##############################################################################
##############################################################################
###
### 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     34.175  0.381  34.591
var_imp       33.463  0.382  33.904
FSmethod      33.150  0.637  33.811
pred_ensembel 12.930  0.107  11.662
enrichfindP    0.542  0.036  14.688
getFASTA       0.410  0.008   6.469
* 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 100.865107 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.009544 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.593606 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.759149 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.618909 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.943997 
final  value 94.038252 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.502686 
iter  10 value 93.905199
iter  20 value 93.881226
iter  20 value 93.881226
iter  20 value 93.881226
final  value 93.881226 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.094243 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.877412 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.294812 
iter  10 value 93.962989
iter  20 value 93.571741
final  value 93.571532 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.921803 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 92.575101 
iter  10 value 86.268667
final  value 86.268064 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.911165 
final  value 94.052909 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.057733 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.811289 
iter  10 value 93.994907
iter  20 value 92.388385
iter  30 value 86.271275
final  value 86.264140 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.123601 
iter  10 value 94.147526
iter  20 value 93.894644
iter  30 value 91.808238
iter  40 value 91.251176
iter  50 value 87.628231
iter  60 value 87.125097
iter  70 value 86.652060
iter  80 value 84.424074
iter  90 value 84.368000
final  value 84.367144 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.200886 
iter  10 value 92.869905
iter  20 value 89.796485
iter  30 value 87.624723
iter  40 value 86.992689
iter  50 value 86.594918
final  value 86.593700 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.838149 
iter  10 value 93.962582
iter  20 value 93.825378
iter  30 value 88.350816
iter  40 value 85.588544
iter  50 value 84.182529
iter  60 value 83.671759
iter  70 value 83.634900
iter  80 value 83.574864
iter  90 value 83.214440
iter 100 value 83.108524
final  value 83.108524 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.252194 
iter  10 value 94.048029
iter  20 value 93.131008
iter  30 value 88.212768
iter  40 value 87.242393
iter  50 value 86.758505
iter  60 value 84.922169
iter  70 value 84.523034
iter  80 value 83.701856
iter  90 value 83.336789
iter 100 value 83.108318
final  value 83.108318 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.764388 
iter  10 value 93.291654
iter  20 value 88.335380
iter  30 value 85.771351
iter  40 value 85.427513
iter  50 value 85.285333
iter  60 value 85.279521
final  value 85.279515 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.150004 
iter  10 value 94.158676
iter  20 value 93.647646
iter  30 value 93.070662
iter  40 value 88.844195
iter  50 value 85.645363
iter  60 value 84.766223
iter  70 value 84.507560
iter  80 value 84.130556
iter  90 value 83.551591
iter 100 value 82.778050
final  value 82.778050 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.918310 
iter  10 value 95.941929
iter  20 value 93.916527
iter  30 value 87.944965
iter  40 value 86.848377
iter  50 value 86.079059
iter  60 value 84.509896
iter  70 value 82.821828
iter  80 value 82.327466
iter  90 value 81.835265
iter 100 value 81.761234
final  value 81.761234 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.392647 
iter  10 value 91.523587
iter  20 value 90.109867
iter  30 value 84.529943
iter  40 value 82.999944
iter  50 value 82.643086
iter  60 value 82.381107
iter  70 value 82.330525
iter  80 value 82.318611
iter  90 value 82.248089
iter 100 value 82.119631
final  value 82.119631 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.756175 
iter  10 value 94.240696
iter  20 value 89.132509
iter  30 value 86.310902
iter  40 value 84.071743
iter  50 value 82.965994
iter  60 value 82.534399
iter  70 value 82.091478
iter  80 value 81.997252
iter  90 value 81.921580
iter 100 value 81.793182
final  value 81.793182 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.491844 
iter  10 value 93.872081
iter  20 value 87.883430
iter  30 value 86.389148
iter  40 value 84.512735
iter  50 value 84.258580
iter  60 value 84.168685
iter  70 value 84.153982
iter  80 value 84.144839
iter  90 value 84.126202
iter 100 value 84.106345
final  value 84.106345 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.353872 
iter  10 value 94.120475
iter  20 value 93.858206
iter  30 value 91.182374
iter  40 value 87.208504
iter  50 value 86.398456
iter  60 value 86.165203
iter  70 value 86.111523
iter  80 value 86.086740
iter  90 value 85.815541
iter 100 value 84.543673
final  value 84.543673 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.018363 
iter  10 value 94.138665
iter  20 value 93.667106
iter  30 value 90.702421
iter  40 value 90.092762
iter  50 value 87.989729
iter  60 value 86.947333
iter  70 value 84.773224
iter  80 value 84.069019
iter  90 value 83.833411
iter 100 value 83.158974
final  value 83.158974 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.218616 
iter  10 value 94.048422
iter  20 value 89.971069
iter  30 value 88.923747
iter  40 value 88.212906
iter  50 value 87.506385
iter  60 value 85.947849
iter  70 value 85.316488
iter  80 value 84.929326
iter  90 value 84.164223
iter 100 value 83.693120
final  value 83.693120 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.231262 
iter  10 value 94.793932
iter  20 value 89.743660
iter  30 value 86.155274
iter  40 value 84.687352
iter  50 value 84.332963
iter  60 value 84.020846
iter  70 value 83.962777
iter  80 value 83.944867
iter  90 value 83.671929
