##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.1’
* 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 loading without being on the library search path ... 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 ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... WARNING
Codoc mismatches from Rd file 'pred_ensembel.Rd':
pred_ensembel
  Code: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 FALSE, filename = "plots.pdf")
  Docs: function(features, gold_standard, classifier = c("avNNet",
                 "svmRadial", "ranger"), resampling.method = "cv",
                 ncross = 2, repeats = 2, verboseIter = TRUE, plots =
                 TRUE, filename = "plots.pdf")
  Mismatches in argument default values:
    Name: 'plots' Code: FALSE Docs: TRUE

* 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
corr_plot     34.152  0.345  34.583
var_imp       33.433  0.404  33.837
FSmethod      32.637  0.602  33.322
pred_ensembel 12.623  0.100  11.374
enrichfindP    0.610  0.036  12.790
getFASTA       0.355  0.007   6.660
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 WARNING, 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.1’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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 103.016115 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.976479 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.713114 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.260387 
iter  10 value 93.843845
iter  20 value 93.773594
final  value 93.772973 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.713625 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.644510 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.749361 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.544381 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.741697 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.106432 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.307094 
iter  10 value 94.376480
iter  20 value 92.471354
final  value 91.891034 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.241996 
iter  10 value 89.191733
iter  20 value 88.387296
iter  30 value 88.381283
final  value 88.381265 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.465749 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.021928 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.637670 
iter  10 value 93.607310
final  value 93.607287 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.506145 
iter  10 value 94.482275
iter  20 value 93.229683
iter  30 value 85.984995
iter  40 value 85.440428
iter  50 value 85.354259
iter  60 value 85.113654
iter  70 value 84.135055
iter  80 value 83.693213
iter  90 value 83.624569
iter 100 value 83.609840
final  value 83.609840 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.913032 
iter  10 value 93.920740
iter  20 value 92.568182
iter  30 value 88.218347
iter  40 value 88.031546
iter  50 value 85.446225
iter  60 value 85.403808
iter  70 value 85.279192
iter  80 value 83.174095
iter  90 value 82.362943
iter 100 value 82.340079
final  value 82.340079 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.629894 
iter  10 value 94.589163
iter  20 value 94.456941
iter  30 value 93.803293
iter  40 value 93.765678
iter  50 value 93.420633
iter  60 value 89.605921
iter  70 value 85.033192
iter  80 value 84.774888
iter  90 value 84.539715
iter 100 value 83.934671
final  value 83.934671 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.583436 
iter  10 value 94.488656
iter  20 value 94.249868
iter  30 value 93.208463
iter  40 value 86.278393
iter  50 value 84.476330
iter  60 value 83.938286
iter  70 value 83.733396
iter  80 value 83.621360
iter  90 value 83.573771
final  value 83.573766 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.956683 
iter  10 value 94.487806
iter  20 value 93.797418
iter  30 value 93.771925
iter  40 value 93.760081
iter  50 value 89.763334
iter  60 value 86.957446
iter  70 value 86.587754
iter  80 value 85.622815
iter  90 value 85.266758
iter 100 value 85.127419
final  value 85.127419 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.807536 
iter  10 value 94.422331
iter  20 value 89.902841
iter  30 value 88.860352
iter  40 value 86.239815
iter  50 value 84.280573
iter  60 value 82.342507
iter  70 value 81.655790
iter  80 value 81.272936
iter  90 value 81.186000
iter 100 value 81.062883
final  value 81.062883 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.815388 
iter  10 value 94.656779
iter  20 value 93.719267
iter  30 value 92.718764
iter  40 value 88.015639
iter  50 value 87.463188
iter  60 value 87.227660
iter  70 value 86.573344
iter  80 value 83.903564
iter  90 value 82.149606
iter 100 value 81.560098
final  value 81.560098 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.452702 
iter  10 value 96.593788
iter  20 value 93.819603
iter  30 value 92.301115
iter  40 value 89.228461
iter  50 value 85.175762
iter  60 value 84.265571
iter  70 value 83.836380
iter  80 value 83.541299
iter  90 value 82.594905
iter 100 value 81.860924
final  value 81.860924 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.803386 
iter  10 value 93.341871
iter  20 value 86.306859
iter  30 value 84.635386
iter  40 value 83.607849
iter  50 value 83.023737
iter  60 value 81.911963
iter  70 value 81.361330
iter  80 value 80.970828
iter  90 value 80.762166
iter 100 value 80.684912
final  value 80.684912 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.909352 
iter  10 value 94.559028
iter  20 value 94.048725
iter  30 value 89.343915
iter  40 value 84.341059
iter  50 value 83.421955
iter  60 value 83.143520
iter  70 value 83.094396
iter  80 value 82.700662
iter  90 value 82.434920
iter 100 value 82.045533
final  value 82.045533 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.862841 
iter  10 value 94.803095
iter  20 value 87.209862
iter  30 value 86.503127
iter  40 value 85.386123
iter  50 value 84.807823
iter  60 value 83.081625
iter  70 value 82.080657
iter  80 value 81.473930
iter  90 value 81.204448
iter 100 value 81.167155
final  value 81.167155 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.286417 
