##############################################################################
##############################################################################
###
### 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_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.2 (2024-10-31)
* 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 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* 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       54.532  1.897  56.465
corr_plot     53.632  1.925  55.619
FSmethod      52.466  1.743  54.260
pred_ensembel 16.703  0.490  15.135
enrichfindP    0.498  0.075   9.501
* 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 4.4.2 (2024-10-31) -- "Pile of Leaves"
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 98.694853 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.188051 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.574713 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.516345 
iter  10 value 84.645482
iter  20 value 84.583753
final  value 84.583659 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.890650 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.835568 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.202296 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.729860 
iter  10 value 88.653938
iter  20 value 88.324831
iter  30 value 88.322522
final  value 88.322511 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.007987 
iter  10 value 94.112933
final  value 94.112903 
converged
Fitting Repeat 5 

# weights:  305
initial  value 138.477272 
iter  10 value 94.461539
iter  10 value 94.461538
iter  10 value 94.461538
final  value 94.461538 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.930359 
iter  10 value 93.342546
iter  20 value 87.291192
iter  30 value 83.653753
iter  40 value 83.464668
iter  50 value 83.437806
iter  60 value 83.436828
iter  70 value 83.429172
iter  80 value 83.404701
iter  90 value 83.023584
iter 100 value 82.632724
final  value 82.632724 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.948145 
iter  10 value 94.460126
iter  20 value 92.143875
iter  30 value 90.776201
iter  40 value 90.774686
final  value 90.604382 
converged
Fitting Repeat 3 

# weights:  507
initial  value 140.580698 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.452324 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.707159 
iter  10 value 88.969767
final  value 88.789517 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.533781 
iter  10 value 94.190585
iter  20 value 93.787191
iter  30 value 89.362994
iter  40 value 88.437282
iter  50 value 84.020124
iter  60 value 83.085658
iter  70 value 82.642850
iter  80 value 81.931815
iter  90 value 81.671045
iter 100 value 81.426476
final  value 81.426476 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.133828 
iter  10 value 94.434103
iter  20 value 94.162561
iter  30 value 93.242009
iter  40 value 85.910935
iter  50 value 83.233337
iter  60 value 82.011511
iter  70 value 81.811737
iter  80 value 81.712411
iter  90 value 81.540916
iter 100 value 81.176019
final  value 81.176019 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.834922 
iter  10 value 94.737651
iter  20 value 94.262177
iter  30 value 86.178142
iter  40 value 83.599455
iter  50 value 82.825810
iter  60 value 82.785788
iter  70 value 82.781782
final  value 82.781780 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.766393 
iter  10 value 94.490906
iter  20 value 92.793649
iter  30 value 91.410706
iter  40 value 91.206253
iter  50 value 90.912740
iter  60 value 90.902432
final  value 90.902320 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.389810 
iter  10 value 94.498325
iter  20 value 92.420450
iter  30 value 87.854332
iter  40 value 87.266281
iter  50 value 83.601342
iter  60 value 82.815318
iter  70 value 81.710055
iter  80 value 81.181095
final  value 81.172565 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.202823 
iter  10 value 94.517040
iter  20 value 87.979555
iter  30 value 86.274843
iter  40 value 85.473213
iter  50 value 84.588056
iter  60 value 83.573305
iter  70 value 82.271309
iter  80 value 81.725725
iter  90 value 81.519202
iter 100 value 81.178646
final  value 81.178646 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.241404 
iter  10 value 94.444961
iter  20 value 88.647941
iter  30 value 84.259695
iter  40 value 83.251823
iter  50 value 82.713781
iter  60 value 81.732916
iter  70 value 80.499376
iter  80 value 80.047117
iter  90 value 79.939711
iter 100 value 79.845107
final  value 79.845107 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 133.009098 
iter  10 value 95.326689
iter  20 value 94.842622
iter  30 value 90.245496
iter  40 value 87.514766
iter  50 value 85.479546
iter  60 value 84.583777
iter  70 value 83.707527
iter  80 value 82.154198
iter  90 value 81.559559
iter 100 value 81.545151
final  value 81.545151 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.540197 
iter  10 value 94.497330
iter  20 value 86.939814
iter  30 value 85.836365
iter  40 value 85.510167
iter  50 value 84.525735
iter  60 value 83.159142
iter  70 value 82.734650
iter  80 value 82.045378
iter  90 value 81.648774
iter 100 value 81.509427
final  value 81.509427 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.048070 
iter  10 value 94.500285
iter  20 value 90.838810
iter  30 value 90.425869
iter  40 value 89.134940
iter  50 value 83.966354
iter  60 value 83.098701
iter  70 value 82.998747
iter  80 value 82.855402
iter  90 value 81.154507
iter 100 value 80.281712
final  value 80.281712 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.439234 
iter  10 value 94.233397
iter  20 value 87.181012
iter  30 value 85.058364
iter  40 value 84.260990
iter  50 value 83.316877
iter  60 value 82.752399
iter  70 value 82.175183
iter  80 value 81.823089
iter  90 value 80.683298
iter 100 value 80.304503
final  value 80.304503 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.131747 
iter  10 value 94.109939
iter  20 value 85.267745
iter  30 value 83.924386