iter 100 value 82.917836
final  value 82.917836 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.244978 
iter  10 value 94.299181
iter  20 value 87.181028
iter  30 value 86.751492
iter  40 value 85.582331
iter  50 value 85.385601
iter  60 value 83.903313
iter  70 value 82.418616
iter  80 value 82.028634
iter  90 value 81.913034
iter 100 value 81.659991
final  value 81.659991 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.228227 
iter  10 value 94.039700
iter  20 value 94.038349
final  value 94.038270 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.518268 
final  value 94.054399 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.378640 
final  value 94.054790 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.092402 
iter  10 value 94.054708
iter  20 value 94.050331
iter  30 value 94.040186
iter  40 value 94.039700
iter  50 value 94.039423
iter  60 value 94.038992
iter  70 value 94.038312
final  value 94.038261 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.315731 
final  value 94.054296 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.894499 
iter  10 value 94.057266
iter  20 value 94.053053
final  value 94.053019 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.999469 
iter  10 value 93.814932
iter  20 value 93.810292
final  value 93.810286 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.548087 
iter  10 value 90.531749
iter  20 value 86.254215
iter  30 value 86.203509
iter  40 value 86.022704
iter  50 value 86.018741
iter  60 value 85.998335
iter  70 value 84.923990
iter  80 value 84.701085
final  value 84.700975 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.963604 
iter  10 value 94.057322
iter  20 value 94.039471
iter  30 value 91.431193
iter  40 value 91.413402
iter  50 value 87.379611
iter  60 value 87.189582
iter  70 value 87.119956
iter  80 value 87.112689
iter  90 value 87.107951
iter 100 value 87.099401
final  value 87.099401 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.321096 
iter  10 value 94.057434
iter  20 value 94.038580
iter  30 value 91.402213
iter  40 value 89.643166
iter  50 value 89.640043
iter  60 value 89.509633
iter  70 value 89.470729
iter  80 value 87.946863
iter  90 value 87.593817
iter 100 value 87.590343
final  value 87.590343 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.473692 
iter  10 value 93.952952
iter  20 value 93.951080
iter  30 value 90.855150
iter  40 value 86.066678
iter  50 value 86.019519
iter  60 value 86.019136
final  value 86.018226 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.476804 
iter  10 value 93.807711
iter  20 value 93.802728
final  value 93.801707 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.625760 
iter  10 value 93.808978
iter  20 value 93.803949
iter  30 value 87.397996
iter  40 value 86.708971
iter  50 value 86.369194
iter  60 value 85.548829
iter  70 value 85.315304
iter  80 value 85.315046
iter  90 value 85.292510
final  value 85.292243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.731943 
iter  10 value 94.046229
iter  20 value 94.040179
final  value 94.040112 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.940429 
iter  10 value 88.545112
iter  20 value 87.947610
iter  30 value 87.142430
iter  40 value 86.497958
iter  50 value 86.494131
iter  50 value 86.494131
final  value 86.494131 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.903925 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.467738 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.329076 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.148750 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.613485 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.596576 
iter  10 value 93.540495
final  value 93.540410 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.502612 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.907921 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.063591 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.290178 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 129.508516 
iter  10 value 95.664707
iter  20 value 87.797065
final  value 87.794120 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.032404 
iter  10 value 93.579111
final  value 93.558233 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.589598 
iter  10 value 93.772975
final  value 93.772973 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.938082 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.954062 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.167062 
iter  10 value 94.293787
iter  20 value 90.442567
iter  30 value 89.177742
iter  40 value 83.409576
iter  50 value 82.837922
iter  60 value 82.292965
iter  70 value 80.910676
iter  80 value 80.522051
final  value 80.513414 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.769249 
iter  10 value 94.075459
iter  20 value 92.594291
iter  30 value 87.768885
iter  40 value 84.677618
iter  50 value 83.079670
iter  60 value 82.929279
final  value 82.928646 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.098467 
iter  10 value 94.486947
iter  20 value 93.898722
iter  30 value 93.598077
iter  40 value 93.529364
iter  50 value 93.529291
iter  50 value 93.529290
iter  50 value 93.529290
final  value 93.529290 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.240286 
iter  10 value 94.392754
iter  20 value 92.072190
iter  30 value 91.758768
iter  40 value 90.844035
iter  50 value 85.250622
iter  60 value 81.967218
iter  70 value 81.896023
iter  80 value 81.186287
iter  90 value 80.827822
iter 100 value 80.514645
final  value 80.514645 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.604220 
iter  10 value 94.472204
iter  20 value 86.783734
iter  30 value 85.418448
iter  40 value 85.004190
iter  50 value 84.019873
iter  60 value 83.154304
iter  70 value 82.226044
iter  80 value 81.915849
iter  90 value 81.179360
iter 100 value 81.133358
final  value 81.133358 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.842399 
iter  10 value 95.287939
iter  20 value 94.467006
iter  30 value 93.822309
iter  40 value 91.783654
iter  50 value 89.347465
iter  60 value 87.531080
iter  70 value 81.597558
