##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.6.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: x86_64-apple-darwin20 (64-bit)
* R was compiled by
    Apple clang version 14.0.3 (clang-1403.0.22.14.1)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.6.4
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.6.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
FSmethod      50.830  1.738  68.541
corr_plot     50.637  1.589  68.614
var_imp       50.269  1.653  69.862
pred_ensembel 23.644  0.468  25.050
calculateTC    4.687  0.473   6.602
enrichfindP    0.867  0.081  14.493
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 104.595654 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.461644 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.036434 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.426271 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.078408 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.983686 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.713350 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.237998 
iter  10 value 86.778671
iter  20 value 85.559330
iter  30 value 85.318967
iter  40 value 85.310408
iter  50 value 85.310352
final  value 85.310349 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.119902 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.418677 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 132.429085 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.329838 
iter  10 value 88.626012
iter  20 value 86.717754
iter  30 value 86.708097
iter  40 value 86.707724
final  value 86.707692 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.879915 
iter  10 value 93.431365
iter  20 value 91.613939
iter  30 value 91.566985
final  value 91.566666 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.504926 
final  value 94.443244 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.699749 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 112.817256 
iter  10 value 94.429577
iter  20 value 88.785844
iter  30 value 84.716722
iter  40 value 84.326499
iter  50 value 83.889249
iter  60 value 83.736720
iter  70 value 83.684012
iter  80 value 83.667386
iter  90 value 83.664537
final  value 83.663969 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.206471 
iter  10 value 93.397541
iter  20 value 87.340733
iter  30 value 86.703972
iter  40 value 83.456138
iter  50 value 82.675999
iter  60 value 82.418324
iter  70 value 82.388606
final  value 82.388430 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.528308 
iter  10 value 94.441542
iter  20 value 90.222232
iter  30 value 87.082104
iter  40 value 86.806506
iter  50 value 86.546686
iter  60 value 85.439266
iter  70 value 84.658179
iter  80 value 84.639089
final  value 84.637891 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.100095 
iter  10 value 94.101203
iter  20 value 87.220047
iter  30 value 84.824218
iter  40 value 84.142255
iter  50 value 84.123719
iter  60 value 83.964024
iter  70 value 83.807143
iter  80 value 83.701718
iter  90 value 83.663348
iter 100 value 83.656333
final  value 83.656333 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.139961 
iter  10 value 92.481586
iter  20 value 88.586029
iter  30 value 87.605451
iter  40 value 86.673783
iter  50 value 85.275273
iter  60 value 84.655518
iter  70 value 84.558421
final  value 84.558364 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.096712 
iter  10 value 94.631399
iter  20 value 92.611650
iter  30 value 86.322716
iter  40 value 85.415014
iter  50 value 85.039573
iter  60 value 83.254689
iter  70 value 82.508654
iter  80 value 82.315739
iter  90 value 82.105833
iter 100 value 82.039699
final  value 82.039699 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.375052 
iter  10 value 94.163943
iter  20 value 90.000401
iter  30 value 87.989455
iter  40 value 85.134888
iter  50 value 83.876805
iter  60 value 83.666768
iter  70 value 83.347833
iter  80 value 82.495070
iter  90 value 81.889054
iter 100 value 81.377816
final  value 81.377816 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.906305 
iter  10 value 94.351176
iter  20 value 88.706838
iter  30 value 85.412818
iter  40 value 84.975169
iter  50 value 84.421342
iter  60 value 83.205613
iter  70 value 82.426106
iter  80 value 82.221371
iter  90 value 81.549200
iter 100 value 81.267152
final  value 81.267152 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.399765 
iter  10 value 91.921087
iter  20 value 88.388687
iter  30 value 86.790717
iter  40 value 86.686425
iter  50 value 85.865726
iter  60 value 85.088812
iter  70 value 84.636570
iter  80 value 82.294424
iter  90 value 81.507902
iter 100 value 81.120384
final  value 81.120384 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.185992 
iter  10 value 94.487257
iter  20 value 93.157584
iter  30 value 90.438395
iter  40 value 87.486647
iter  50 value 86.669574
iter  60 value 85.839833
iter  70 value 84.616016
iter  80 value 82.752504
iter  90 value 82.515846
iter 100 value 82.418140
final  value 82.418140 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.041458 
iter  10 value 94.783841
iter  20 value 94.530969
iter  30 value 88.998715
iter  40 value 86.448836
iter  50 value 83.490313
iter  60 value 82.722337
iter  70 value 81.701396
iter  80 value 81.344368
iter  90 value 81.232580
iter 100 value 81.186746
final  value 81.186746 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 141.105114 
iter  10 value 95.805837
iter  20 value 90.222237
iter  30 value 87.675312
iter  40 value 85.067012
iter  50 value 83.035915
iter  60 value 82.589162
iter  70 value 82.352381
iter  80 value 82.191930
iter  90 value 82.082976
iter 100 value 81.567253
final  value 81.567253 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 129.101287 
iter  10 value 96.515706
iter  20 value 88.112248
iter  30 value 87.134812
iter  40 value 85.395482