iter  40 value 83.438770
iter  50 value 82.887944
iter  60 value 82.714395
iter  70 value 82.572916
iter  80 value 82.500739
iter  90 value 82.451085
iter 100 value 82.258777
final  value 82.258777 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.762306 
iter  10 value 95.205432
iter  20 value 92.324738
iter  30 value 86.513031
iter  40 value 85.357419
iter  50 value 83.397752
iter  60 value 82.730531
iter  70 value 81.327917
iter  80 value 80.560287
iter  90 value 80.163040
iter 100 value 79.695423
final  value 79.695423 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.193884 
iter  10 value 94.304370
iter  20 value 85.663293
iter  30 value 83.518864
iter  40 value 83.190399
iter  50 value 81.721757
iter  60 value 80.154308
iter  70 value 79.851738
iter  80 value 79.816320
iter  90 value 79.807982
iter 100 value 79.791438
final  value 79.791438 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.836147 
iter  10 value 101.673344
iter  20 value 98.951509
iter  30 value 88.916186
iter  40 value 85.775581
iter  50 value 84.622858
iter  60 value 82.960186
iter  70 value 81.478650
iter  80 value 81.352945
iter  90 value 81.181695
iter 100 value 80.924531
final  value 80.924531 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.886864 
final  value 94.485953 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.708199 
iter  10 value 94.504097
final  value 94.444893 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.545535 
final  value 94.485796 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.999782 
final  value 94.469230 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.943858 
iter  10 value 94.136827
iter  20 value 94.107072
iter  30 value 94.106638
final  value 94.106072 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.961918 
iter  10 value 87.299045
iter  20 value 87.038115
iter  30 value 86.487441
iter  40 value 86.428941
iter  50 value 86.425809
iter  60 value 86.425085
final  value 86.424975 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.279518 
iter  10 value 94.489339
iter  20 value 94.483486
iter  30 value 90.764803
iter  40 value 85.523158
iter  50 value 85.515532
iter  60 value 85.396943
iter  70 value 85.342243
iter  80 value 85.339633
iter  90 value 85.338555
iter 100 value 83.058504
final  value 83.058504 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.672573 
iter  10 value 94.488920
iter  20 value 93.467488
iter  30 value 92.445060
iter  40 value 91.735876
iter  50 value 91.728989
iter  60 value 91.145727
iter  70 value 90.656301
iter  80 value 90.536750
iter  90 value 90.528171
iter 100 value 90.521816
final  value 90.521816 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.497763 
iter  10 value 94.489024
iter  20 value 94.281919
iter  30 value 85.531632
iter  40 value 84.540535
iter  50 value 84.538935
iter  60 value 84.455365
iter  70 value 84.342234
iter  80 value 84.339890
iter  90 value 84.263703
final  value 84.253709 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.233643 
iter  10 value 94.360568
iter  20 value 94.358470
iter  30 value 94.357817
iter  40 value 94.355009
iter  50 value 94.136327
iter  60 value 85.560035
iter  70 value 85.502383
final  value 85.502338 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.243018 
iter  10 value 94.478411
iter  20 value 94.471183
iter  30 value 93.742238
iter  40 value 89.739957
iter  50 value 84.328084
iter  60 value 84.265083
iter  70 value 84.250015
iter  80 value 84.238047
iter  90 value 84.232489
iter 100 value 84.232027
final  value 84.232027 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.393239 
iter  10 value 94.450025
iter  20 value 93.601109
iter  30 value 88.183765
iter  40 value 88.066990
final  value 88.066392 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.006448 
iter  10 value 94.407874
iter  20 value 93.442735
iter  30 value 88.672407
final  value 88.672246 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.590066 
iter  10 value 94.444639
iter  20 value 94.108037
iter  30 value 94.100545
final  value 94.100531 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.404145 
iter  10 value 94.475042
iter  20 value 94.423990
iter  30 value 86.981816
iter  40 value 83.435480
iter  50 value 83.433452
iter  60 value 83.432265
iter  70 value 83.112840
iter  80 value 82.729544
iter  90 value 81.428242
iter 100 value 78.888285
final  value 78.888285 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.311081 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.499621 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.984804 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.603120 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.958006 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.070306 
iter  10 value 94.252966
final  value 94.252921 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.339371 
final  value 93.567525 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.300227 
iter  10 value 92.754062
final  value 92.613874 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.773513 
final  value 94.252920 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.154442 
iter  10 value 94.090635
final  value 94.090583 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.823511 
iter  10 value 91.239248
iter  20 value 89.429105
iter  30 value 89.160217
iter  40 value 89.159981
final  value 89.159980 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.253834 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.161464 
iter  10 value 94.112906
final  value 94.112903 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.374575 
iter  10 value 94.090585
iter  20 value 88.389641
final  value 88.344498 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.967772 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.899810 
iter  10 value 94.488593
iter  20 value 91.580875
iter  30 value 84.624026
iter  40 value 84.129166
iter  50 value 83.317167
iter  60 value 83.186487
iter  70 value 83.163537
final  value 83.162997 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.410929 