iter  80 value 80.427822
iter  90 value 79.854745
iter 100 value 79.596919
final  value 79.596919 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.928009 
iter  10 value 94.418435
iter  20 value 93.723001
iter  30 value 93.397848
iter  40 value 85.779979
iter  50 value 85.149382
iter  60 value 84.611419
iter  70 value 84.280177
iter  80 value 84.013999
iter  90 value 83.764384
iter 100 value 83.592816
final  value 83.592816 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.407101 
iter  10 value 94.432087
iter  20 value 88.409069
iter  30 value 87.862827
iter  40 value 82.264175
iter  50 value 80.722042
iter  60 value 79.723262
iter  70 value 79.556517
iter  80 value 79.510131
iter  90 value 79.464876
iter 100 value 79.363522
final  value 79.363522 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.373116 
iter  10 value 94.403814
iter  20 value 91.210957
iter  30 value 90.042613
iter  40 value 89.662589
iter  50 value 87.834787
iter  60 value 85.994581
iter  70 value 82.809853
iter  80 value 81.574985
iter  90 value 80.492682
iter 100 value 80.297175
final  value 80.297175 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 128.074728 
iter  10 value 94.651641
iter  20 value 93.862469
iter  30 value 87.442913
iter  40 value 84.185543
iter  50 value 82.974821
iter  60 value 82.752079
iter  70 value 82.718945
iter  80 value 82.704284
iter  90 value 81.961624
iter 100 value 81.111808
final  value 81.111808 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.963860 
iter  10 value 92.441106
iter  20 value 84.929323
iter  30 value 84.771350
iter  40 value 83.693438
iter  50 value 83.291103
iter  60 value 83.126528
iter  70 value 82.854770
iter  80 value 81.167090
iter  90 value 80.042711
iter 100 value 79.749864
final  value 79.749864 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.866646 
iter  10 value 89.747962
iter  20 value 88.521029
iter  30 value 86.596226
iter  40 value 83.196975
iter  50 value 83.052518
iter  60 value 82.778736
iter  70 value 82.631603
iter  80 value 82.149397
iter  90 value 80.830096
iter 100 value 80.171751
final  value 80.171751 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.733354 
iter  10 value 93.939462
iter  20 value 88.510541
iter  30 value 85.914989
iter  40 value 83.770701
iter  50 value 81.314875
iter  60 value 81.015678
iter  70 value 80.732592
iter  80 value 80.365129
iter  90 value 80.258600
iter 100 value 80.184636
final  value 80.184636 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.990090 
iter  10 value 94.311983
iter  20 value 93.097810
iter  30 value 86.060617
iter  40 value 84.764994
iter  50 value 82.526750
iter  60 value 82.153793
iter  70 value 81.904843
iter  80 value 80.393502
iter  90 value 79.562775
iter 100 value 79.361151
final  value 79.361151 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.426953 
iter  10 value 94.561743
iter  20 value 84.416428
iter  30 value 81.953084
iter  40 value 81.658363
iter  50 value 80.958941
iter  60 value 80.308264
iter  70 value 79.923133
iter  80 value 79.524222
iter  90 value 79.104718
iter 100 value 79.025439
final  value 79.025439 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.403710 
iter  10 value 94.485883
iter  20 value 94.484276
final  value 94.484216 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.074289 
iter  10 value 93.775338
iter  20 value 93.775066
iter  30 value 92.923516
iter  40 value 90.703516
iter  50 value 85.974378
iter  60 value 85.672576
iter  70 value 84.983073
iter  80 value 84.887254
final  value 84.886846 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.328935 
iter  10 value 94.485925
final  value 94.484213 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.878225 
iter  10 value 93.559935
iter  20 value 92.624534
iter  30 value 83.878885
iter  40 value 83.875956
iter  50 value 83.875360
iter  60 value 83.868114
iter  70 value 83.657190
final  value 83.657117 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.547722 
final  value 94.485776 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.906814 
iter  10 value 91.956453
iter  20 value 91.512038
iter  30 value 91.215802
iter  40 value 91.190980
iter  50 value 87.437542
iter  60 value 84.638264
iter  70 value 83.941047
iter  80 value 83.320404
final  value 83.320038 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.573200 
iter  10 value 93.778655
iter  20 value 93.766807
iter  30 value 93.483982
iter  40 value 93.410025
final  value 93.409827 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.558974 
iter  10 value 94.488543
iter  20 value 93.430178
final  value 93.409764 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.666570 
iter  10 value 93.778842
iter  20 value 93.777993
iter  30 value 93.723119
iter  40 value 93.136404
iter  50 value 84.600654
iter  60 value 84.565667
iter  70 value 84.320861
iter  80 value 84.127649
iter  90 value 84.127456
iter 100 value 84.127369
final  value 84.127369 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.826262 
iter  10 value 93.778253
iter  20 value 93.777396
iter  30 value 93.278354
iter  40 value 86.218456
iter  50 value 85.307025
iter  60 value 84.145801
iter  70 value 83.928598
iter  80 value 83.851621
iter  90 value 83.826874
iter 100 value 83.814521
final  value 83.814521 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.985631 
iter  10 value 94.491143
iter  20 value 86.578070
iter  30 value 86.443901
iter  40 value 86.363221
iter  50 value 83.398280
iter  60 value 83.012546
iter  70 value 82.783930
final  value 82.783786 
converged
Fitting Repeat 2 

# weights:  507
initial  value 133.278207 
iter  10 value 94.491470
iter  20 value 94.421596
iter  30 value 89.012874
iter  40 value 82.817575
iter  50 value 80.246648
iter  60 value 80.206917
iter  70 value 80.048576
iter  80 value 80.045774
iter  90 value 80.043750
iter 100 value 80.040348
final  value 80.040348 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.889822 
iter  10 value 91.945536
iter  20 value 87.893225
iter  30 value 86.371717
iter  40 value 86.143278
iter  50 value 86.038803
iter  60 value 86.033363
iter  70 value 86.013389
iter  80 value 86.012955