iter  50 value 84.929424
iter  60 value 82.539328
iter  70 value 82.240138
iter  80 value 82.183499
iter  90 value 82.157759
iter 100 value 81.879143
final  value 81.879143 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.714023 
iter  10 value 95.272581
iter  20 value 88.445081
iter  30 value 87.052393
iter  40 value 82.678422
iter  50 value 82.114311
iter  60 value 81.825328
iter  70 value 81.606837
iter  80 value 81.515156
iter  90 value 81.370499
iter 100 value 81.177702
final  value 81.177702 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 134.878058 
iter  10 value 94.700383
iter  20 value 91.397022
iter  30 value 89.985839
iter  40 value 87.967038
iter  50 value 87.060487
iter  60 value 86.791185
iter  70 value 86.319885
iter  80 value 84.685168
iter  90 value 84.270063
iter 100 value 84.111219
final  value 84.111219 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.384152 
final  value 94.485833 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.742136 
final  value 94.485991 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.235818 
final  value 94.485771 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.724845 
iter  10 value 94.485628
iter  20 value 94.484248
final  value 94.484217 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.157446 
final  value 94.485772 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.202667 
iter  10 value 94.457945
iter  20 value 94.428448
final  value 94.400728 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.957942 
iter  10 value 94.488984
iter  20 value 94.450568
iter  30 value 88.895214
iter  40 value 88.395681
iter  50 value 88.362131
iter  60 value 87.420069
iter  70 value 86.687650
iter  80 value 86.666561
iter  90 value 86.655540
iter 100 value 86.485290
final  value 86.485290 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.256547 
iter  10 value 94.486098
iter  20 value 94.314554
iter  30 value 87.652412
final  value 87.652019 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.706456 
iter  10 value 94.487366
iter  20 value 93.570242
iter  30 value 86.994202
iter  40 value 83.215415
iter  50 value 82.997954
iter  60 value 82.989945
final  value 82.989217 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.979309 
iter  10 value 94.489121
iter  20 value 94.351326
iter  30 value 92.872283
iter  40 value 92.872147
iter  50 value 91.854780
iter  60 value 91.317981
iter  70 value 91.260148
iter  80 value 91.259061
final  value 91.259037 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.928719 
iter  10 value 94.491837
iter  20 value 94.470453
iter  30 value 92.400877
iter  40 value 87.183420
iter  50 value 87.180803
final  value 87.180776 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.071915 
iter  10 value 94.491699
iter  20 value 90.012073
iter  30 value 85.833930
iter  40 value 85.825686
iter  50 value 85.724097
iter  60 value 85.601001
final  value 85.600980 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.383585 
iter  10 value 94.451895
iter  20 value 94.443416
iter  30 value 94.377377
iter  40 value 90.859748
iter  50 value 86.497141
iter  60 value 85.880487
iter  70 value 85.877816
iter  80 value 85.875964
iter  90 value 85.875508
iter 100 value 83.575018
final  value 83.575018 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.394319 
iter  10 value 94.492000
final  value 94.491139 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.099321 
iter  10 value 94.451092
iter  20 value 94.447116
iter  20 value 94.447116
iter  20 value 94.447116
final  value 94.447116 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.758145 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.207245 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.407316 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.681330 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.430443 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.241156 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.890368 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.274431 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.083902 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 123.444820 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.161835 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.872388 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.121679 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.669534 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.970936 
iter  10 value 93.553443
iter  20 value 93.322977
iter  30 value 92.969949
final  value 92.969862 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.240245 
iter  10 value 94.037275
iter  20 value 93.128115
iter  30 value 93.114821
iter  40 value 93.083859
iter  50 value 92.957055
iter  60 value 89.395841
iter  70 value 86.540688
iter  80 value 86.467125
iter  90 value 86.348734
iter 100 value 85.060811
final  value 85.060811 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.031861 
iter  10 value 94.044969
iter  20 value 93.631035
iter  30 value 93.510496
iter  40 value 93.461645
iter  50 value 92.510585
iter  60 value 85.427620
iter  70 value 85.148698
iter  80 value 84.966739
iter  90 value 84.911856
iter 100 value 84.901792
final  value 84.901792 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.210810 
iter  10 value 94.058872
iter  20 value 94.055355
iter  30 value 93.305243
iter  40 value 93.121548
iter  50 value 93.072828
final  value 93.067792 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.883993 
iter  10 value 94.065123
iter  20 value 93.520306
iter  30 value 93.234494
iter  40 value 92.680313
iter  50 value 87.064958
iter  60 value 86.459061
iter  70 value 86.449909
iter  80 value 86.326234
iter  90 value 85.716512
iter 100 value 85.221761
final  value 85.221761 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.064747 
iter  10 value 94.053214
iter  20 value 93.516200