iter  10 value 94.327344
iter  20 value 89.388877
iter  30 value 87.018281
iter  40 value 85.582575
iter  50 value 84.679398
iter  60 value 81.280597
iter  70 value 81.164176
iter  80 value 81.039960
iter  90 value 80.647531
iter 100 value 80.603247
final  value 80.603247 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.178094 
iter  10 value 94.574624
iter  20 value 94.488803
iter  30 value 88.950913
iter  40 value 85.004676
iter  50 value 83.236800
iter  60 value 80.990476
iter  70 value 80.828094
iter  80 value 80.680208
iter  90 value 80.447356
final  value 80.445769 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.211195 
iter  10 value 94.264279
iter  20 value 85.212755
iter  30 value 84.893385
iter  40 value 83.585297
iter  50 value 83.570166
final  value 83.567551 
converged
Fitting Repeat 5 

# weights:  103
initial  value 120.100490 
iter  10 value 94.159767
iter  20 value 87.282826
iter  30 value 86.307260
iter  40 value 85.162714
iter  50 value 83.834913
iter  60 value 83.651328
final  value 83.651174 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.348440 
iter  10 value 97.633729
iter  20 value 94.642325
iter  30 value 94.283343
iter  40 value 86.049638
iter  50 value 85.257460
iter  60 value 83.917854
iter  70 value 83.003050
iter  80 value 82.860820
iter  90 value 82.767486
iter 100 value 82.561902
final  value 82.561902 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.341271 
iter  10 value 94.477201
iter  20 value 86.969523
iter  30 value 85.705630
iter  40 value 84.974511
iter  50 value 83.576561
iter  60 value 83.416173
iter  70 value 83.368835
iter  80 value 83.361222
iter  90 value 83.340313
iter 100 value 83.268679
final  value 83.268679 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.222869 
iter  10 value 94.376334
iter  20 value 94.086246
iter  30 value 86.109702
iter  40 value 84.613702
iter  50 value 83.573632
iter  60 value 83.311641
iter  70 value 83.183390
iter  80 value 83.127403
iter  90 value 82.691850
iter 100 value 81.955084
final  value 81.955084 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.212368 
iter  10 value 94.036431
iter  20 value 93.134117
iter  30 value 91.885485
iter  40 value 84.497861
iter  50 value 84.146417
iter  60 value 83.887527
iter  70 value 83.280682
iter  80 value 83.158784
iter  90 value 83.088837
iter 100 value 81.760842
final  value 81.760842 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.042661 
iter  10 value 94.482472
iter  20 value 87.755400
iter  30 value 84.419004
iter  40 value 83.688939
iter  50 value 83.580408
iter  60 value 83.228030
iter  70 value 82.097888
iter  80 value 81.832452
iter  90 value 81.538720
iter 100 value 81.253106
final  value 81.253106 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.081771 
iter  10 value 94.250308
iter  20 value 90.550674
iter  30 value 83.919228
iter  40 value 81.692943
iter  50 value 81.246556
iter  60 value 80.626266
iter  70 value 80.303569
iter  80 value 79.752030
iter  90 value 79.658177
iter 100 value 79.622958
final  value 79.622958 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 133.281508 
iter  10 value 94.378460
iter  20 value 89.469800
iter  30 value 84.992806
iter  40 value 84.617178
iter  50 value 83.468642
iter  60 value 82.301661
iter  70 value 81.681872
iter  80 value 80.562836
iter  90 value 80.208371
iter 100 value 80.125125
final  value 80.125125 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.505448 
iter  10 value 96.319417
iter  20 value 94.297877
iter  30 value 84.129838
iter  40 value 82.197000
iter  50 value 81.634357
iter  60 value 81.085813
iter  70 value 79.994136
iter  80 value 79.456748
iter  90 value 79.042834
iter 100 value 79.014118
final  value 79.014118 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 133.183585 
iter  10 value 95.352178
iter  20 value 86.065072
iter  30 value 83.886969
iter  40 value 83.361770
iter  50 value 83.284181
iter  60 value 83.253520
iter  70 value 83.046327
iter  80 value 82.069790
iter  90 value 80.326455
iter 100 value 79.886077
final  value 79.886077 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.769469 
iter  10 value 94.008207
iter  20 value 87.809956
iter  30 value 85.824241
iter  40 value 85.450252
iter  50 value 85.124063
iter  60 value 83.897852
iter  70 value 82.228739
iter  80 value 80.947998
iter  90 value 80.095435
iter 100 value 79.315588
final  value 79.315588 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.804520 
final  value 94.485709 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.391184 
final  value 94.485713 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.525752 
iter  10 value 94.485951
iter  20 value 94.484233
iter  30 value 92.616762
iter  40 value 92.614574
iter  50 value 92.614441
iter  60 value 92.614380
iter  70 value 84.330581
iter  80 value 83.887025
iter  90 value 83.877941
final  value 83.877921 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.364429 
final  value 94.485946 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.303224 
final  value 94.485882 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.163344 
iter  10 value 94.489146
iter  20 value 94.484243
final  value 94.484214 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.241702 
iter  10 value 94.489028
iter  20 value 94.484231
iter  30 value 92.620205
final  value 92.614622 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.767526 
iter  10 value 94.489131
iter  20 value 94.376373
iter  30 value 90.894900
iter  40 value 86.522876
iter  50 value 83.142507
iter  60 value 83.036340
iter  70 value 83.022620
iter  80 value 83.001661
final  value 83.001550 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.528477 
iter  10 value 94.472018
iter  20 value 94.467543
iter  30 value 92.614690
iter  30 value 92.614690
iter  30 value 92.614690
final  value 92.614690 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.010995 
iter  10 value 94.485350
iter  20 value 94.475526
iter  30 value 85.683560
iter  40 value 84.382194