final  value 86.012940 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.472802 
iter  10 value 93.822518
iter  20 value 93.801472
iter  30 value 93.570906
iter  40 value 93.570207
iter  50 value 93.409686
final  value 93.409483 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.826565 
iter  10 value 94.319866
iter  20 value 93.998224
iter  30 value 90.483245
iter  40 value 87.941874
iter  50 value 87.941404
iter  60 value 87.940259
final  value 87.940221 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.729595 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.856858 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.190577 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.712159 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.595701 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.756243 
iter  10 value 94.466842
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.929100 
iter  10 value 94.276328
final  value 94.276324 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.949993 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.468912 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.543455 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.850658 
iter  10 value 86.115828
iter  20 value 85.833499
final  value 85.833463 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.207608 
final  value 94.484137 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.470653 
iter  10 value 91.292511
iter  20 value 91.155632
iter  30 value 91.136879
iter  40 value 82.477200
iter  50 value 81.917538
iter  60 value 81.850422
iter  70 value 81.782132
iter  80 value 81.627681
iter  90 value 81.626335
final  value 81.626315 
converged
Fitting Repeat 4 

# weights:  507
initial  value 129.374080 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.380886 
iter  10 value 92.649884
iter  20 value 83.882669
iter  30 value 82.831246
iter  40 value 82.819517
final  value 82.819239 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.483680 
iter  10 value 94.438099
iter  20 value 88.889211
iter  30 value 85.563621
iter  40 value 84.105305
iter  50 value 83.904176
final  value 83.903828 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.637503 
iter  10 value 94.487397
iter  20 value 94.361580
iter  30 value 92.491760
iter  40 value 92.355668
iter  50 value 92.101101
iter  60 value 91.979427
iter  70 value 91.438693
iter  80 value 91.200780
iter  90 value 91.144719
iter  90 value 91.144719
iter  90 value 91.144719
final  value 91.144719 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.691114 
iter  10 value 92.175758
iter  20 value 85.084948
iter  30 value 83.808995
iter  40 value 83.422355
iter  50 value 83.175582
final  value 83.175513 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.067363 
iter  10 value 94.477935
iter  20 value 92.635395
iter  30 value 91.856937
iter  40 value 91.829765
iter  50 value 85.784578
iter  60 value 85.131222
iter  70 value 84.636364
iter  80 value 83.631274
iter  90 value 83.176189
final  value 83.175513 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.969338 
iter  10 value 92.598309
iter  20 value 89.801652
iter  30 value 89.350397
iter  40 value 88.152132
iter  50 value 86.970553
iter  60 value 86.337534
iter  70 value 83.559234
iter  80 value 83.499911
iter  90 value 83.484768
final  value 83.480867 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.245594 
iter  10 value 94.504290
iter  20 value 85.586127
iter  30 value 84.906750
iter  40 value 84.757790
iter  50 value 84.122697
iter  60 value 80.682672
iter  70 value 80.085101
iter  80 value 79.777745
iter  90 value 79.573323
iter 100 value 79.469136
final  value 79.469136 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.399850 
iter  10 value 94.383910
iter  20 value 87.578965
iter  30 value 85.693634
iter  40 value 83.686571
iter  50 value 83.352755
iter  60 value 82.368308
iter  70 value 80.168513
iter  80 value 79.692447
iter  90 value 79.307777
iter 100 value 79.195474
final  value 79.195474 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.250797 
iter  10 value 94.533453
iter  20 value 94.412532
iter  30 value 90.699872
iter  40 value 89.670285
iter  50 value 87.369987
iter  60 value 84.505316
iter  70 value 83.531726
iter  80 value 81.982791
iter  90 value 80.622098
iter 100 value 79.322220
final  value 79.322220 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.745733 
iter  10 value 94.449003
iter  20 value 89.810526
iter  30 value 87.990704
iter  40 value 86.843316
iter  50 value 84.189374
iter  60 value 82.136019
iter  70 value 81.484457
iter  80 value 80.569833
iter  90 value 80.074103
iter 100 value 79.653216
final  value 79.653216 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 132.523406 
iter  10 value 94.456140
iter  20 value 89.332412
iter  30 value 84.145146
iter  40 value 83.750928
iter  50 value 83.522002
iter  60 value 82.706844
iter  70 value 80.583757
iter  80 value 80.039810
iter  90 value 79.929014
iter 100 value 79.397470
final  value 79.397470 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.701817 
iter  10 value 99.567036
iter  20 value 94.797706
iter  30 value 94.443458
iter  40 value 91.812101
iter  50 value 82.400675
iter  60 value 80.623282
iter  70 value 79.912014
iter  80 value 79.193658
iter  90 value 79.046227
iter 100 value 78.834601
final  value 78.834601 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.293283 
iter  10 value 94.616550
iter  20 value 86.565034
iter  30 value 83.801752
iter  40 value 81.388043
iter  50 value 80.068202
iter  60 value 79.453760
iter  70 value 79.356407
iter  80 value 79.220915
iter  90 value 78.929995
iter 100 value 78.717641
final  value 78.717641 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.307358 
iter  10 value 97.053794
iter  20 value 86.594615
iter  30 value 83.462936
iter  40 value 83.296480
iter  50 value 82.319952
iter  60 value 80.548441
iter  70 value 80.113558
iter  80 value 79.954172
iter  90 value 79.346950
iter 100 value 78.839114
final  value 78.839114 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.153408 
iter  10 value 94.776693
iter  20 value 90.626719