iter  30 value 86.805346
iter  40 value 86.314415
iter  50 value 83.705033
iter  60 value 83.354936
iter  70 value 83.235337
iter  80 value 82.763038
iter  90 value 82.484221
iter 100 value 82.436868
final  value 82.436868 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.249311 
iter  10 value 94.017820
iter  20 value 93.727675
iter  30 value 93.043545
iter  40 value 87.624088
iter  50 value 86.674079
iter  60 value 86.144082
iter  70 value 83.701939
iter  80 value 82.701227
iter  90 value 82.061799
iter 100 value 81.708507
final  value 81.708507 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 128.466006 
iter  10 value 94.577748
iter  20 value 93.768829
iter  30 value 85.160586
iter  40 value 83.826491
iter  50 value 83.417665
iter  60 value 82.924472
iter  70 value 82.661497
iter  80 value 82.495849
iter  90 value 82.177147
iter 100 value 81.776472
final  value 81.776472 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.898552 
iter  10 value 93.869131
iter  20 value 91.874671
iter  30 value 85.990605
iter  40 value 84.783122
iter  50 value 83.814625
iter  60 value 83.155097
iter  70 value 82.424822
iter  80 value 82.058374
iter  90 value 82.038705
iter 100 value 82.020549
final  value 82.020549 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.857206 
iter  10 value 94.152556
iter  20 value 94.056549
iter  30 value 93.981578
iter  40 value 89.583687
iter  50 value 84.671504
iter  60 value 83.884434
iter  70 value 83.426437
iter  80 value 82.695363
iter  90 value 81.999160
iter 100 value 81.751190
final  value 81.751190 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.507352 
iter  10 value 94.112401
iter  20 value 93.178645
iter  30 value 86.412829
iter  40 value 85.130907
iter  50 value 84.787267
iter  60 value 84.371578
iter  70 value 83.112679
iter  80 value 82.725478
iter  90 value 82.072748
iter 100 value 81.523677
final  value 81.523677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.339070 
iter  10 value 94.848653
iter  20 value 91.470566
iter  30 value 86.082004
iter  40 value 85.227044
iter  50 value 85.051583
iter  60 value 84.709864
iter  70 value 83.219082
iter  80 value 81.568620
iter  90 value 80.922430
iter 100 value 80.641638
final  value 80.641638 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.118646 
iter  10 value 93.742217
iter  20 value 91.926362
iter  30 value 87.606424
iter  40 value 85.835404
iter  50 value 84.830244
iter  60 value 82.797456
iter  70 value 82.014230
iter  80 value 81.891966
iter  90 value 81.643706
iter 100 value 81.590648
final  value 81.590648 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.387811 
iter  10 value 94.853273
iter  20 value 94.048922
iter  30 value 92.640204
iter  40 value 85.824384
iter  50 value 85.483619
iter  60 value 85.263753
iter  70 value 85.180969
iter  80 value 85.014738
iter  90 value 83.642830
iter 100 value 82.527795
final  value 82.527795 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.162840 
iter  10 value 94.006495
iter  20 value 90.830975
iter  30 value 87.037503
iter  40 value 85.710727
iter  50 value 84.337998
iter  60 value 82.727732
iter  70 value 82.223151
iter  80 value 81.913209
iter  90 value 81.575859
iter 100 value 81.341847
final  value 81.341847 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.488913 
iter  10 value 92.987040
iter  20 value 86.210068
iter  30 value 85.673095
iter  40 value 85.061714
iter  50 value 84.268698
iter  60 value 83.350859
iter  70 value 81.732383
iter  80 value 81.230002
iter  90 value 80.964953
iter 100 value 80.781915
final  value 80.781915 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.507225 
final  value 94.054434 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.990907 
final  value 94.054709 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.737848 
iter  10 value 94.054614
iter  20 value 94.052928
final  value 94.052912 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.148359 
final  value 94.056259 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.937323 
iter  10 value 94.054607
iter  20 value 94.025293
final  value 93.583041 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.936891 
iter  10 value 94.056849
iter  20 value 93.479349
iter  30 value 93.125719
iter  40 value 93.124343
iter  50 value 93.123118
iter  60 value 93.122992
iter  70 value 93.122802
iter  70 value 93.122802
iter  70 value 93.122801
final  value 93.122801 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.642256 
iter  10 value 93.123536
iter  20 value 93.106045
iter  30 value 93.047027
iter  40 value 88.495524
iter  50 value 88.213498
final  value 88.201841 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.972290 
iter  10 value 93.376904
iter  20 value 93.375725
iter  30 value 93.375036
iter  40 value 93.374797
final  value 93.374593 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.537193 
iter  10 value 92.169270
iter  20 value 92.081952
iter  30 value 92.040329
iter  40 value 91.900380
final  value 91.900352 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.932599 
iter  10 value 93.587963
iter  20 value 93.063186
iter  30 value 92.954664
iter  40 value 85.160036
iter  50 value 84.433682
iter  60 value 84.428219
final  value 84.427634 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.827444 
iter  10 value 93.590960
iter  20 value 93.041771
iter  30 value 90.295726
iter  40 value 86.291792
iter  50 value 86.120513
iter  60 value 85.214847
iter  70 value 85.175152
iter  80 value 84.851688
iter  90 value 83.888542
iter 100 value 83.828235
final  value 83.828235 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.494206 
iter  10 value 94.061208
iter  20 value 93.955019
iter  30 value 89.531352
iter  40 value 89.373581
iter  50 value 86.799374
iter  60 value 84.475037
iter  70 value 84.420311
iter  80 value 84.417621
iter  90 value 84.417471
iter 100 value 84.407263