iter  10 value 94.467920
iter  20 value 93.743054
iter  30 value 89.770452
iter  40 value 86.825023
iter  50 value 85.841528
iter  60 value 84.139676
iter  70 value 82.426772
iter  80 value 81.906570
iter  90 value 81.673696
iter 100 value 81.389609
final  value 81.389609 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.190828 
iter  10 value 93.517142
iter  20 value 86.991960
iter  30 value 85.008168
iter  40 value 82.826980
iter  50 value 82.543012
iter  60 value 82.382502
iter  70 value 82.115788
iter  80 value 81.678743
iter  90 value 81.017543
iter 100 value 80.814569
final  value 80.814569 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.124752 
iter  10 value 94.172196
iter  20 value 89.338301
iter  30 value 85.910308
iter  40 value 84.725498
iter  50 value 83.084432
iter  60 value 81.413953
iter  70 value 81.050306
iter  80 value 80.930456
iter  90 value 80.845437
iter 100 value 80.765508
final  value 80.765508 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.310937 
iter  10 value 94.584710
iter  20 value 91.996717
iter  30 value 89.986634
iter  40 value 85.559770
iter  50 value 83.449911
iter  60 value 82.930587
iter  70 value 82.382299
iter  80 value 82.026076
iter  90 value 81.639375
iter 100 value 81.499855
final  value 81.499855 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 122.011412 
iter  10 value 94.485986
final  value 94.484221 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.661309 
final  value 94.485912 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.624062 
final  value 94.485591 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.136220 
iter  10 value 94.276730
iter  10 value 94.276729
iter  10 value 94.276729
final  value 94.276729 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.165247 
final  value 94.485930 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.966701 
iter  10 value 94.190398
iter  20 value 94.186977
iter  30 value 93.640361
iter  40 value 93.619847
iter  50 value 93.618942
iter  60 value 93.607988
iter  70 value 90.623046
iter  80 value 88.272300
iter  90 value 85.595369
iter 100 value 83.650827
final  value 83.650827 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.409473 
iter  10 value 94.488552
iter  20 value 94.481336
iter  30 value 88.575958
iter  40 value 87.913178
iter  50 value 85.209639
iter  60 value 81.883256
iter  70 value 81.315912
iter  80 value 81.278467
iter  90 value 81.254475
iter 100 value 81.182501
final  value 81.182501 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.231050 
iter  10 value 94.488601
iter  20 value 94.448650
iter  30 value 86.536722
iter  40 value 86.036030
iter  50 value 86.034988
final  value 86.034739 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.179241 
iter  10 value 94.489157
iter  20 value 94.483162
final  value 94.275447 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.932245 
iter  10 value 94.480942
iter  20 value 94.280359
iter  30 value 94.279084
iter  40 value 94.267476
iter  50 value 92.312403
iter  60 value 92.241710
iter  70 value 91.702721
iter  80 value 91.546040
iter  90 value 91.259162
final  value 91.259135 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.759993 
iter  10 value 94.491431
iter  20 value 91.929413
iter  30 value 90.774224
iter  40 value 83.734126
final  value 83.724069 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.687504 
iter  10 value 94.467671
iter  20 value 93.713503
iter  30 value 86.813792
iter  40 value 83.981298
iter  50 value 83.806961
iter  60 value 82.161156
iter  70 value 81.627694
iter  80 value 81.601037
iter  90 value 81.592192
iter  90 value 81.592191
final  value 81.592191 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.499935 
iter  10 value 94.492156
iter  20 value 94.449732
iter  30 value 86.209629
iter  40 value 84.638984
iter  50 value 83.067685
iter  60 value 82.692928
iter  70 value 82.674438
iter  80 value 82.622678
final  value 82.619869 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.195513 
iter  10 value 94.298522
iter  20 value 94.282227
iter  30 value 94.276140
iter  40 value 86.436517
iter  50 value 82.881721
iter  60 value 82.687372
iter  70 value 82.657938
iter  80 value 82.646921
final  value 82.646193 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.097832 
iter  10 value 94.493124
iter  20 value 94.485324
iter  30 value 94.135235
iter  40 value 86.260905
iter  50 value 85.254756
iter  60 value 85.225271
final  value 85.225131 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.784032 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.847690 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.522898 
final  value 94.046703 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.436203 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.982916 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.272506 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.783694 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.235656 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.648897 
iter  10 value 93.991378
final  value 93.991342 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.837144 
final  value 94.046703 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.247047 
iter  10 value 94.019093
iter  10 value 94.019093
iter  10 value 94.019093
final  value 94.019093 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.076370 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.147613 
final  value 93.589492 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.089758 
final  value 93.991342 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.561342 
iter  10 value 94.076202
iter  20 value 82.871797
iter  30 value 82.159662
iter  40 value 81.761631
iter  50 value 81.761332
iter  50 value 81.761332
iter  50 value 81.761332
final  value 81.761332 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.844604 
iter  10 value 93.955394
iter  20 value 88.515539
iter  30 value 84.220496
iter  40 value 83.931106
iter  50 value 82.785742
iter  60 value 82.564373
final  value 82.539189 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.386078 