final  value 84.382147 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.512840 
iter  10 value 94.121441
iter  20 value 94.116026
iter  30 value 94.091726
iter  40 value 92.035601
iter  50 value 90.293708
iter  60 value 90.121262
iter  70 value 90.120412
iter  80 value 89.784855
iter  90 value 87.408225
iter 100 value 87.336069
final  value 87.336069 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.797521 
iter  10 value 84.602738
iter  20 value 84.489488
iter  30 value 83.993159
final  value 83.985124 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.001661 
iter  10 value 94.490415
iter  20 value 94.042264
iter  30 value 89.060484
iter  40 value 88.097094
iter  50 value 88.094240
iter  60 value 87.730087
iter  70 value 82.670266
iter  80 value 82.657526
iter  90 value 82.656081
iter 100 value 82.201899
final  value 82.201899 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.794872 
iter  10 value 94.475026
iter  20 value 94.468152
final  value 94.467160 
converged
Fitting Repeat 5 

# weights:  507
initial  value 144.697164 
iter  10 value 94.488646
iter  20 value 94.480962
iter  30 value 94.478703
iter  40 value 91.305052
iter  50 value 83.941543
iter  60 value 83.878640
iter  70 value 83.878563
iter  80 value 82.463174
iter  90 value 82.339892
iter 100 value 82.170140
final  value 82.170140 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.863277 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.981199 
iter  10 value 92.945456
final  value 92.945355 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.141665 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.823354 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.764487 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.558268 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.618582 
final  value 94.011429 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.688619 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.604528 
iter  10 value 89.748768
iter  20 value 89.447992
final  value 89.446857 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.285787 
iter  10 value 92.945372
final  value 92.945355 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.625790 
final  value 94.052907 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.455665 
final  value 94.052907 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.217571 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.406204 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.146437 
final  value 94.052907 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.817449 
iter  10 value 93.711301
iter  20 value 93.353769
iter  30 value 93.292907
iter  40 value 89.814150
iter  50 value 89.547767
iter  60 value 84.996426
iter  70 value 84.796259
iter  80 value 84.347067
iter  90 value 84.152788
iter 100 value 84.040202
final  value 84.040202 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.216426 
iter  10 value 94.070832
iter  20 value 93.847247
iter  30 value 93.380122
iter  40 value 93.131581
iter  50 value 93.039103
iter  60 value 89.843773
iter  70 value 88.718846
iter  80 value 86.671612
iter  90 value 85.482797
iter 100 value 83.622263
final  value 83.622263 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.096090 
iter  10 value 87.381372
iter  20 value 86.712444
iter  30 value 84.220771
iter  40 value 84.043803
iter  50 value 84.032958
iter  60 value 84.032171
iter  70 value 84.031810
final  value 84.031782 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.652845 
iter  10 value 93.341731
iter  20 value 86.795808
iter  30 value 86.765854
iter  40 value 86.759732
iter  50 value 86.757739
iter  60 value 86.671512
iter  70 value 86.629472
iter  80 value 84.383434
iter  90 value 84.116656
iter 100 value 84.074034
final  value 84.074034 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.898971 
iter  10 value 93.998609
iter  20 value 86.028751
iter  30 value 85.006953
iter  40 value 84.900381
iter  50 value 84.856752
final  value 84.855811 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.035523 
iter  10 value 95.273109
iter  20 value 93.076017
iter  30 value 90.914283
iter  40 value 87.755217
iter  50 value 87.249092
iter  60 value 84.274860
iter  70 value 83.983555
iter  80 value 83.699445
iter  90 value 83.500686
iter 100 value 82.936883
final  value 82.936883 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.702455 
iter  10 value 94.109061
iter  20 value 93.290171
iter  30 value 89.398110
iter  40 value 88.636572
iter  50 value 85.517737
iter  60 value 84.268569
iter  70 value 82.814068
iter  80 value 81.622342
iter  90 value 81.281218
iter 100 value 80.993907
final  value 80.993907 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.825100 
iter  10 value 94.305627
iter  20 value 87.992012
iter  30 value 87.310971
iter  40 value 86.421502
iter  50 value 86.160248
iter  60 value 83.655574
iter  70 value 82.103798
iter  80 value 81.754532
iter  90 value 81.639120
iter 100 value 81.600249
final  value 81.600249 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.713195 
iter  10 value 93.381348
iter  20 value 92.520849
iter  30 value 85.456143
iter  40 value 84.155714
iter  50 value 83.933440
iter  60 value 83.603691
iter  70 value 82.088418
iter  80 value 81.266818
iter  90 value 81.214916
iter 100 value 81.078266
final  value 81.078266 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.881605 
iter  10 value 92.852850
iter  20 value 91.433507
iter  30 value 91.151415
iter  40 value 88.680807
iter  50 value 85.372084
iter  60 value 83.603248
iter  70 value 82.343207
iter  80 value 82.067537
iter  90 value 81.679277
iter 100 value 81.568427
final  value 81.568427 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.735595 
iter  10 value 94.124512
iter  20 value 93.404427
iter  30 value 90.103413
iter  40 value 84.603738
iter  50 value 83.872198
iter  60 value 83.699577
iter  70 value 82.558312
iter  80 value 82.015643
iter  90 value 81.777292
iter 100 value 81.361712