final  value 84.407263 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.269690 
iter  10 value 94.059621
iter  20 value 93.667959
iter  30 value 85.979303
iter  40 value 85.978134
iter  50 value 85.393453
iter  60 value 84.610512
final  value 84.610186 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.242125 
iter  10 value 93.021522
iter  20 value 92.945182
iter  30 value 92.878943
iter  40 value 92.873690
iter  50 value 92.873310
iter  60 value 92.873166
iter  70 value 92.873115
final  value 92.873076 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.814173 
iter  10 value 94.060723
iter  20 value 94.041595
iter  30 value 85.216239
iter  40 value 83.437215
iter  50 value 82.843137
final  value 82.813967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.941251 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.752835 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.699085 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.931959 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.501938 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.708692 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.658185 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.771007 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.646550 
final  value 92.786232 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.226889 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.845839 
final  value 94.467392 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.379341 
final  value 94.428840 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.492044 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.016249 
iter  10 value 93.955965
iter  20 value 93.936869
iter  30 value 93.422007
final  value 93.413497 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.704732 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 114.886027 
iter  10 value 94.486564
iter  20 value 94.482832
iter  30 value 91.018926
iter  40 value 86.928693
iter  50 value 86.258682
iter  60 value 84.093099
iter  70 value 82.975787
iter  80 value 81.693241
iter  90 value 80.976804
iter 100 value 80.949654
final  value 80.949654 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.498274 
iter  10 value 93.937875
iter  20 value 87.417869
iter  30 value 85.257450
iter  40 value 85.013581
iter  50 value 84.833600
iter  60 value 84.542809
iter  70 value 81.705211
iter  80 value 81.008301
iter  90 value 80.960306
iter 100 value 80.959357
final  value 80.959357 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.494035 
iter  10 value 93.985221
iter  20 value 93.392472
iter  30 value 92.003637
iter  40 value 88.884140
iter  50 value 82.656084
iter  60 value 82.253875
iter  70 value 81.258964
iter  80 value 81.221235
iter  80 value 81.221234
final  value 81.221234 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.304202 
iter  10 value 94.487410
iter  20 value 84.513796
iter  30 value 82.756699
iter  40 value 81.276871
iter  50 value 81.131397
iter  60 value 81.084682
iter  70 value 80.786412
final  value 80.784735 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.549559 
iter  10 value 94.484701
iter  20 value 88.399699
iter  30 value 84.313312
iter  40 value 81.906990
iter  50 value 81.299212
iter  60 value 81.200426
final  value 81.200239 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.876176 
iter  10 value 94.648470
iter  20 value 85.905112
iter  30 value 83.121598
iter  40 value 80.239253
iter  50 value 77.813466
iter  60 value 77.543630
iter  70 value 77.270856
iter  80 value 77.204178
iter  90 value 77.180403
iter 100 value 77.169858
final  value 77.169858 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.735991 
iter  10 value 94.322051
iter  20 value 85.214690
iter  30 value 83.985811
iter  40 value 81.148939
iter  50 value 80.360884
iter  60 value 79.224408
iter  70 value 77.974705
iter  80 value 77.414862
iter  90 value 77.372492
iter 100 value 77.092447
final  value 77.092447 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.532095 
iter  10 value 94.508318
iter  20 value 94.433355
iter  30 value 84.539187
iter  40 value 82.716969
iter  50 value 81.251249
iter  60 value 80.790221
iter  70 value 80.726438
iter  80 value 80.618549
iter  90 value 80.274093
iter 100 value 79.775354
final  value 79.775354 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.222756 
iter  10 value 94.595824
iter  20 value 85.000162
iter  30 value 82.562742
iter  40 value 81.307801
iter  50 value 81.201512
iter  60 value 80.645211
iter  70 value 78.952139
iter  80 value 77.850152
iter  90 value 77.620091
iter 100 value 77.490456
final  value 77.490456 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.908171 
iter  10 value 94.434646
iter  20 value 85.039469
iter  30 value 82.664276
iter  40 value 81.188037
iter  50 value 78.477128
iter  60 value 78.074939
iter  70 value 77.797155
iter  80 value 77.086984
iter  90 value 76.589351
iter 100 value 76.339925
final  value 76.339925 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.032366 
iter  10 value 95.942921
iter  20 value 92.871909
iter  30 value 92.084606
iter  40 value 91.887283
iter  50 value 91.737684
iter  60 value 84.576512
iter  70 value 80.539029
iter  80 value 79.228835
iter  90 value 78.847217
iter 100 value 78.188181
final  value 78.188181 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.566602 
iter  10 value 95.535323
iter  20 value 84.668581
iter  30 value 82.272977
iter  40 value 81.446550
iter  50 value 81.249366
iter  60 value 80.856511
iter  70 value 80.220555
iter  80 value 79.243408
iter  90 value 78.124294
iter 100 value 77.538271
final  value 77.538271 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.402748 
iter  10 value 94.697702
iter  20 value 90.032238
iter  30 value 84.317159
iter  40 value 80.306478
iter  50 value 79.218915
iter  60 value 78.010776
iter  70 value 77.682848