iter  10 value 94.414653
iter  20 value 94.147167
iter  30 value 94.144313
iter  40 value 94.008879
iter  50 value 87.550909
iter  60 value 85.327697
iter  70 value 83.874735
iter  80 value 83.397229
iter  90 value 83.058512
final  value 83.035409 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.741490 
iter  10 value 94.487010
iter  20 value 94.311497
iter  30 value 93.285880
iter  40 value 93.145581
iter  50 value 93.135997
iter  60 value 93.035616
iter  70 value 90.763881
iter  80 value 88.537966
iter  90 value 84.195147
iter 100 value 83.657991
final  value 83.657991 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.277627 
iter  10 value 94.969263
iter  20 value 92.346660
iter  30 value 84.468693
iter  40 value 83.890956
iter  50 value 83.313027
iter  60 value 82.661877
iter  70 value 82.539212
final  value 82.539189 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.610481 
iter  10 value 93.023878
iter  20 value 83.557925
iter  30 value 83.106876
iter  40 value 82.876619
iter  50 value 82.797598
iter  60 value 82.778363
final  value 82.778361 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.855486 
iter  10 value 94.329323
iter  20 value 93.226479
iter  30 value 93.077422
iter  40 value 88.008966
iter  50 value 83.511576
iter  60 value 82.348167
iter  70 value 81.116953
iter  80 value 80.867045
iter  90 value 80.742081
iter 100 value 80.680171
final  value 80.680171 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.844901 
iter  10 value 94.126271
iter  20 value 88.451399
iter  30 value 86.377357
iter  40 value 86.014372
iter  50 value 85.382011
iter  60 value 81.815678
iter  70 value 80.547586
iter  80 value 80.422119
iter  90 value 80.250142
iter 100 value 79.929464
final  value 79.929464 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.647352 
iter  10 value 94.518229
iter  20 value 91.623495
iter  30 value 86.365533
iter  40 value 85.211646
iter  50 value 83.983200
iter  60 value 82.955557
iter  70 value 82.153963
iter  80 value 81.032335
iter  90 value 80.686202
iter 100 value 80.519387
final  value 80.519387 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.680976 
iter  10 value 94.583965
iter  20 value 93.807533
iter  30 value 93.702464
iter  40 value 91.301818
iter  50 value 84.972092
iter  60 value 82.708814
iter  70 value 82.298828
iter  80 value 81.280076
iter  90 value 80.365890
iter 100 value 80.179338
final  value 80.179338 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.513786 
iter  10 value 94.779693
iter  20 value 89.734725
iter  30 value 88.304501
iter  40 value 86.449670
iter  50 value 83.355463
iter  60 value 82.508807
iter  70 value 82.319884
final  value 82.301623 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.856755 
iter  10 value 94.166595
iter  20 value 85.269455
iter  30 value 84.885087
iter  40 value 84.494599
iter  50 value 82.965242
iter  60 value 82.512106
iter  70 value 82.361768
iter  80 value 82.178002
iter  90 value 81.819847
iter 100 value 80.828696
final  value 80.828696 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.954206 
iter  10 value 92.660120
iter  20 value 86.735807
iter  30 value 86.262471
iter  40 value 86.167693
iter  50 value 85.275469
iter  60 value 82.186494
iter  70 value 82.047550
iter  80 value 81.690913
iter  90 value 81.521598
iter 100 value 81.337455
final  value 81.337455 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.055554 
iter  10 value 94.665958
iter  20 value 94.125001
iter  30 value 92.306421
iter  40 value 88.219275
iter  50 value 83.685048
iter  60 value 83.032205
iter  70 value 82.588042
iter  80 value 82.339215
iter  90 value 81.616853
iter 100 value 80.486379
final  value 80.486379 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.066836 
iter  10 value 94.745122
iter  20 value 86.720208
iter  30 value 84.146657
iter  40 value 83.040612
iter  50 value 82.514431
iter  60 value 81.379949
iter  70 value 81.083766
iter  80 value 80.337252
iter  90 value 79.968173
iter 100 value 79.935225
final  value 79.935225 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.732170 
iter  10 value 89.038114
iter  20 value 85.029917
iter  30 value 84.654158
iter  40 value 81.934905
iter  50 value 81.011295
iter  60 value 80.509156
iter  70 value 80.295144
iter  80 value 80.079547
iter  90 value 79.995223
iter 100 value 79.932840
final  value 79.932840 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 113.627582 
final  value 94.485710 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.532961 
iter  10 value 94.485753
iter  20 value 94.482040
iter  30 value 94.027251
final  value 94.027228 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.960792 
final  value 94.485831 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.814053 
final  value 94.485793 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.287460 
final  value 94.485921 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.749641 
iter  10 value 94.032025
iter  20 value 94.026215
iter  30 value 87.311454
iter  40 value 84.126191
iter  50 value 83.708174
final  value 83.706007 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.630875 
iter  10 value 94.488827
iter  20 value 89.863205
iter  30 value 86.309697
final  value 86.309648 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.429154 
iter  10 value 94.488847
iter  20 value 94.221629
iter  30 value 86.762957
iter  40 value 86.750977
iter  50 value 84.509253
iter  60 value 80.669065
iter  70 value 78.950360
iter  80 value 78.519418
iter  90 value 78.518002
iter 100 value 78.512134
final  value 78.512134 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 128.639144 
iter  10 value 94.489567
iter  20 value 94.454431
final  value 94.026771 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.159735 
iter  10 value 94.487355
iter  20 value 94.256691
iter  30 value 94.027424
final  value 94.027334 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.133526 
iter  10 value 94.035296
iter  20 value 94.029234
iter  30 value 94.027179
iter  40 value 87.222907
iter  50 value 86.328731
iter  60 value 86.255519
iter  70 value 85.455993
iter  80 value 84.540387