final  value 81.361712 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.486746 
iter  10 value 93.995558
iter  20 value 93.111251
iter  30 value 89.085594
iter  40 value 84.818469
iter  50 value 84.184690
iter  60 value 83.506736
iter  70 value 82.024713
iter  80 value 81.271420
iter  90 value 81.054075
iter 100 value 81.045193
final  value 81.045193 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.157085 
iter  10 value 97.033503
iter  20 value 93.623821
iter  30 value 92.219849
iter  40 value 87.154492
iter  50 value 84.192664
iter  60 value 83.914128
iter  70 value 83.600771
iter  80 value 83.579356
iter  90 value 83.545458
iter 100 value 83.206734
final  value 83.206734 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.809436 
iter  10 value 93.755868
iter  20 value 86.471118
iter  30 value 85.204785
iter  40 value 84.728273
iter  50 value 83.384652
iter  60 value 83.008363
iter  70 value 82.742241
iter  80 value 82.691508
iter  90 value 82.660083
iter 100 value 82.652907
final  value 82.652907 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.514451 
iter  10 value 93.229616
iter  20 value 91.754455
iter  30 value 85.436414
iter  40 value 84.077245
iter  50 value 83.435412
iter  60 value 82.242357
iter  70 value 81.290670
iter  80 value 81.073137
iter  90 value 80.900186
iter 100 value 80.877973
final  value 80.877973 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.174387 
final  value 94.054669 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.926013 
iter  10 value 94.058797
final  value 94.055298 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.840470 
final  value 94.054364 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.978324 
final  value 94.054776 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.315248 
final  value 94.054648 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.356818 
iter  10 value 85.583564
iter  20 value 84.976841
iter  30 value 84.596019
iter  40 value 84.193565
iter  50 value 83.151265
iter  60 value 83.137745
iter  70 value 83.135458
iter  80 value 83.134860
iter  90 value 83.123410
iter 100 value 81.908252
final  value 81.908252 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.736575 
iter  10 value 92.951530
iter  20 value 92.950751
iter  30 value 92.946411
final  value 92.946357 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.357141 
iter  10 value 93.633670
iter  20 value 93.629651
final  value 93.629549 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.165983 
iter  10 value 94.057811
iter  20 value 93.992323
iter  30 value 92.946813
iter  40 value 92.946554
iter  50 value 87.661924
iter  60 value 85.855554
iter  70 value 85.789934
final  value 85.789928 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.394075 
iter  10 value 93.546881
iter  20 value 92.951168
iter  30 value 92.947376
final  value 92.946136 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.149414 
iter  10 value 92.998032
iter  20 value 92.899692
iter  30 value 92.895269
iter  40 value 92.887370
iter  50 value 92.820258
iter  60 value 92.556125
iter  70 value 87.957851
iter  80 value 85.982843
iter  90 value 85.620583
iter 100 value 81.170018
final  value 81.170018 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 94.901405 
iter  10 value 94.060972
iter  20 value 93.937802
iter  30 value 86.715808
iter  40 value 86.619612
iter  50 value 86.611332
iter  60 value 86.611142
iter  70 value 84.014084
iter  80 value 83.819178
iter  90 value 83.815329
final  value 83.815314 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.167724 
iter  10 value 88.594895
iter  20 value 86.430500
iter  30 value 86.421977
final  value 86.420714 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.308077 
iter  10 value 92.962121
iter  20 value 92.890701
iter  30 value 92.827944
iter  40 value 92.823696
iter  50 value 92.812708
iter  60 value 92.681898
iter  70 value 91.659750
iter  80 value 85.146385
iter  90 value 84.081201
iter 100 value 83.933078
final  value 83.933078 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.461049 
iter  10 value 94.060534
iter  20 value 93.429309
iter  30 value 92.827145
final  value 92.814627 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.442919 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.851606 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.262257 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.993198 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.922086 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.257032 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.424690 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.167935 
final  value 92.945739 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.238443 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.483648 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 136.149901 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.146472 
iter  10 value 93.552301
final  value 93.552265 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.415458 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.435096 
iter  10 value 92.578017
iter  20 value 92.259226
iter  30 value 92.255848
final  value 92.255844 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.866586 
final  value 93.904720 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.393659 
iter  10 value 93.963358
iter  20 value 91.585312
iter  30 value 84.931153
iter  40 value 84.171795
iter  50 value 82.878665
iter  60 value 82.611120
final  value 82.611106 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.726585 
iter  10 value 94.054890
iter  20 value 93.358000
iter  30 value 93.278387
iter  40 value 87.098159
iter  50 value 85.027748
iter  60 value 84.010914
iter  70 value 82.316043
iter  80 value 81.885480
iter  90 value 81.752514
final  value 81.752512 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.844332 
iter  10 value 94.035346
iter  20 value 89.311421
iter  30 value 84.191430
iter  40 value 83.240020
iter  50 value 82.961214
iter  60 value 82.708998
iter  70 value 82.611828