iter  80 value 77.307260
iter  90 value 76.930624
iter 100 value 76.900193
final  value 76.900193 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.208350 
iter  10 value 94.670541
iter  20 value 88.984846
iter  30 value 86.841883
iter  40 value 82.258278
iter  50 value 80.500982
iter  60 value 79.878029
iter  70 value 79.748769
iter  80 value 79.486434
iter  90 value 78.647888
iter 100 value 78.534162
final  value 78.534162 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.958153 
iter  10 value 87.967600
iter  20 value 83.375617
iter  30 value 80.234954
iter  40 value 77.727516
iter  50 value 77.469975
iter  60 value 77.352072
iter  70 value 77.045725
iter  80 value 76.845842
iter  90 value 76.503814
iter 100 value 76.371333
final  value 76.371333 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.313943 
final  value 94.485827 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.994315 
final  value 94.485728 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.991981 
final  value 94.485718 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.039708 
final  value 94.485711 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.650123 
iter  10 value 94.485745
iter  20 value 94.484024
iter  30 value 92.287035
iter  40 value 91.973535
final  value 91.476556 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.189786 
iter  10 value 94.472284
iter  20 value 93.526425
iter  30 value 89.346079
iter  40 value 78.825709
iter  50 value 78.761055
iter  60 value 78.741583
iter  70 value 78.722056
iter  80 value 78.715252
iter  90 value 78.696683
iter 100 value 78.664138
final  value 78.664138 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.677939 
iter  10 value 94.488887
iter  20 value 86.051317
iter  30 value 81.206432
iter  40 value 81.185366
final  value 81.183214 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.534522 
iter  10 value 94.488617
iter  20 value 86.776159
iter  30 value 80.437489
iter  40 value 80.437085
final  value 80.435744 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.367176 
final  value 94.489288 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.854729 
iter  10 value 94.488372
iter  20 value 94.406466
iter  30 value 82.714727
iter  40 value 80.883616
iter  50 value 80.164428
iter  60 value 80.077772
iter  70 value 78.771734
iter  80 value 78.349578
iter  90 value 78.341094
iter 100 value 78.340031
final  value 78.340031 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.813675 
iter  10 value 94.338705
iter  20 value 93.925931
iter  30 value 93.510077
iter  40 value 93.505149
iter  50 value 93.504548
iter  60 value 93.499082
iter  70 value 93.498226
final  value 93.498211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.677556 
iter  10 value 88.174315
iter  20 value 82.752588
iter  30 value 82.722909
iter  40 value 82.692368
iter  50 value 80.906330
iter  60 value 79.820110
iter  70 value 79.655544
iter  80 value 79.583311
iter  80 value 79.583311
iter  80 value 79.583311
final  value 79.583311 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.583141 
iter  10 value 87.938297
iter  20 value 86.329625
iter  30 value 86.018689
iter  40 value 83.055436
iter  50 value 82.677475
iter  60 value 80.864883
iter  70 value 80.700621
iter  80 value 80.698562
iter  90 value 80.685062
iter 100 value 80.576238
final  value 80.576238 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.793554 
iter  10 value 92.794979
iter  20 value 92.791263
iter  30 value 86.172849
iter  40 value 82.977795
iter  50 value 82.925542
iter  60 value 82.908781
iter  70 value 82.903572
final  value 82.903422 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.022561 
iter  10 value 94.437067
iter  20 value 92.285720
iter  30 value 80.509820
iter  40 value 79.681485
iter  50 value 79.679997
iter  60 value 79.667131
iter  70 value 79.515393
iter  80 value 79.512758
iter  90 value 79.484715
iter 100 value 79.002632
final  value 79.002632 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.080204 
iter  10 value 90.033718
iter  20 value 84.042462
iter  30 value 83.707324
iter  40 value 83.529487
final  value 83.528083 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.464701 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.085796 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.869633 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.303825 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 123.781018 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.580499 
iter  10 value 94.106994
iter  20 value 88.622401
final  value 88.621431 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.950763 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.172182 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.613404 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.535028 
final  value 94.112903 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.850262 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.025450 
iter  10 value 89.624165
iter  20 value 88.757582
iter  30 value 87.837044
iter  40 value 86.871320
iter  50 value 86.835086
final  value 86.834591 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.865643 
iter  10 value 94.090586
final  value 94.090584 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.932378 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.556630 
iter  10 value 94.475219
iter  20 value 93.646112
iter  30 value 87.770555
iter  40 value 87.117141
iter  50 value 86.741529
iter  60 value 86.073714
iter  70 value 84.043606
iter  80 value 82.722435
iter  90 value 82.677626
iter 100 value 82.672921
final  value 82.672921 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.884298 
iter  10 value 94.489039
iter  20 value 89.977719
iter  30 value 86.731391
iter  40 value 85.215145
iter  50 value 84.125617
iter  60 value 83.716734
iter  70 value 83.453921
iter  80 value 83.033059