iter  90 value 84.539062
final  value 84.538289 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.847755 
iter  10 value 94.035427
iter  20 value 94.028334
final  value 94.027915 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.982294 
iter  10 value 89.728357
iter  20 value 88.122670
iter  30 value 88.106158
iter  40 value 88.105792
iter  50 value 88.099822
iter  60 value 87.186080
iter  70 value 87.163036
iter  80 value 83.953853
iter  90 value 81.528207
iter 100 value 80.653239
final  value 80.653239 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.207204 
iter  10 value 94.493039
iter  20 value 94.141904
iter  30 value 85.970678
iter  40 value 85.901071
iter  50 value 85.900782
iter  60 value 85.649682
iter  70 value 81.554560
iter  80 value 80.269928
iter  90 value 79.201655
iter 100 value 78.961985
final  value 78.961985 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.212002 
iter  10 value 94.489880
iter  20 value 94.061580
final  value 94.027216 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.933004 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 112.961543 
final  value 94.275363 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.081609 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.774704 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.811236 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.645872 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.378886 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.984401 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.481839 
iter  10 value 94.420838
final  value 94.420833 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.510363 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.322712 
iter  10 value 91.005262
final  value 89.080247 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.677510 
iter  10 value 94.297118
iter  20 value 93.065689
iter  30 value 92.215268
iter  40 value 91.982201
iter  50 value 91.981935
final  value 91.981910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.571482 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.155455 
iter  10 value 94.466824
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.529943 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.479238 
iter  10 value 94.486432
iter  20 value 94.219307
iter  30 value 94.140402
iter  40 value 91.288986
iter  50 value 87.157163
iter  60 value 86.958962
iter  70 value 86.815723
iter  80 value 86.045535
iter  90 value 85.907960
iter 100 value 85.868754
final  value 85.868754 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.499408 
iter  10 value 94.520690
iter  20 value 94.228474
iter  30 value 87.997786
iter  40 value 85.820713
iter  50 value 84.623053
iter  60 value 84.173394
iter  70 value 83.798267
iter  80 value 82.990067
iter  90 value 82.640018
iter 100 value 82.543717
final  value 82.543717 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.348716 
iter  10 value 94.488712
iter  20 value 90.571497
iter  30 value 85.915180
iter  40 value 84.913980
iter  50 value 84.411696
iter  60 value 84.255234
iter  70 value 84.249938
iter  80 value 84.239730
final  value 84.237094 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.845086 
iter  10 value 93.682606
iter  20 value 88.142043
iter  30 value 87.679312
iter  40 value 87.272125
iter  50 value 84.719679
iter  60 value 84.257461
iter  70 value 84.250009
final  value 84.249638 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.774746 
iter  10 value 94.593837
iter  20 value 94.471339
iter  30 value 87.396388
iter  40 value 85.612284
iter  50 value 85.518521
iter  60 value 83.848466
iter  70 value 83.373002
iter  80 value 82.967158
iter  90 value 82.786682
final  value 82.679705 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.272726 
iter  10 value 94.727013
iter  20 value 93.122729
iter  30 value 92.662472
iter  40 value 92.193313
iter  50 value 87.171944
iter  60 value 86.863072
iter  70 value 85.694035
iter  80 value 83.485140
iter  90 value 82.007118
iter 100 value 81.901654
final  value 81.901654 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.962654 
iter  10 value 94.761956
iter  20 value 86.841485
iter  30 value 85.280624
iter  40 value 83.735242
iter  50 value 83.096484
iter  60 value 82.596809
iter  70 value 82.031160
iter  80 value 81.846656
iter  90 value 81.649125
iter 100 value 81.476701
final  value 81.476701 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.092175 
iter  10 value 94.487623
iter  20 value 87.954476
iter  30 value 86.778342
iter  40 value 84.728530
iter  50 value 84.300335
iter  60 value 84.082566
iter  70 value 84.033517
iter  80 value 83.375270
iter  90 value 82.620693
iter 100 value 82.215937
final  value 82.215937 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.270607 
iter  10 value 94.294793
iter  20 value 88.316731
iter  30 value 86.828068
iter  40 value 83.567224
iter  50 value 82.733836
iter  60 value 82.289777
iter  70 value 82.051726
iter  80 value 81.660064
iter  90 value 81.620765
iter 100 value 81.562508
final  value 81.562508 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.698141 
iter  10 value 94.316484
iter  20 value 90.956542
iter  30 value 85.676417
iter  40 value 84.828461
iter  50 value 84.604175
iter  60 value 83.913794
iter  70 value 82.798388
iter  80 value 82.675172
iter  90 value 82.521357
iter 100 value 82.337779
final  value 82.337779 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 134.472346 
iter  10 value 94.469883
iter  20 value 94.191777
iter  30 value 88.169340
iter  40 value 86.327453
iter  50 value 85.177968
iter  60 value 84.803710
iter  70 value 84.474021
iter  80 value 83.172327
iter  90 value 82.088895
iter 100 value 81.777638
final  value 81.777638 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.019345 
iter  10 value 94.016391
iter  20 value 87.444027
iter  30 value 87.000777
iter  40 value 86.415336
iter  50 value 85.348444
iter  60 value 84.778497
iter  70 value 84.695083
iter  80 value 83.947582
iter  90 value 83.573273
iter 100 value 82.263626
final  value 82.263626 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.791949 