iter  30 value 83.921631
iter  40 value 80.506810
iter  50 value 79.827703
iter  60 value 79.660077
iter  70 value 79.517946
iter  80 value 79.373246
iter  90 value 79.320621
iter 100 value 79.310415
final  value 79.310415 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.345065 
iter  10 value 94.886737
iter  20 value 94.783537
iter  30 value 94.067230
iter  40 value 91.361565
iter  50 value 84.648211
iter  60 value 84.070340
iter  70 value 83.690366
iter  80 value 83.442187
iter  90 value 82.797746
iter 100 value 81.270791
final  value 81.270791 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.509239 
final  value 94.485802 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.113268 
final  value 94.485822 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.931417 
final  value 94.485750 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.539926 
final  value 94.485908 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.207261 
iter  10 value 94.485745
iter  20 value 94.484227
iter  30 value 86.619359
iter  40 value 84.443935
iter  50 value 84.442536
iter  60 value 84.196829
final  value 84.164547 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.344929 
iter  10 value 94.480667
iter  20 value 94.471788
iter  30 value 94.468447
iter  40 value 94.434860
iter  50 value 93.148062
iter  60 value 82.635502
iter  70 value 82.122673
iter  80 value 82.115421
iter  90 value 82.022871
iter 100 value 82.016107
final  value 82.016107 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.081376 
iter  10 value 94.488894
iter  20 value 94.395945
iter  30 value 93.441819
iter  40 value 87.311699
iter  50 value 85.661430
iter  60 value 84.275252
iter  70 value 84.266909
iter  80 value 84.266266
iter  90 value 84.262971
iter 100 value 84.106428
final  value 84.106428 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.088647 
iter  10 value 93.957156
iter  20 value 93.951819
iter  30 value 93.675418
iter  40 value 93.282010
iter  50 value 92.614320
final  value 92.609266 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.844593 
iter  10 value 94.489429
iter  20 value 94.484066
iter  30 value 89.413119
iter  40 value 85.873676
iter  50 value 85.465962
iter  60 value 84.765865
iter  70 value 78.240768
iter  80 value 76.891211
iter  90 value 76.637524
iter 100 value 76.610410
final  value 76.610410 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.238083 
iter  10 value 94.054480
iter  20 value 93.702731
iter  30 value 93.698489
iter  40 value 93.695921
iter  50 value 93.692548
iter  60 value 93.469375
iter  70 value 83.486847
iter  80 value 83.348612
iter  90 value 83.338374
iter 100 value 83.338263
final  value 83.338263 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.995826 
iter  10 value 94.491797
iter  20 value 94.068812
iter  30 value 88.214738
iter  40 value 84.941278
iter  50 value 84.523883
iter  60 value 80.638513
iter  70 value 78.323630
iter  80 value 78.297482
iter  90 value 78.288573
iter 100 value 78.251656
final  value 78.251656 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.984736 
iter  10 value 94.932512
iter  20 value 91.349697
iter  30 value 85.568946
iter  40 value 85.386750
iter  50 value 85.382256
iter  60 value 84.966339
iter  70 value 84.962852
iter  80 value 81.408540
iter  90 value 80.790392
iter 100 value 79.990932
final  value 79.990932 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.740250 
iter  10 value 94.469542
iter  20 value 86.462624
iter  30 value 86.081190
iter  40 value 84.395568
iter  50 value 84.392782
iter  60 value 84.391012
iter  70 value 84.349106
iter  80 value 84.345005
iter  90 value 84.344428
iter 100 value 84.342586
final  value 84.342586 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.212033 
iter  10 value 94.297543
iter  20 value 93.710057
iter  30 value 93.705909
iter  40 value 93.699417
iter  50 value 86.579324
iter  60 value 82.938268
iter  70 value 81.728841
iter  80 value 81.493288
iter  90 value 81.489559
iter 100 value 81.489021
final  value 81.489021 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.195218 
iter  10 value 94.147691
iter  20 value 94.143797
iter  30 value 93.702993
iter  40 value 92.763030
iter  50 value 91.275314
iter  60 value 90.791798
iter  70 value 90.718472
iter  80 value 90.718340
final  value 90.718328 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.170221 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.885707 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.634500 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.242829 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.901992 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.295111 
iter  10 value 94.032967
iter  10 value 94.032967
iter  10 value 94.032967
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.658094 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.115421 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.281140 
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.391558 
final  value 93.324529 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.603560 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.900357 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 127.415358 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.383034 
iter  10 value 94.034739
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.003643 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.035716 
iter  10 value 94.015899
iter  20 value 84.446846
iter  30 value 83.094476
iter  40 value 81.493128
iter  50 value 81.165463
iter  60 value 81.086396
iter  70 value 81.081218
final  value 81.081217 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.906890 
iter  10 value 94.054977
iter  20 value 93.887952
iter  30 value 84.541034
iter  40 value 81.556867
iter  50 value 81.182860
iter  60 value 81.137514
iter  70 value 81.088746
final  value 81.081216 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.539376 
iter  10 value 93.745669
iter  20 value 83.434133
iter  30 value 82.874939
iter  40 value 82.663925
iter  50 value 81.375615
iter  60 value 81.085597
iter  70 value 81.081220