final  value 83.008491 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.353423 
iter  10 value 94.488296
iter  20 value 94.090070
iter  30 value 87.301349
iter  40 value 87.216113
iter  50 value 85.238685
iter  60 value 84.565663
iter  70 value 83.875728
iter  80 value 83.515520
iter  90 value 82.966249
iter 100 value 82.933464
final  value 82.933464 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.817915 
iter  10 value 94.445133
iter  20 value 88.589477
iter  30 value 84.329696
iter  40 value 83.800984
iter  50 value 83.033691
iter  60 value 83.020353
iter  70 value 83.012670
final  value 83.008491 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.825606 
iter  10 value 93.524967
iter  20 value 88.814222
iter  30 value 84.125200
iter  40 value 83.646744
iter  50 value 83.246363
iter  60 value 82.928684
iter  70 value 82.714453
iter  80 value 82.449683
iter  90 value 82.236318
final  value 82.236012 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.633051 
iter  10 value 94.456466
iter  20 value 91.971925
iter  30 value 89.838002
iter  40 value 89.595354
iter  50 value 84.705898
iter  60 value 84.367150
iter  70 value 82.730682
iter  80 value 81.617669
iter  90 value 81.375848
iter 100 value 81.176612
final  value 81.176612 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.585356 
iter  10 value 94.521545
iter  20 value 94.340033
iter  30 value 91.823827
iter  40 value 90.801788
iter  50 value 90.110233
iter  60 value 84.891754
iter  70 value 82.558683
iter  80 value 81.838264
iter  90 value 81.477292
iter 100 value 81.289598
final  value 81.289598 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.026381 
iter  10 value 93.979207
iter  20 value 90.041824
iter  30 value 89.791149
iter  40 value 88.867064
iter  50 value 85.174719
iter  60 value 83.475486
iter  70 value 81.933969
iter  80 value 81.463299
iter  90 value 81.409420
iter 100 value 81.353392
final  value 81.353392 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.868833 
iter  10 value 94.568878
iter  20 value 87.563617
iter  30 value 86.790186
iter  40 value 85.484126
iter  50 value 83.857737
iter  60 value 83.178555
iter  70 value 82.980812
iter  80 value 82.522504
iter  90 value 81.527806
iter 100 value 81.312850
final  value 81.312850 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.510331 
iter  10 value 94.442952
iter  20 value 94.002330
iter  30 value 92.500893
iter  40 value 91.548230
iter  50 value 90.133117
iter  60 value 89.951188
iter  70 value 89.635080
iter  80 value 89.304092
iter  90 value 86.592379
iter 100 value 84.144116
final  value 84.144116 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.956995 
iter  10 value 94.845585
iter  20 value 87.634983
iter  30 value 85.824573
iter  40 value 83.886232
iter  50 value 83.410087
iter  60 value 82.918927
iter  70 value 81.978072
iter  80 value 81.658044
iter  90 value 81.524691
iter 100 value 81.116364
final  value 81.116364 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.839058 
iter  10 value 94.075258
iter  20 value 84.181555
iter  30 value 83.435234
iter  40 value 82.654420
iter  50 value 81.649783
iter  60 value 80.922580
iter  70 value 80.753524
iter  80 value 80.655203
iter  90 value 80.582538
iter 100 value 80.562836
final  value 80.562836 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.114442 
iter  10 value 94.932093
iter  20 value 91.103716
iter  30 value 87.035604
iter  40 value 86.244544
iter  50 value 85.716652
iter  60 value 81.811870
iter  70 value 81.204162
iter  80 value 81.026614
iter  90 value 80.963924
iter 100 value 80.808455
final  value 80.808455 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.407704 
iter  10 value 94.494825
iter  20 value 86.284995
iter  30 value 84.151055
iter  40 value 83.825221
iter  50 value 83.318364
iter  60 value 82.713965
iter  70 value 82.568069
iter  80 value 82.095178
iter  90 value 81.709178
iter 100 value 81.624787
final  value 81.624787 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.447864 
iter  10 value 91.471784
iter  20 value 84.397383
iter  30 value 84.046217
iter  40 value 83.763138
iter  50 value 83.627651
iter  60 value 82.861130
iter  70 value 82.358393
iter  80 value 81.880765
iter  90 value 81.425746
iter 100 value 81.178964
final  value 81.178964 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.489428 
final  value 94.486086 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.947322 
final  value 94.485977 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.117670 
final  value 94.486037 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.907476 
final  value 94.485766 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.554037 
final  value 94.485999 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.725838 
iter  10 value 94.489027
iter  20 value 90.568716
iter  30 value 87.037385
iter  40 value 86.780169
iter  50 value 84.612764
iter  60 value 84.611017
iter  70 value 84.209046
iter  80 value 84.058337
final  value 84.055917 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.280095 
iter  10 value 94.496505
iter  20 value 94.466230
iter  30 value 94.389433
iter  40 value 94.333884
iter  50 value 94.324522
iter  60 value 94.323384
iter  60 value 94.323384
iter  60 value 94.323383
final  value 94.323383 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.812542 
iter  10 value 94.489161
iter  20 value 94.243529
iter  30 value 91.791514
iter  40 value 91.790723
final  value 91.790657 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.294230 
iter  10 value 94.471884
iter  20 value 94.466449
iter  30 value 94.270235
iter  40 value 92.923107
final  value 92.923099 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.620259 
iter  10 value 94.488996
iter  20 value 94.369203
iter  30 value 91.783147
iter  40 value 91.707828
final  value 91.707254 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.554450 
iter  10 value 91.512889
