  60 value 81.386262
iter  70 value 80.645640
iter  80 value 80.437090
iter  90 value 80.308519
iter 100 value 80.135422
final  value 80.135422 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.301677 
iter  10 value 94.439853
iter  20 value 93.562214
iter  30 value 88.014655
iter  40 value 85.853865
iter  50 value 84.657651
iter  60 value 83.128284
iter  70 value 81.885543
iter  80 value 80.680322
iter  90 value 80.379104
iter 100 value 79.965572
final  value 79.965572 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.179674 
iter  10 value 94.344850
iter  20 value 90.957422
iter  30 value 84.975636
iter  40 value 84.400230
iter  50 value 81.616745
iter  60 value 81.314405
iter  70 value 81.304785
iter  80 value 81.274904
iter  90 value 81.182349
iter 100 value 80.538108
final  value 80.538108 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.112213 
iter  10 value 94.322443
iter  20 value 87.127327
iter  30 value 83.612182
iter  40 value 81.868943
iter  50 value 81.136485
iter  60 value 80.863221
iter  70 value 80.489546
iter  80 value 80.380273
iter  90 value 80.284829
iter 100 value 80.228028
final  value 80.228028 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.919803 
iter  10 value 95.977320
iter  20 value 93.816368
iter  30 value 93.448628
iter  40 value 90.973649
iter  50 value 85.902757
iter  60 value 84.843799
iter  70 value 82.656490
iter  80 value 81.610601
iter  90 value 80.927497
iter 100 value 80.590751
final  value 80.590751 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.396022 
iter  10 value 94.486050
final  value 94.484409 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.756482 
final  value 94.485998 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.382883 
iter  10 value 94.106278
iter  20 value 93.775836
iter  30 value 93.774446
iter  40 value 92.245098
iter  50 value 84.062154
iter  60 value 82.988494
iter  70 value 82.940564
iter  80 value 82.855840
iter  90 value 82.798869
iter 100 value 82.677358
final  value 82.677358 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.417050 
final  value 94.485680 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.192505 
final  value 94.486090 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.436146 
iter  10 value 94.280414
iter  20 value 94.015847
iter  30 value 91.770935
iter  40 value 91.330522
iter  50 value 91.096449
iter  60 value 91.082574
final  value 91.082546 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.229650 
iter  10 value 92.689103
iter  20 value 91.907997
iter  30 value 91.904900
iter  40 value 91.779921
iter  50 value 91.671981
final  value 91.671221 
converged
Fitting Repeat 3 

# weights:  305
initial  value 139.323320 
iter  10 value 94.489362
iter  20 value 94.484235
final  value 94.484216 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.348321 
iter  10 value 94.484495
iter  20 value 86.199444
final  value 83.616918 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.800311 
iter  10 value 94.488067
iter  20 value 94.430934
iter  30 value 93.624966
iter  40 value 92.334395
iter  50 value 91.242145
iter  60 value 91.241066
iter  70 value 91.240691
iter  80 value 91.240473
final  value 91.240442 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.510919 
iter  10 value 94.283574
iter  20 value 94.109116
iter  30 value 86.273772
iter  40 value 85.758298
final  value 85.758191 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.100514 
iter  10 value 93.957679
iter  20 value 93.936653
iter  30 value 93.927122
iter  40 value 93.775330
iter  50 value 91.536074
iter  60 value 84.958850
iter  70 value 82.532679
iter  80 value 80.093939
iter  90 value 80.058444
iter 100 value 79.945859
final  value 79.945859 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.958110 
iter  10 value 93.802698
iter  20 value 93.362284
iter  30 value 92.852331
iter  40 value 92.844007
iter  50 value 92.842820
iter  60 value 92.841424
iter  70 value 91.606700
iter  80 value 84.679098
iter  90 value 80.941214
iter 100 value 79.715821
final  value 79.715821 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.066963 
iter  10 value 93.710126
iter  20 value 93.703196
iter  30 value 91.393469
iter  40 value 85.658584
iter  50 value 84.019897
iter  60 value 83.732309
iter  70 value 83.729555
iter  80 value 83.656142
iter  90 value 82.998337
iter 100 value 82.498263
final  value 82.498263 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.653011 
iter  10 value 94.492526
iter  20 value 94.330416
iter  30 value 93.595281
final  value 93.588944 
converged
Fitting Repeat 1 

# weights:  103
initial  value 121.366522 
iter  10 value 113.393055
iter  20 value 109.059248
iter  30 value 109.056491
iter  40 value 109.054920
iter  50 value 106.675049
iter  60 value 106.656421
final  value 106.656381 
converged
Fitting Repeat 2 

# weights:  103
initial  value 118.687599 
final  value 117.867603 
converged
Fitting Repeat 3 

# weights:  103
initial  value 121.499262 
final  value 117.891820 
converged
Fitting Repeat 4 

# weights:  103
initial  value 119.624327 
final  value 117.891976 
converged
Fitting Repeat 5 

# weights:  103
initial  value 123.389745 
final  value 117.892442 
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 -- Fri Jul 12 21:55:24 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 17.473   1.202  24.248