iter  10 value 94.829525
iter  20 value 93.355530
iter  30 value 91.585075
iter  40 value 85.148297
iter  50 value 84.546213
iter  60 value 83.327263
iter  70 value 82.274474
iter  80 value 81.866096
iter  90 value 81.576746
iter 100 value 81.341434
final  value 81.341434 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.684613 
iter  10 value 94.487178
iter  20 value 86.450460
iter  30 value 85.969188
iter  40 value 85.064243
iter  50 value 84.188486
iter  60 value 82.642831
iter  70 value 82.298286
iter  80 value 81.799628
iter  90 value 81.350625
iter 100 value 81.169515
final  value 81.169515 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.121622 
iter  10 value 93.183085
iter  20 value 86.381225
iter  30 value 84.044146
iter  40 value 84.012397
iter  50 value 83.964870
iter  60 value 83.544695
iter  70 value 82.717937
iter  80 value 82.085678
iter  90 value 81.909769
iter 100 value 81.819552
final  value 81.819552 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.634119 
iter  10 value 94.486158
final  value 94.484219 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.812988 
final  value 94.485836 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.143569 
final  value 94.485844 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.454738 
iter  10 value 94.468452
iter  20 value 94.466850
final  value 94.466836 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.566893 
final  value 94.485445 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.428547 
iter  10 value 94.164451
iter  20 value 94.160384
iter  30 value 89.176288
iter  40 value 85.889201
iter  50 value 85.374578
iter  60 value 83.657366
iter  70 value 81.326626
iter  80 value 80.870225
iter  90 value 80.720139
iter 100 value 80.640043
final  value 80.640043 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.528819 
iter  10 value 94.489115
iter  20 value 94.484476
iter  30 value 92.320782
iter  40 value 84.423924
iter  50 value 83.859580
iter  60 value 83.612759
iter  70 value 83.463273
iter  80 value 83.420644
iter  90 value 83.404137
iter 100 value 83.404109
final  value 83.404109 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.169405 
iter  10 value 94.490128
iter  20 value 93.807063
iter  30 value 93.219237
iter  40 value 87.892474
iter  50 value 85.385072
iter  60 value 83.992392
iter  70 value 83.588320
final  value 83.582797 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.288594 
iter  10 value 94.471725
iter  20 value 94.412470
iter  30 value 94.340043
iter  40 value 94.261695
iter  50 value 94.160208
final  value 94.160099 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.675969 
iter  10 value 94.489172
iter  20 value 94.452380
iter  30 value 86.053326
iter  40 value 86.027074
iter  50 value 85.624131
iter  60 value 84.984547
iter  70 value 83.588555
iter  80 value 83.318724
iter  90 value 83.311336
final  value 83.308211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.228577 
iter  10 value 94.475195
iter  20 value 94.468481
iter  30 value 87.645483
iter  40 value 84.874393
iter  50 value 83.565840
iter  60 value 82.742502
iter  70 value 82.627489
iter  80 value 82.617596
final  value 82.616964 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.710862 
iter  10 value 93.617506
iter  20 value 92.096699
iter  30 value 91.993978
iter  40 value 91.987960
iter  50 value 88.417557
iter  60 value 86.390918
iter  70 value 86.237237
iter  80 value 86.229505
iter  90 value 86.225265
iter 100 value 86.224198
final  value 86.224198 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.012782 
iter  10 value 94.489749
iter  20 value 93.370527
iter  30 value 84.736617
iter  40 value 84.726543
iter  50 value 84.725525
iter  60 value 84.724707
iter  70 value 84.724054
iter  80 value 84.708115
iter  90 value 84.706226
final  value 84.705121 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.342393 
iter  10 value 84.901988
iter  20 value 83.531493
iter  30 value 83.523722
iter  40 value 83.203523
iter  50 value 82.753949
iter  60 value 82.228952
iter  70 value 81.605772
iter  80 value 81.300697
iter  90 value 81.133541
iter 100 value 81.105541
final  value 81.105541 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.729020 
iter  10 value 94.491929
iter  20 value 94.484304
iter  30 value 92.035673
iter  40 value 84.736316
final  value 84.721754 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.522933 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.463235 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.074582 
iter  10 value 93.801491
iter  20 value 93.612149
final  value 93.612099 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.012626 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.849091 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.738866 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.185721 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.288664 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.061315 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.681052 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.379475 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 132.293994 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.631783 
iter  10 value 85.073594
final  value 85.015367 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.229900 
iter  10 value 91.848204
iter  10 value 91.848204
iter  10 value 91.848204
final  value 91.848204 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.543482 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.964992 
iter  10 value 93.913725
iter  20 value 85.327328
iter  30 value 80.561082
iter  40 value 80.325239
iter  50 value 79.873342
iter  60 value 79.234287
iter  70 value 78.953308
iter  80 value 78.899904
iter  90 value 78.836840
final  value 78.836703 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.729778 
iter  10 value 94.015998
iter  20 value 92.105579
iter  30 value 88.581323
iter  40 value 88.202264
iter  50 value 83.153296
iter  60 value 81.880890
iter  70 value 81.161980
iter  80 value 80.938738
final  value 80.930396 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.672501 