final  value 82.611106 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.833947 
iter  10 value 93.808635
iter  20 value 92.901653
iter  30 value 86.023319
iter  40 value 84.830505
iter  50 value 83.609292
iter  60 value 82.661722
iter  70 value 82.611450
final  value 82.611106 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.275723 
iter  10 value 94.058861
iter  20 value 93.742537
iter  30 value 92.618896
iter  40 value 85.850281
iter  50 value 85.710115
iter  60 value 84.229179
iter  70 value 83.328946
iter  80 value 82.447000
iter  90 value 82.162697
final  value 82.161625 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.260668 
iter  10 value 91.674076
iter  20 value 86.018872
iter  30 value 85.905039
iter  40 value 85.181826
iter  50 value 81.581498
iter  60 value 79.737893
iter  70 value 79.402414
iter  80 value 79.128900
iter  90 value 78.646844
iter 100 value 78.349125
final  value 78.349125 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.281929 
iter  10 value 93.696126
iter  20 value 89.268882
iter  30 value 85.345219
iter  40 value 84.803248
iter  50 value 83.403850
iter  60 value 82.891685
iter  70 value 81.519928
iter  80 value 81.103279
iter  90 value 80.242258
iter 100 value 79.785963
final  value 79.785963 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.288813 
iter  10 value 94.122059
iter  20 value 93.648500
iter  30 value 86.748413
iter  40 value 83.669957
iter  50 value 82.136664
iter  60 value 80.568841
iter  70 value 79.482957
iter  80 value 79.385649
iter  90 value 79.164133
iter 100 value 79.021957
final  value 79.021957 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.522714 
iter  10 value 94.137143
iter  20 value 87.190582
iter  30 value 86.025561
iter  40 value 85.470435
iter  50 value 84.746461
iter  60 value 82.144156
iter  70 value 80.612963
iter  80 value 80.548356
iter  90 value 80.516700
iter 100 value 80.334905
final  value 80.334905 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.546759 
iter  10 value 93.952852
iter  20 value 93.688030
iter  30 value 89.819160
iter  40 value 87.158446
iter  50 value 86.289685
iter  60 value 85.197505
iter  70 value 82.916398
iter  80 value 82.203024
iter  90 value 81.835972
iter 100 value 81.827653
final  value 81.827653 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.352371 
iter  10 value 93.930039
iter  20 value 88.978463
iter  30 value 87.237841
iter  40 value 85.676366
iter  50 value 82.573449
iter  60 value 81.349528
iter  70 value 79.154957
iter  80 value 78.960727
iter  90 value 78.680441
iter 100 value 78.581843
final  value 78.581843 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.437608 
iter  10 value 91.673950
iter  20 value 88.582271
iter  30 value 86.717051
iter  40 value 83.983102
iter  50 value 83.028817
iter  60 value 82.339054
iter  70 value 80.736395
iter  80 value 80.095012
iter  90 value 79.867464
iter 100 value 79.581024
final  value 79.581024 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.770290 
iter  10 value 94.349860
iter  20 value 90.936686
iter  30 value 87.505530
iter  40 value 85.119011
iter  50 value 80.055142
iter  60 value 79.163910
iter  70 value 78.563595
iter  80 value 78.271797
iter  90 value 78.247025
iter 100 value 78.223186
final  value 78.223186 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.244428 
iter  10 value 94.313687
iter  20 value 93.956595
iter  30 value 85.917878
iter  40 value 83.499735
iter  50 value 81.824370
iter  60 value 80.539967
iter  70 value 79.233465
iter  80 value 79.099018
iter  90 value 79.025247
iter 100 value 79.019823
final  value 79.019823 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.268641 
iter  10 value 93.969451
iter  20 value 89.390328
iter  30 value 88.009322
iter  40 value 86.933905
iter  50 value 84.912113
iter  60 value 83.750125
iter  70 value 82.795272
iter  80 value 82.182201
iter  90 value 81.801844
iter 100 value 81.750242
final  value 81.750242 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.000443 
final  value 94.054602 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.115814 
final  value 94.054413 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.198979 
final  value 94.054412 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.219928 
iter  10 value 86.408258
iter  20 value 84.074609
iter  30 value 84.005053
iter  40 value 84.004462
iter  50 value 82.445846
iter  60 value 82.305081
iter  70 value 82.304624
iter  80 value 82.259330
iter  90 value 82.148752
iter 100 value 82.147179
final  value 82.147179 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.225089 
final  value 94.054482 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.088083 
iter  10 value 90.989256
iter  20 value 90.887392
iter  30 value 90.724895
iter  40 value 90.550806
iter  50 value 90.550491
iter  60 value 90.549999
iter  70 value 90.549621
iter  80 value 90.549146
final  value 90.548752 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.170130 
iter  10 value 94.055548
iter  20 value 88.565200
iter  30 value 86.117929
iter  40 value 81.911429
iter  50 value 81.560136
iter  60 value 81.558551
iter  70 value 81.538476
iter  80 value 81.505649
iter  90 value 81.504959
iter 100 value 81.504432
final  value 81.504432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.361996 
iter  10 value 94.057877
iter  20 value 94.037294
iter  30 value 93.604869
final  value 93.604661 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.165788 
iter  10 value 94.058001
iter  20 value 93.904730
iter  30 value 88.011875
iter  40 value 82.424060
iter  50 value 82.423884
iter  50 value 82.423884
iter  50 value 82.423884
final  value 82.423884 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.228402 
iter  10 value 93.587715
iter  20 value 93.583895
iter  30 value 92.782999
iter  40 value 88.121083
iter  50 value 88.006526
iter  50 value 88.006525
iter  50 value 88.006525
final  value 88.006525 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.977759 
iter  10 value 91.175768
iter  20 value 91.169363