final  value 81.081217 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.287238 
iter  10 value 93.920476
iter  20 value 92.371158
iter  30 value 92.125395
iter  40 value 87.761951
iter  50 value 84.231143
iter  60 value 81.724355
iter  70 value 81.319302
iter  80 value 80.829687
iter  90 value 80.219205
iter 100 value 80.164868
final  value 80.164868 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.520223 
iter  10 value 93.851065
iter  20 value 83.215138
iter  30 value 81.911334
iter  40 value 81.689931
iter  50 value 80.763671
iter  60 value 80.486696
iter  70 value 80.218889
iter  80 value 80.159385
iter  80 value 80.159385
iter  80 value 80.159385
final  value 80.159385 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.041033 
iter  10 value 94.115828
iter  20 value 83.138712
iter  30 value 82.576705
iter  40 value 82.361971
iter  50 value 81.934107
iter  60 value 80.711462
iter  70 value 78.403341
iter  80 value 77.942449
iter  90 value 77.768909
iter 100 value 77.607918
final  value 77.607918 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.829190 
iter  10 value 94.048285
iter  20 value 87.833079
iter  30 value 82.858204
iter  40 value 81.900013
iter  50 value 81.323556
iter  60 value 80.713348
iter  70 value 80.329880
iter  80 value 78.653337
iter  90 value 78.083607
iter 100 value 77.910275
final  value 77.910275 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.064681 
iter  10 value 94.159978
iter  20 value 93.790885
iter  30 value 90.490177
iter  40 value 89.799161
iter  50 value 89.155632
iter  60 value 88.921995
iter  70 value 85.472787
iter  80 value 84.526709
iter  90 value 82.071409
iter 100 value 79.848831
final  value 79.848831 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.632981 
iter  10 value 94.689939
iter  20 value 93.160605
iter  30 value 86.495566
iter  40 value 85.405562
iter  50 value 82.715470
iter  60 value 79.416071
iter  70 value 78.577068
iter  80 value 78.484638
iter  90 value 78.313972
iter 100 value 78.281503
final  value 78.281503 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 126.290940 
iter  10 value 93.996038
iter  20 value 88.741715
iter  30 value 83.183165
iter  40 value 82.494210
iter  50 value 82.332195
iter  60 value 81.207236
iter  70 value 80.300897
iter  80 value 80.256372
iter  90 value 80.211520
iter 100 value 80.106396
final  value 80.106396 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.084173 
iter  10 value 96.734390
iter  20 value 89.514294
iter  30 value 86.357903
iter  40 value 85.028262
iter  50 value 82.188469
iter  60 value 81.845238
iter  70 value 80.785457
iter  80 value 80.055254
iter  90 value 79.950799
iter 100 value 79.085224
final  value 79.085224 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.739822 
iter  10 value 94.039308
iter  20 value 89.702689
iter  30 value 85.421468
iter  40 value 83.840265
iter  50 value 80.948080
iter  60 value 79.958790
iter  70 value 79.436323
iter  80 value 79.188977
iter  90 value 79.039138
iter 100 value 78.973311
final  value 78.973311 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.765527 
iter  10 value 94.171692
iter  20 value 91.952738
iter  30 value 89.998135
iter  40 value 89.158663
iter  50 value 87.456964
iter  60 value 83.057896
iter  70 value 81.184062
iter  80 value 79.328706
iter  90 value 78.681447
iter 100 value 78.386917
final  value 78.386917 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.232113 
iter  10 value 93.659010
iter  20 value 91.815808
iter  30 value 90.486416
iter  40 value 86.730693
iter  50 value 80.954432
iter  60 value 79.495881
iter  70 value 79.203287
iter  80 value 78.756640
iter  90 value 78.561874
iter 100 value 78.463902
final  value 78.463902 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.512057 
iter  10 value 93.757582
iter  20 value 89.639895
iter  30 value 83.553088
iter  40 value 80.599477
iter  50 value 79.436384
iter  60 value 78.991401
iter  70 value 78.447263
iter  80 value 78.169699
iter  90 value 77.856227
iter 100 value 77.737488
final  value 77.737488 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.409591 
iter  10 value 81.153562
iter  20 value 81.143101
iter  30 value 81.022284
iter  40 value 80.845248
final  value 80.845245 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.804757 
final  value 94.054611 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.406908 
final  value 94.034649 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.536384 
final  value 94.054445 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.413954 
final  value 94.054534 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.448087 
iter  10 value 94.038159
iter  20 value 93.905112
iter  30 value 89.594239
iter  40 value 88.454256
iter  50 value 84.626900
iter  60 value 84.520895
iter  70 value 81.293251
iter  80 value 81.003585
iter  90 value 80.881708
final  value 80.860643 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.063882 
iter  10 value 90.039184
iter  20 value 89.550111
iter  30 value 89.449738
iter  40 value 89.388975
iter  50 value 89.362173
iter  60 value 78.786009
iter  70 value 78.145027
iter  80 value 78.035542
iter  90 value 77.694810
iter 100 value 77.536987
final  value 77.536987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.489002 
iter  10 value 91.932239
iter  20 value 91.376494
iter  30 value 91.375857
iter  40 value 91.371569
iter  50 value 91.371237
iter  60 value 91.187541
iter  70 value 89.200928
iter  80 value 83.027308
iter  90 value 80.295290
iter 100 value 78.606908
final  value 78.606908 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.295090 
iter  10 value 93.329711
iter  20 value 89.806792
iter  30 value 87.861942
iter  40 value 87.250995
iter  50 value 87.211824
final  value 87.211689 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.711487 
iter  10 value 87.572140
iter  20 value 80.445505
iter  30 value 79.908294
iter  40 value 79.837441
iter  50 value 79.509996
final  value 79.462546 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.628654 
final  value 94.040343 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.922577 
iter  10 value 94.041650
iter  20 value 94.021433