iter  10 value 94.082204
iter  20 value 94.005568
iter  30 value 85.996625
iter  40 value 84.301023
iter  50 value 83.477097
iter  60 value 82.521980
iter  70 value 82.392788
iter  80 value 82.098511
iter  90 value 81.723837
iter 100 value 81.715256
final  value 81.715256 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.276455 
iter  10 value 94.057588
iter  20 value 91.090959
iter  30 value 86.309914
iter  40 value 85.413189
iter  50 value 83.762343
iter  60 value 83.532433
iter  70 value 81.701958
iter  80 value 79.695985
iter  90 value 79.403741
iter 100 value 79.296295
final  value 79.296295 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.974316 
iter  10 value 94.043210
iter  20 value 93.847278
iter  30 value 84.076104
iter  40 value 83.271335
iter  50 value 82.807793
iter  60 value 81.181652
iter  70 value 80.463433
iter  80 value 80.373603
iter  90 value 78.826915
iter 100 value 78.440220
final  value 78.440220 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.618168 
iter  10 value 94.751434
iter  20 value 85.439062
iter  30 value 84.547129
iter  40 value 83.608900
iter  50 value 83.442964
iter  60 value 83.379241
iter  70 value 82.577775
iter  80 value 82.100492
iter  90 value 82.082980
iter 100 value 81.971546
final  value 81.971546 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.961144 
iter  10 value 93.522896
iter  20 value 91.423476
iter  30 value 83.117900
iter  40 value 81.420322
iter  50 value 80.716199
iter  60 value 80.605063
iter  70 value 79.899860
iter  80 value 77.875731
iter  90 value 76.949376
iter 100 value 76.266281
final  value 76.266281 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 137.442247 
iter  10 value 94.095032
iter  20 value 87.212442
iter  30 value 82.142732
iter  40 value 81.865724
iter  50 value 81.276353
iter  60 value 80.509202
iter  70 value 80.236504
iter  80 value 79.979076
iter  90 value 79.466332
iter 100 value 78.751102
final  value 78.751102 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.534595 
iter  10 value 93.727885
iter  20 value 92.411540
iter  30 value 92.298746
iter  40 value 88.119743
iter  50 value 81.263187
iter  60 value 78.902165
iter  70 value 78.248811
iter  80 value 78.029596
iter  90 value 77.963886
iter 100 value 77.807564
final  value 77.807564 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.648232 
iter  10 value 92.015189
iter  20 value 82.986330
iter  30 value 81.951452
iter  40 value 80.156240
iter  50 value 79.713471
iter  60 value 79.556343
iter  70 value 79.326251
iter  80 value 78.329705
iter  90 value 78.175257
iter 100 value 77.144636
final  value 77.144636 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.923547 
iter  10 value 94.056460
iter  20 value 83.895087
iter  30 value 81.690291
iter  40 value 78.709570
iter  50 value 77.939302
iter  60 value 77.431233
iter  70 value 76.809873
iter  80 value 76.735237
iter  90 value 76.549339
iter 100 value 76.093867
final  value 76.093867 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.675759 
iter  10 value 94.159348
iter  20 value 89.301028
iter  30 value 84.110473
iter  40 value 82.058235
iter  50 value 81.057993
iter  60 value 80.494390
iter  70 value 79.960372
iter  80 value 79.877721
iter  90 value 78.970022
iter 100 value 78.217257
final  value 78.217257 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.311810 
iter  10 value 94.355155
iter  20 value 88.362094
iter  30 value 85.110581
iter  40 value 81.339807
iter  50 value 77.425971
iter  60 value 77.003902
iter  70 value 76.808246
iter  80 value 76.688671
iter  90 value 76.450316
iter 100 value 76.347711
final  value 76.347711 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.735939 
iter  10 value 96.521866
iter  20 value 84.211178
iter  30 value 83.702187
iter  40 value 83.488082
iter  50 value 82.724915
iter  60 value 81.310756
iter  70 value 78.877371
iter  80 value 78.674104
iter  90 value 78.365522
iter 100 value 78.068521
final  value 78.068521 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.863496 
iter  10 value 94.086556
iter  20 value 87.546117
iter  30 value 84.758294
iter  40 value 83.550490
iter  50 value 82.219583
iter  60 value 81.796762
iter  70 value 81.659928
iter  80 value 81.521258
iter  90 value 79.724265
iter 100 value 78.400824
final  value 78.400824 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.348371 
final  value 94.054356 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.564950 
final  value 94.054582 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.631497 
final  value 94.054564 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.134967 
iter  10 value 94.054473
iter  20 value 93.983882
iter  30 value 90.877035
iter  40 value 90.867944
iter  50 value 90.677977
iter  60 value 90.675330
iter  70 value 90.674082
iter  80 value 90.674013
final  value 90.673945 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.236105 
final  value 94.054508 
converged
Fitting Repeat 1 

# weights:  305
initial  value 132.700626 
iter  10 value 94.058678
iter  20 value 94.051184
iter  30 value 88.108678
iter  40 value 87.722140
iter  50 value 87.720292
iter  60 value 87.720190
iter  70 value 87.720055
iter  80 value 87.719960
iter  80 value 87.719960
final  value 87.719960 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.908193 
iter  10 value 94.013514
iter  20 value 94.006225
iter  30 value 94.005019
final  value 94.005015 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.800936 
iter  10 value 94.057022
iter  20 value 93.628755
iter  30 value 81.164862
iter  40 value 81.158852
iter  50 value 80.928730
iter  60 value 79.396498
iter  70 value 77.018667
iter  80 value 75.322515
iter  90 value 74.874614
iter 100 value 74.725238
final  value 74.725238 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.200005 
iter  10 value 94.058280
iter  20 value 94.006140
iter  30 value 83.207881
iter  40 value 83.204965
iter  50 value 81.088017
iter  60 value 81.084512
iter  70 value 80.911470
iter  80 value 80.506128
iter  90 value 80.415568
iter 100 value 80.414624
final  value 80.414624 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.741209 