iter  20 value 91.383432
iter  30 value 91.380377
iter  40 value 90.257928
iter  50 value 89.514275
iter  60 value 89.022857
iter  70 value 88.678349
iter  80 value 88.673479
final  value 88.671497 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.207585 
iter  10 value 94.492316
iter  20 value 94.458379
iter  30 value 87.118249
iter  40 value 82.807224
iter  50 value 82.792042
iter  60 value 82.791613
final  value 82.791534 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.520876 
iter  10 value 94.492614
iter  20 value 91.834380
iter  30 value 87.434012
iter  40 value 85.469339
iter  50 value 84.196930
iter  60 value 83.999270
iter  70 value 82.622950
iter  80 value 82.558002
iter  90 value 82.556884
iter 100 value 82.556687
final  value 82.556687 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.310584 
iter  10 value 94.492384
iter  20 value 94.484331
iter  30 value 93.863625
iter  40 value 88.174897
iter  50 value 87.502278
final  value 87.502076 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.333876 
iter  10 value 94.475130
iter  20 value 94.455148
iter  30 value 94.452966
iter  40 value 94.450494
iter  50 value 94.450003
iter  60 value 87.712428
iter  70 value 87.034015
iter  80 value 86.595146
final  value 86.578174 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.275926 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.688978 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.968533 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.836757 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.324413 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.382978 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.159357 
iter  10 value 85.111633
iter  20 value 83.910201
iter  30 value 83.909751
iter  40 value 83.679304
final  value 83.679291 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.834975 
iter  10 value 93.541483
final  value 93.473742 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.624090 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.494595 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.797530 
final  value 93.288889 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.539096 
final  value 93.084594 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.555951 
iter  10 value 91.507340
iter  20 value 87.931561
final  value 87.813230 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.703724 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.580339 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 120.410773 
iter  10 value 92.246689
iter  20 value 86.074013
iter  30 value 84.511692
iter  40 value 82.947848
iter  50 value 82.648871
iter  60 value 82.183394
iter  70 value 81.679644
iter  80 value 80.631323
iter  90 value 80.628871
final  value 80.628425 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.301142 
iter  10 value 93.981598
iter  20 value 93.225320
iter  30 value 93.062567
iter  40 value 91.068983
iter  50 value 85.137338
iter  60 value 81.292626
iter  70 value 81.182552
iter  80 value 81.122484
iter  90 value 81.121951
iter 100 value 80.850281
final  value 80.850281 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.678028 
iter  10 value 93.743946
iter  20 value 93.081980
iter  30 value 93.065099
iter  40 value 93.060841
iter  50 value 92.577640
iter  60 value 89.590559
iter  70 value 88.856457
iter  80 value 87.959777
iter  90 value 85.166914
iter 100 value 83.729875
final  value 83.729875 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.014281 
iter  10 value 93.951546
iter  20 value 85.552723
iter  30 value 83.570865
iter  40 value 82.423294
iter  50 value 80.741521
iter  60 value 80.630062
iter  70 value 80.628452
final  value 80.628425 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.115412 
iter  10 value 94.064480
iter  20 value 93.890785
iter  30 value 93.684058
iter  40 value 90.820034
iter  50 value 88.147353
iter  60 value 83.395912
iter  70 value 83.179851
iter  80 value 83.164710
final  value 83.164702 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.686279 
iter  10 value 95.525725
iter  20 value 92.733172
iter  30 value 90.703157
iter  40 value 84.161662
iter  50 value 82.969302
iter  60 value 82.367485
iter  70 value 82.034529
iter  80 value 81.101509
iter  90 value 80.892060
iter 100 value 80.339739
final  value 80.339739 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.078482 
iter  10 value 93.979348
iter  20 value 91.807364
iter  30 value 88.024430
iter  40 value 84.201629
iter  50 value 82.664460
iter  60 value 81.971746
iter  70 value 81.796864
iter  80 value 81.531229
iter  90 value 81.008136
iter 100 value 80.844207
final  value 80.844207 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.898579 
iter  10 value 93.928401
iter  20 value 89.914504
iter  30 value 83.742229
iter  40 value 83.177746
iter  50 value 82.703702
iter  60 value 82.596533
iter  70 value 82.521532
iter  80 value 81.835825
iter  90 value 80.277549
iter 100 value 79.929288
final  value 79.929288 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.234337 
iter  10 value 92.930491
iter  20 value 84.203940
iter  30 value 83.382599
iter  40 value 83.275658
iter  50 value 82.995160
iter  60 value 81.269966
iter  70 value 80.213525
iter  80 value 79.821334
iter  90 value 79.783683
iter 100 value 79.703018
final  value 79.703018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.052388 
iter  10 value 93.912244
iter  20 value 86.255275
iter  30 value 85.121607
iter  40 value 84.770831
iter  50 value 82.273484
iter  60 value 80.337519
iter  70 value 80.111178
iter  80 value 79.849643
iter  90 value 79.777277
iter 100 value 79.666744
final  value 79.666744 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.877762 
iter  10 value 93.274918
iter  20 value 89.522418
iter  30 value 87.865223
iter  40 value 84.250872
iter  50 value 81.827416