iter  30 value 90.991222
iter  40 value 90.827097
iter  50 value 84.728562
iter  60 value 83.871954
iter  70 value 83.870151
iter  80 value 83.862258
iter  90 value 81.544227
iter 100 value 81.494008
final  value 81.494008 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.617978 
iter  10 value 91.528923
iter  20 value 84.739331
iter  30 value 83.292492
iter  40 value 83.010354
iter  50 value 83.003292
iter  60 value 83.002363
iter  70 value 81.226282
iter  80 value 80.809021
iter  90 value 80.805619
final  value 80.805103 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.599417 
iter  10 value 94.101292
iter  20 value 89.667890
iter  30 value 81.213983
iter  40 value 81.143699
iter  50 value 81.135395
iter  60 value 80.855175
iter  70 value 80.847322
iter  80 value 80.843953
iter  90 value 80.748756
iter 100 value 80.547497
final  value 80.547497 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.186124 
iter  10 value 94.049457
iter  20 value 94.039293
final  value 94.037792 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.001863 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.088111 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.731603 
iter  10 value 94.473697
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.504935 
final  value 94.354286 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.840302 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.175620 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.313560 
iter  10 value 94.415779
iter  20 value 94.354286
iter  20 value 94.354286
iter  20 value 94.354286
final  value 94.354286 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.814180 
iter  10 value 93.225667
iter  20 value 93.221414
final  value 93.221353 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.907852 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.772337 
final  value 92.376405 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.581519 
iter  10 value 93.951740
final  value 93.866667 
converged
Fitting Repeat 2 

# weights:  507
initial  value 128.156617 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.269952 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.307130 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.989686 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.045875 
iter  10 value 94.486434
iter  20 value 93.963590
iter  30 value 93.857877
iter  40 value 93.838712
iter  50 value 91.206584
iter  60 value 85.926624
iter  70 value 84.093532
iter  80 value 82.728739
iter  90 value 82.477133
iter 100 value 82.197135
final  value 82.197135 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.343338 
iter  10 value 94.491309
iter  20 value 94.478772
iter  30 value 94.070320
iter  40 value 93.947886
iter  50 value 93.871096
iter  60 value 93.851842
iter  70 value 93.849719
iter  80 value 93.848157
iter  90 value 93.842459
iter 100 value 92.453828
final  value 92.453828 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.583005 
iter  10 value 94.484298
iter  20 value 94.340169
iter  30 value 94.228191
iter  40 value 92.415612
iter  50 value 88.710483
iter  60 value 87.789732
iter  70 value 85.954854
iter  80 value 85.609302
iter  90 value 85.506269
final  value 85.505314 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.852743 
iter  10 value 94.486453
iter  20 value 93.992091
iter  30 value 93.843971
iter  40 value 91.878565
iter  50 value 89.342079
iter  60 value 88.298323
iter  70 value 87.613119
iter  80 value 83.085978
iter  90 value 82.561477
iter 100 value 82.301937
final  value 82.301937 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.994807 
iter  10 value 94.513189
iter  20 value 94.470917
iter  30 value 87.143081
iter  40 value 86.826688
iter  50 value 86.812703
iter  60 value 86.234451
iter  70 value 85.943662
final  value 85.941498 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.740278 
iter  10 value 94.028857
iter  20 value 83.719033
iter  30 value 82.744977
iter  40 value 82.523718
iter  50 value 82.104054
iter  60 value 81.529215
iter  70 value 81.298304
iter  80 value 81.078029
iter  90 value 81.005931
iter 100 value 80.871029
final  value 80.871029 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.704391 
iter  10 value 95.537683
iter  20 value 94.132540
iter  30 value 93.823900
iter  40 value 88.873324
iter  50 value 88.742362
iter  60 value 86.844168
iter  70 value 85.625338
iter  80 value 84.216543
iter  90 value 83.366217
iter 100 value 82.698742
final  value 82.698742 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.788617 
iter  10 value 94.495651
iter  20 value 94.477777
iter  30 value 93.456176
iter  40 value 91.181427
iter  50 value 85.585917
iter  60 value 83.958822
iter  70 value 82.384834
iter  80 value 82.045464
iter  90 value 81.604273
iter 100 value 81.318415
final  value 81.318415 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.822921 
iter  10 value 94.433631
iter  20 value 93.987671
iter  30 value 91.823302
iter  40 value 88.419473
iter  50 value 88.292768
iter  60 value 87.684151
iter  70 value 87.142777
iter  80 value 84.454759
iter  90 value 83.506335
iter 100 value 81.635781
final  value 81.635781 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.074969 
iter  10 value 94.713505
iter  20 value 89.592650
iter  30 value 88.133953
iter  40 value 87.874910
iter  50 value 87.724965
iter  60 value 85.589914
iter  70 value 85.350795
iter  80 value 84.917035
iter  90 value 83.721603
iter 100 value 81.959941
final  value 81.959941 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 140.037709 
iter  10 value 94.711711
iter  20 value 93.876069
iter  30 value 88.259700
iter  40 value 86.855043
iter  50 value 85.814514
iter  60 value 84.476472
iter  70 value 83.963473
iter  80 value 83.559761
iter  90 value 82.153356
iter 100 value 81.765779
final  value 81.765779 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.388641 
iter  10 value 94.311991
iter  20 value 90.179596
iter  30 value 85.038679
iter  40 value 84.172901
iter  50 value 82.593642
iter  60 value 81.590060
iter  70 value 81.350036
iter  80 value 81.094641
iter  90 value 80.984867