iter  30 value 90.733628
iter  40 value 90.541940
iter  50 value 90.425340
iter  60 value 90.325428
iter  70 value 90.303739
iter  80 value 90.268935
iter  90 value 90.255020
iter 100 value 90.254911
final  value 90.254911 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.197195 
iter  10 value 93.856923
iter  20 value 92.718369
iter  30 value 92.714651
iter  40 value 92.677632
iter  50 value 92.675204
iter  60 value 84.546629
iter  70 value 83.090755
iter  80 value 80.478590
iter  90 value 79.752097
iter 100 value 78.810210
final  value 78.810210 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.949399 
iter  10 value 93.886664
iter  20 value 93.878424
iter  30 value 93.318472
iter  40 value 93.273647
iter  50 value 84.807519
iter  60 value 82.372791
iter  70 value 82.144753
iter  80 value 82.134589
iter  90 value 82.128783
iter 100 value 82.126095
final  value 82.126095 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.994066 
iter  10 value 91.303970
iter  20 value 91.225992
iter  30 value 90.894566
iter  40 value 90.883894
iter  50 value 90.881700
iter  60 value 90.552071
iter  70 value 90.548999
iter  80 value 90.545780
iter  90 value 90.165980
iter 100 value 89.975664
final  value 89.975664 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.332992 
iter  10 value 93.912735
iter  20 value 93.104323
iter  30 value 93.103889
iter  40 value 93.055728
iter  50 value 91.047241
iter  60 value 82.588021
iter  70 value 81.863226
iter  80 value 81.477210
iter  90 value 81.359297
iter 100 value 81.351253
final  value 81.351253 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.440040 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.009920 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.806937 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.253596 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.697919 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.591791 
iter  10 value 94.467397
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.653441 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.380189 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.933111 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.981102 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.921963 
iter  10 value 94.467391
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.503007 
iter  10 value 88.274150
iter  20 value 87.744325
iter  30 value 87.741096
final  value 87.740932 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.870271 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.234063 
iter  10 value 88.727084
final  value 88.726318 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.790630 
final  value 94.064368 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.967124 
iter  10 value 94.002121
iter  20 value 89.793798
iter  30 value 86.355934
iter  40 value 85.441843
iter  50 value 85.195745
iter  60 value 84.735180
iter  70 value 84.185610
iter  80 value 84.088888
final  value 84.088686 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.896093 
iter  10 value 94.477177
iter  20 value 92.857933
iter  30 value 89.572687
iter  40 value 86.773394
iter  50 value 85.035150
iter  60 value 82.587464
iter  70 value 82.158726
iter  80 value 81.814672
iter  90 value 81.761776
iter 100 value 81.695798
final  value 81.695798 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.123280 
iter  10 value 94.537712
iter  20 value 94.485141
iter  30 value 90.359165
iter  40 value 87.823120
iter  50 value 87.472205
iter  60 value 86.616863
iter  70 value 85.952970
final  value 85.931146 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.180321 
iter  10 value 94.391357
iter  20 value 88.931083
iter  30 value 88.289524
iter  40 value 84.694605
iter  50 value 83.793135
iter  60 value 83.693328
iter  70 value 83.617606
iter  80 value 83.543719
iter  90 value 83.410222
iter 100 value 82.837066
final  value 82.837066 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.192540 
iter  10 value 94.485616
iter  20 value 94.158213
iter  30 value 88.120831
iter  40 value 85.072052
iter  50 value 84.922565
iter  60 value 84.693979
iter  70 value 83.939812
iter  80 value 83.670316
iter  90 value 83.634046
final  value 83.627339 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.658167 
iter  10 value 94.352098
iter  20 value 92.693074
iter  30 value 90.815121
iter  40 value 88.964531
iter  50 value 85.655250
iter  60 value 82.609903
iter  70 value 81.716124
iter  80 value 81.256505
iter  90 value 80.992577
iter 100 value 80.811480
final  value 80.811480 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.763301 
iter  10 value 94.514757
iter  20 value 94.412747
iter  30 value 91.860872
iter  40 value 89.290301
iter  50 value 84.263583
iter  60 value 83.209314
iter  70 value 82.707803
iter  80 value 82.246964
iter  90 value 81.929589
iter 100 value 81.537172
final  value 81.537172 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.172233 
iter  10 value 94.663966
iter  20 value 93.738703
iter  30 value 88.212825
iter  40 value 86.432054
iter  50 value 82.699402
iter  60 value 81.538608
iter  70 value 81.103827
iter  80 value 80.741258
iter  90 value 80.534750
iter 100 value 80.366348
final  value 80.366348 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.358527 
iter  10 value 94.487931
iter  20 value 93.241624
iter  30 value 86.732979
iter  40 value 84.309634
iter  50 value 83.948048
iter  60 value 83.027641
iter  70 value 82.646300
iter  80 value 81.395626
iter  90 value 81.244296
iter 100 value 81.160500
final  value 81.160500 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.967661 
iter  10 value 92.724715
iter  20 value 85.057121
iter  30 value 84.075635
iter  40 value 83.961019
iter  50 value 82.276907
iter  60 value 82.044595
iter  70 value 81.840827
iter  80 value 81.789889
iter  90 value 81.632198
iter 100 value 81.377836
final  value 81.377836 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.591038 
iter  10 value 94.173661
iter  20 value 88.364447