iter  60 value 80.158276
iter  70 value 80.077530
iter  80 value 79.941677
iter  90 value 79.735505
iter 100 value 79.656336
final  value 79.656336 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.264335 
iter  10 value 94.622324
iter  20 value 93.914740
iter  30 value 88.232784
iter  40 value 87.731937
iter  50 value 84.106624
iter  60 value 81.943765
iter  70 value 81.249965
iter  80 value 80.278803
iter  90 value 79.911842
iter 100 value 79.769479
final  value 79.769479 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.551659 
iter  10 value 95.724203
iter  20 value 85.388467
iter  30 value 83.493694
iter  40 value 82.597726
iter  50 value 81.543718
iter  60 value 80.616572
iter  70 value 79.555098
iter  80 value 79.116497
iter  90 value 79.033402
iter 100 value 78.994961
final  value 78.994961 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.078793 
iter  10 value 94.079984
iter  20 value 92.488070
iter  30 value 84.369923
iter  40 value 83.989996
iter  50 value 83.371217
iter  60 value 82.823202
iter  70 value 82.300701
iter  80 value 80.792736
iter  90 value 80.314280
iter 100 value 79.965511
final  value 79.965511 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 139.561845 
iter  10 value 92.673335
iter  20 value 88.216110
iter  30 value 83.534661
iter  40 value 82.471209
iter  50 value 82.083803
iter  60 value 81.557128
iter  70 value 81.451991
iter  80 value 81.383336
iter  90 value 81.354579
iter 100 value 81.297776
final  value 81.297776 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.127774 
final  value 94.054681 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.326970 
iter  10 value 94.054430
final  value 94.053201 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.219791 
iter  10 value 93.584170
iter  20 value 93.209600
iter  30 value 84.003851
iter  40 value 83.723612
iter  50 value 83.721306
iter  50 value 83.721306
iter  50 value 83.721306
final  value 83.721306 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.665624 
iter  10 value 94.054659
final  value 94.053034 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.866511 
final  value 94.054592 
converged
Fitting Repeat 1 

# weights:  305
initial  value 128.435705 
iter  10 value 94.057942
iter  20 value 94.053008
iter  30 value 93.604777
iter  40 value 92.978534
iter  50 value 92.970800
iter  60 value 92.963584
iter  70 value 87.416087
final  value 86.934506 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.126422 
iter  10 value 93.587903
iter  20 value 93.552525
iter  30 value 89.112228
iter  40 value 89.110016
iter  50 value 87.254289
iter  60 value 86.639901
iter  70 value 82.466827
iter  80 value 79.521273
iter  90 value 79.126185
iter 100 value 79.032820
final  value 79.032820 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.115915 
iter  10 value 94.057740
iter  20 value 94.052894
iter  30 value 93.921500
iter  40 value 90.027192
iter  50 value 83.181141
iter  60 value 83.043282
iter  70 value 83.042759
iter  80 value 82.816552
iter  90 value 82.457665
iter 100 value 82.436795
final  value 82.436795 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.671723 
iter  10 value 93.478736
iter  20 value 93.237432
final  value 93.105021 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.917749 
iter  10 value 94.057351
final  value 94.052933 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.295847 
iter  10 value 89.479354
iter  20 value 85.556002
iter  30 value 85.549161
iter  40 value 85.535661
iter  50 value 84.059472
iter  60 value 81.884803
iter  70 value 81.812982
iter  80 value 81.812565
iter  90 value 81.584921
iter 100 value 81.113602
final  value 81.113602 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.419477 
iter  10 value 94.061372
iter  20 value 93.961604
iter  30 value 93.155030
iter  40 value 92.997084
iter  50 value 92.976811
iter  60 value 92.950410
iter  70 value 87.560041
iter  80 value 82.667555
iter  90 value 82.454265
iter 100 value 82.413977
final  value 82.413977 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.235742 
iter  10 value 94.061457
iter  20 value 93.963876
final  value 93.582663 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.137358 
iter  10 value 94.059540
iter  20 value 93.816564
iter  30 value 92.949286
final  value 92.949251 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.231544 
iter  10 value 92.967461
iter  20 value 92.964945
iter  30 value 92.951110
iter  40 value 92.949628
final  value 92.949480 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.654924 
iter  10 value 117.894960
iter  20 value 117.836885
iter  30 value 117.512956
final  value 117.512939 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.668219 
iter  10 value 115.032344
iter  20 value 115.010919
final  value 115.008250 
converged
Fitting Repeat 3 

# weights:  305
initial  value 131.131523 
iter  10 value 117.764539
iter  20 value 108.368193
iter  30 value 107.252147
iter  40 value 107.108853
iter  50 value 106.315324
iter  60 value 106.223470
iter  70 value 106.221719
iter  80 value 105.691940
iter  90 value 105.689239
iter 100 value 105.481500
final  value 105.481500 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.481526 
iter  10 value 109.252300
iter  20 value 107.009787
iter  30 value 107.008689
iter  40 value 105.057603
final  value 105.057453 
converged
Fitting Repeat 5 

# weights:  305
initial  value 128.041963 
iter  10 value 117.763870
iter  20 value 117.759231
iter  30 value 117.190969
iter  40 value 108.257246
iter  50 value 108.250359
iter  60 value 108.208868
iter  70 value 103.450527
iter  80 value 102.609046
iter  90 value 102.607536
iter 100 value 102.598703
final  value 102.598703 
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 -- Mon Oct 16 02:53:13 2023 
*********************************************** 
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 
 67.804   2.085  79.789