iter 100 value 80.963816
final  value 80.963816 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.474718 
iter  10 value 94.346662
iter  20 value 88.822672
iter  30 value 85.780495
iter  40 value 85.247733
iter  50 value 83.049135
iter  60 value 81.734419
iter  70 value 81.393639
iter  80 value 81.196504
iter  90 value 81.127525
iter 100 value 80.993917
final  value 80.993917 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.638111 
iter  10 value 93.859495
iter  20 value 92.162887
iter  30 value 82.972593
iter  40 value 82.356696
iter  50 value 81.912445
iter  60 value 81.262721
iter  70 value 80.827140
iter  80 value 80.770492
iter  90 value 80.717057
iter 100 value 80.688521
final  value 80.688521 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.056517 
iter  10 value 93.964831
iter  20 value 86.834173
iter  30 value 85.946874
iter  40 value 83.838004
iter  50 value 81.927793
iter  60 value 81.586098
iter  70 value 81.503332
iter  80 value 81.437165
iter  90 value 81.153146
iter 100 value 81.092045
final  value 81.092045 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.529467 
iter  10 value 94.485960
iter  20 value 94.479759
iter  30 value 93.763563
final  value 93.742199 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.321552 
iter  10 value 94.398919
iter  20 value 94.382953
iter  30 value 94.381975
iter  40 value 93.982421
iter  50 value 93.912933
final  value 93.912925 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.605898 
final  value 94.485735 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.914677 
final  value 94.485742 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.699703 
final  value 94.485881 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.087182 
iter  10 value 93.927640
iter  20 value 93.772473
iter  30 value 93.671099
iter  40 value 87.963765
iter  50 value 82.325748
iter  60 value 82.321262
iter  70 value 82.151132
iter  80 value 82.135387
iter  90 value 82.039603
iter 100 value 82.030869
final  value 82.030869 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.228452 
iter  10 value 94.466216
iter  20 value 92.988079
iter  30 value 86.273768
iter  40 value 86.231517
iter  50 value 86.231246
final  value 86.231229 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.868699 
iter  10 value 94.493701
iter  20 value 94.368795
iter  30 value 94.031648
iter  40 value 94.029332
iter  50 value 94.027423
final  value 94.026676 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.669606 
iter  10 value 94.485340
final  value 94.484239 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.244253 
iter  10 value 94.359368
iter  20 value 94.341251
iter  30 value 92.032240
iter  40 value 92.031069
iter  40 value 92.031068
iter  40 value 92.031068
final  value 92.031068 
converged
Fitting Repeat 1 

# weights:  507
initial  value 130.811604 
iter  10 value 94.491455
iter  20 value 94.420371
iter  30 value 85.157808
iter  40 value 84.392486
iter  50 value 82.421291
iter  60 value 81.427955
iter  70 value 80.984057
iter  80 value 80.883669
iter  90 value 79.965233
iter 100 value 79.300893
final  value 79.300893 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.477253 
iter  10 value 94.492034
iter  20 value 94.484633
iter  30 value 87.910315
iter  40 value 86.307510
iter  50 value 84.934501
iter  60 value 84.801415
final  value 84.800730 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.329192 
iter  10 value 94.023043
iter  20 value 93.980593
iter  30 value 93.873432
iter  40 value 93.867497
iter  50 value 88.416255
iter  60 value 84.227826
iter  70 value 83.649972
iter  80 value 83.582478
iter  90 value 83.580539
iter 100 value 81.251345
final  value 81.251345 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.759857 
iter  10 value 86.404572
iter  20 value 85.987680
iter  30 value 85.984806
iter  40 value 85.981604
final  value 85.981464 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.501491 
iter  10 value 94.034897
iter  20 value 94.026814
iter  30 value 88.083809
iter  40 value 87.813959
iter  50 value 87.457852
iter  60 value 83.477040
iter  70 value 81.442543
iter  80 value 81.361503
iter  90 value 81.327355
iter 100 value 81.326391
final  value 81.326391 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 129.451955 
iter  10 value 114.749724
iter  20 value 109.431476
iter  30 value 109.116355
iter  40 value 107.969375
iter  50 value 103.586951
iter  60 value 103.120222
iter  70 value 102.829263
iter  80 value 102.626046
iter  90 value 102.379471
iter 100 value 102.056672
final  value 102.056672 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 131.708823 
iter  10 value 114.087994
iter  20 value 107.365952
iter  30 value 107.179205
iter  40 value 104.037185
iter  50 value 102.739228
iter  60 value 102.077223
iter  70 value 101.718338
iter  80 value 101.652923
iter  90 value 101.193457
iter 100 value 101.086033
final  value 101.086033 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 129.752972 
iter  10 value 117.068634
iter  20 value 108.543708
iter  30 value 108.137384
iter  40 value 107.888762
iter  50 value 106.782883
iter  60 value 104.357626
iter  70 value 102.459670
iter  80 value 101.911918
iter  90 value 101.073426
iter 100 value 100.655676
final  value 100.655676 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 132.580597 
iter  10 value 118.017322
iter  20 value 108.478162
iter  30 value 107.332826
iter  40 value 107.007741
iter  50 value 105.692977
iter  60 value 104.025496
iter  70 value 101.831824
iter  80 value 101.358851
iter  90 value 101.175171
iter 100 value 101.045998
final  value 101.045998 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 130.850400 
iter  10 value 117.924087
iter  20 value 110.098816
iter  30 value 107.359895
iter  40 value 107.230861
iter  50 value 105.603981
iter  60 value 104.877645
iter  70 value 104.756494
iter  80 value 104.749523
iter  90 value 104.715913
iter 100 value 103.128175
final  value 103.128175 
stopped after 100 iterations
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 -- Sat Dec 20 00:12:40 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 
 40.766   1.162  92.700