iter  30 value 87.434096
iter  40 value 87.192509
iter  50 value 85.305042
iter  60 value 83.563619
iter  70 value 82.974422
iter  80 value 81.598765
iter  90 value 81.325991
iter 100 value 81.023758
final  value 81.023758 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.788261 
iter  10 value 94.591382
iter  20 value 91.190038
iter  30 value 85.861100
iter  40 value 83.888593
iter  50 value 82.737299
iter  60 value 82.539514
iter  70 value 81.603359
iter  80 value 81.061298
iter  90 value 80.736949
iter 100 value 80.517442
final  value 80.517442 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.764943 
iter  10 value 94.612844
iter  20 value 92.047129
iter  30 value 90.912864
iter  40 value 87.295333
iter  50 value 82.452311
iter  60 value 81.487872
iter  70 value 81.295845
iter  80 value 81.136226
iter  90 value 80.955324
iter 100 value 80.765239
final  value 80.765239 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.518508 
iter  10 value 94.584130
iter  20 value 89.680128
iter  30 value 87.995473
iter  40 value 85.651747
iter  50 value 85.194716
iter  60 value 84.984815
iter  70 value 84.013251
iter  80 value 83.346202
iter  90 value 82.267392
iter 100 value 82.022290
final  value 82.022290 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.499680 
iter  10 value 93.926810
iter  20 value 87.225406
iter  30 value 86.360271
iter  40 value 83.802743
iter  50 value 83.510699
iter  60 value 82.520787
iter  70 value 82.366191
iter  80 value 82.215133
iter  90 value 82.134709
iter 100 value 81.906097
final  value 81.906097 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.042984 
final  value 94.485779 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.403155 
final  value 94.486023 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.144253 
final  value 94.485726 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.888210 
final  value 94.485938 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.841716 
final  value 94.485786 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.815066 
iter  10 value 94.489001
iter  20 value 94.470860
final  value 94.467688 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.380855 
iter  10 value 94.489192
iter  20 value 94.436252
iter  30 value 90.910165
iter  40 value 85.576955
iter  50 value 85.514291
iter  60 value 85.219847
final  value 85.211584 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.127205 
iter  10 value 94.378005
iter  20 value 92.996795
iter  30 value 83.770495
iter  40 value 83.532503
iter  50 value 83.531464
iter  60 value 83.531329
iter  70 value 83.531128
iter  80 value 83.530999
iter  90 value 83.530804
iter 100 value 82.476986
final  value 82.476986 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.680677 
iter  10 value 94.267216
iter  20 value 94.265176
iter  30 value 93.969120
iter  40 value 87.272663
iter  50 value 87.236065
final  value 87.235895 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.089758 
iter  10 value 94.489433
iter  20 value 94.423925
iter  30 value 84.878513
iter  40 value 84.871307
iter  50 value 84.864027
iter  60 value 84.862961
iter  70 value 83.570052
iter  80 value 83.375289
iter  90 value 81.713039
iter 100 value 80.004261
final  value 80.004261 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 138.109094 
iter  10 value 94.493213
iter  20 value 94.335870
iter  30 value 83.020085
iter  40 value 82.918130
iter  50 value 82.915875
iter  60 value 82.914971
iter  70 value 82.912629
iter  80 value 82.911617
iter  90 value 82.909771
final  value 82.909159 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.069923 
iter  10 value 94.500697
iter  20 value 94.369405
iter  30 value 91.281119
iter  40 value 86.780084
iter  50 value 86.761861
iter  60 value 85.063114
iter  70 value 84.096027
iter  80 value 84.003605
iter  90 value 83.911416
iter 100 value 83.910456
final  value 83.910456 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.247086 
iter  10 value 94.475011
iter  20 value 94.447684
iter  30 value 89.713606
iter  40 value 89.679578
iter  50 value 89.295299
iter  60 value 88.857977
iter  70 value 88.558032
iter  80 value 86.077607
iter  90 value 86.009438
iter 100 value 86.008015
final  value 86.008015 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.318914 
iter  10 value 94.492437
iter  20 value 94.486954
iter  30 value 94.478804
final  value 94.467452 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.093825 
iter  10 value 94.490705
iter  20 value 94.471282
iter  30 value 94.240117
iter  40 value 94.203124
iter  50 value 93.364996
iter  60 value 84.867318
iter  70 value 83.910163
iter  80 value 81.807796
iter  90 value 81.040625
iter 100 value 80.909511
final  value 80.909511 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 125.474619 
iter  10 value 117.870899
iter  20 value 117.850705
iter  30 value 112.986128
iter  40 value 106.187846
iter  50 value 105.074323
iter  60 value 104.941111
final  value 104.936230 
converged
Fitting Repeat 2 

# weights:  305
initial  value 131.685043 
iter  10 value 114.665743
iter  20 value 107.585377
iter  30 value 107.054795
iter  40 value 105.696195
final  value 105.673757 
converged
Fitting Repeat 3 

# weights:  305
initial  value 122.622015 
iter  10 value 117.554747
iter  20 value 117.532180
iter  30 value 115.492827
iter  40 value 114.803776
iter  50 value 114.797840
iter  60 value 104.830333
iter  70 value 103.974377
final  value 103.974143 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.909970 
iter  10 value 117.763810
iter  20 value 117.733093
iter  30 value 117.729403
iter  40 value 117.728526
iter  40 value 117.728525
iter  40 value 117.728525
final  value 117.728525 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.871591 
iter  10 value 117.763695
iter  20 value 117.759703
final  value 117.759648 
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 Jan 31 22:14:32 2025 
*********************************************** 
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 
 48.985   1.680 100.816