iter  10 value 94.058375
iter  20 value 93.479862
iter  30 value 92.100810
final  value 92.100070 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.158414 
iter  10 value 94.059805
iter  20 value 93.794964
iter  30 value 86.539342
iter  40 value 86.528405
iter  50 value 86.404832
iter  60 value 85.528287
iter  70 value 84.934725
iter  80 value 83.493824
iter  90 value 83.327467
iter 100 value 83.287354
final  value 83.287354 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.159936 
iter  10 value 94.017256
iter  20 value 94.005490
iter  30 value 94.004926
iter  40 value 83.389860
iter  50 value 80.369537
iter  60 value 80.346491
iter  70 value 80.241938
iter  80 value 80.235055
iter  90 value 79.457504
iter 100 value 75.211107
final  value 75.211107 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.167479 
iter  10 value 94.017132
iter  20 value 88.168477
iter  30 value 81.156774
iter  40 value 81.020382
iter  50 value 81.019949
final  value 81.019755 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.252263 
iter  10 value 94.061386
iter  20 value 93.946032
iter  30 value 85.379869
iter  40 value 85.323507
iter  50 value 85.099831
iter  50 value 85.099830
iter  50 value 85.099830
final  value 85.099830 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.927113 
iter  10 value 93.266605
iter  20 value 93.264257
iter  30 value 93.154158
iter  40 value 91.969428
iter  50 value 89.619084
iter  60 value 89.611672
iter  70 value 89.610700
final  value 89.610689 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.590285 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.263059 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.296028 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.995690 
final  value 94.044445 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.038230 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.043329 
final  value 93.893853 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.751899 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.954438 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.643810 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.856658 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.506572 
iter  10 value 94.023443
final  value 94.023305 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.306952 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.179853 
iter  10 value 93.576975
iter  20 value 93.510263
final  value 93.510217 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.366195 
iter  10 value 91.726512
iter  20 value 91.433438
iter  30 value 91.432754
final  value 91.432749 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.059119 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.502911 
iter  10 value 94.058550
iter  20 value 93.796508
iter  30 value 90.849797
iter  40 value 89.121335
iter  50 value 86.747964
iter  60 value 84.027334
iter  70 value 82.973850
iter  80 value 82.821226
iter  90 value 82.760053
iter 100 value 82.676894
final  value 82.676894 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.886024 
iter  10 value 94.056115
iter  20 value 93.841595
iter  30 value 88.544131
iter  40 value 86.882384
iter  50 value 86.520696
iter  60 value 85.687003
iter  70 value 84.791504
iter  80 value 83.070168
iter  90 value 82.891901
iter 100 value 82.373107
final  value 82.373107 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.679910 
iter  10 value 94.077638
iter  20 value 93.368031
iter  30 value 88.489239
iter  40 value 85.767319
iter  50 value 85.664966
iter  60 value 85.593042
iter  70 value 85.483616
iter  80 value 83.711340
iter  90 value 83.236868
iter 100 value 83.070256
final  value 83.070256 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.385935 
iter  10 value 94.056700
iter  20 value 85.578898
iter  30 value 84.998406
iter  40 value 84.910098
iter  50 value 84.745235
iter  60 value 84.657700
iter  70 value 84.648377
iter  70 value 84.648377
iter  70 value 84.648377
final  value 84.648377 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.800632 
iter  10 value 94.045025
iter  20 value 89.159252
iter  30 value 87.826959
iter  40 value 86.266603
iter  50 value 85.700682
iter  60 value 85.221892
iter  70 value 85.117955
iter  80 value 85.076766
final  value 85.076528 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.591716 
iter  10 value 94.266761
iter  20 value 93.825376
iter  30 value 90.021938
iter  40 value 87.559313
iter  50 value 86.768801
iter  60 value 86.610150
iter  70 value 86.575156
iter  80 value 84.056898
iter  90 value 83.582010
iter 100 value 83.242615
final  value 83.242615 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.342003 
iter  10 value 94.021884
iter  20 value 90.554058
iter  30 value 86.695405
iter  40 value 86.563882
iter  50 value 86.257999
iter  60 value 84.265705
iter  70 value 82.890482
iter  80 value 82.220797
iter  90 value 82.053978
iter 100 value 81.916274
final  value 81.916274 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.339606 
iter  10 value 94.101083
iter  20 value 88.462019
iter  30 value 84.877183
iter  40 value 84.688169
iter  50 value 84.633722
iter  60 value 84.628012
iter  70 value 84.571444
iter  80 value 83.799292
iter  90 value 83.252703
iter 100 value 83.155554
final  value 83.155554 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.680977 
iter  10 value 94.125578
iter  20 value 93.822816
iter  30 value 91.375944
iter  40 value 85.050116
iter  50 value 83.472781
iter  60 value 83.088221
iter  70 value 82.261849
iter  80 value 81.994841
iter  90 value 81.441638
iter 100 value 81.331003
final  value 81.331003 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.400890 
iter  10 value 94.085793
iter  20 value 87.396585
iter  30 value 86.540060
iter  40 value 85.931419
iter  50 value 84.401256
iter  60 value 83.639348
iter  70 value 82.637421
iter  80 value 81.743513
iter  90 value 81.423509
iter 100 value 81.357517
final  value 81.357517 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.525765 
iter  10 value 93.619487
iter  20 value 88.885108
iter  30 value 86.657085
iter  40 value 86.232829
iter  50 value 85.042251
iter  60 value 83.450452
iter  70 value 82.048605
iter  80 value 81.535048
iter  90 value 81.223037
iter 100 value 80.655386
final  value 80.655386 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.936385 
iter  10 value 94.378991
iter  20 value 94.078617
iter  30 value 93.798847
iter  40 value 93.677765
iter  50 value 87.377624
iter  60 value 82.727625
iter  70 value 82.140808
iter  80 value 81.515421
iter  90 value 81.455671
iter 100 value 81.326583
final  value 81.326583 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.187099 
iter  10 value 94.364321
iter  20 value 93.359243
iter  30 value 87.094014
iter  40 value 82.981636
iter  50 value 81.325396
iter  60 value 80.812566
iter  70 value 80.659248
iter  80 value 80.585949
iter  90 value 80.506830
iter 100 value 80.454872
final  value 80.454872 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.972197 
iter  10 value 94.095517
iter  20 value 93.470811
iter  30 value 86.858156
iter  40 value 85.839132
iter  50 value 82.011602
iter  60 value 81.266203
iter  70 value 80.958905
iter  80 value 80.813810
iter  90 value 80.808279
iter 100 value 80.794552
final  value 80.794552 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.276455 
iter  10 value 94.033237
iter  20 value 86.757002
iter  30 value 83.610007
iter  40 value 81.829885
iter  50 value 81.279761
iter  60 value 80.942090
iter  70 value 80.799621
iter  80 value 80.741166
iter  90 value 80.652570
iter 100 value 80.624524
final  value 80.624524 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.448045 
final  value 94.054575 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.458171 
final  value 94.054471 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.130957 
final  value 94.054799 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.683654 
final  value 93.630181 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.991792 
final  value 94.054671 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.785577 
iter  10 value 94.057729
iter  20 value 94.053160
iter  30 value 86.645371
final  value 86.620553 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.960468 
iter  10 value 86.496066
iter  20 value 86.494076
iter  30 value 86.486138
iter  40 value 85.811320
iter  50 value 85.448120
iter  60 value 85.445061
iter  70 value 85.425662
iter  80 value 85.415218
iter  90 value 85.415101
iter 100 value 85.415060
final  value 85.415060 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.976101 
iter  10 value 94.057108
iter  20 value 93.986593
iter  30 value 86.292808
iter  40 value 84.918044
iter  50 value 84.892314
iter  60 value 84.669816
iter  70 value 84.503725
iter  80 value 84.498128
iter  90 value 83.907012
iter 100 value 83.671031
final  value 83.671031 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.076429 
iter  10 value 94.037890
iter  20 value 86.677214
iter  30 value 84.174597
iter  40 value 83.850678
iter  50 value 83.790988
iter  60 value 83.264042
iter  70 value 82.190856
final  value 82.080674 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.983177 
iter  10 value 94.057868
iter  20 value 94.053060
iter  30 value 88.623856
final  value 87.376211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.383513 
iter  10 value 94.061726
iter  20 value 93.790435
iter  30 value 92.332791
iter  40 value 92.046819
iter  50 value 84.969426
iter  60 value 84.784483
iter  70 value 84.782817
iter  80 value 84.767390
iter  90 value 84.700677
final  value 84.700229 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.714389 
iter  10 value 93.468146
iter  20 value 93.462130
iter  30 value 93.455757
iter  40 value 93.098408
iter  50 value 92.855681
iter  60 value 92.855596
iter  70 value 88.468071
iter  80 value 83.086304
iter  90 value 82.626943
iter 100 value 82.387532
final  value 82.387532 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.188334 
iter  10 value 94.062374
iter  20 value 94.053173
iter  30 value 94.005507
iter  40 value 87.377414
iter  50 value 87.376954
iter  60 value 87.350108
iter  70 value 87.220656
iter  80 value 87.218137
final  value 87.217956 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.953690 
iter  10 value 94.060296
iter  20 value 93.847429
iter  30 value 93.840308
iter  40 value 86.184036
iter  50 value 85.117711
iter  60 value 85.097222
iter  70 value 85.096342
final  value 85.096315 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.631906 
iter  10 value 94.041182
iter  20 value 89.141705
iter  30 value 86.348408
iter  40 value 84.838613
iter  50 value 84.835088
iter  60 value 84.820384
iter  70 value 84.801443
iter  80 value 84.799230
iter  90 value 82.453921
iter 100 value 81.352414
final  value 81.352414 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 120.474312 
iter  10 value 117.763522
iter  20 value 117.746750
iter  30 value 108.568597
iter  40 value 108.524704
iter  50 value 104.872331
iter  60 value 102.811244
final  value 102.747210 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.986708 
iter  10 value 117.893072
iter  20 value 108.120470
final  value 106.779624 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.957917 
iter  10 value 117.440348
iter  20 value 107.328934
iter  30 value 106.646599
iter  40 value 106.644571
iter  40 value 106.644571
final  value 106.644571 
converged
Fitting Repeat 4 

# weights:  305
initial  value 127.708967 
iter  10 value 117.763531
iter  20 value 117.759270
iter  30 value 117.547144
iter  40 value 108.456126
iter  50 value 105.911648
iter  60 value 101.896204
iter  70 value 101.579487
iter  80 value 101.565066
final  value 101.565021 
converged
Fitting Repeat 5 

# weights:  305
initial  value 140.063945 
iter  10 value 117.895574
iter  20 value 117.513367
iter  30 value 113.887401
iter  40 value 109.125538
iter  50 value 106.141062
iter  60 value 105.474106
iter  70 value 105.372666
iter  70 value 105.372665
iter  70 value 105.372665
final  value 105.372665 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Dec 23 00:15:20 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 
 41.823   1.929  92.152