##############################################################################
##############################################################################
###
### Running command:
###
###   D:\biocbuild\bbs-3.15-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=D:\biocbuild\bbs-3.15-bioc\R\library --no-vignettes --timings HPiP_1.1.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'D:/biocbuild/bbs-3.15-bioc/meat/HPiP.Rcheck'
* using R Under development (unstable) (2021-11-21 r81221)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.1.2'
* 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 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
corr_plot     28.08   3.28   31.94
var_imp       27.36   3.83   33.21
FSmethod      26.36   4.49   30.84
pred_ensembel 18.12   0.35    9.40
enrichfindP    0.27   0.02    8.69
* 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
  'D:/biocbuild/bbs-3.15-bioc/meat/HPiP.Rcheck/00check.log'
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   D:\biocbuild\bbs-3.15-bioc\R\bin\R.exe CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library 'D:/biocbuild/bbs-3.15-bioc/R/library'
* installing *source* package 'HPiP' ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
  converting help for package 'HPiP'
    finding HTML links ... done
    FSmethod                                html  
    FreqInteractors                         html  
    Gold_ReferenceSet                       html  
    UP000464024_df                          html  
    calculateAAC                            html  
    calculateAutocor                        html  
    calculateBE                             html  
    calculateCTDC                           html  
    calculateCTDD                           html  
    calculateCTDT                           html  
    calculateCTriad                         html  
    calculateDC                             html  
    calculateF                              html  
    calculateKSAAP                          html  
    calculateQD_Sm                          html  
    calculateTC                             html  
    calculateTC_Sm                          html  
    corr_plot                               html  
    enrich.df                               html  
    enrichfindP                             html  
    enrichfind_cpx                          html  
    enrichfind_hp                           html  
    enrichplot                              html  
    example_data                            html  
    filter_missing_values                   html  
    getFASTA                                html  
    getHPI                                  html  
    get_negativePPI                         html  
    get_positivePPI                         html  
    host_se                                 html  
    impute_missing_data                     html  
    plotPPI                                 html  
    pred_ensembel                           html  
    predicted_PPIs                          html  
    run_clustering                          html  
    unlabel_data                            html  
    var_imp                                 html  
    viral_se                                html  
** 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)
Making 'packages.html' ...Warning in packageDescription(i, lib.loc = lib, fields = "Title", encoding = "UTF-8") :
  DESCRIPTION file of package 'GBScleanR' is missing or broken
Warning in packageDescription(i, lib.loc = lib, fields = "Title", encoding = "UTF-8") :
  DESCRIPTION file of package 'mistyR' is missing or broken
 done

R Under development (unstable) (2021-11-21 r81221) -- "Unsuffered Consequences"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (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
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 101.005805 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.071920 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.925909 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.527274 
final  value 94.484137 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.159307 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.491678 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.863438 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.467290 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.651726 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.146539 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.056748 
iter  10 value 93.260452
final  value 93.221034 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.321342 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.843219 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.409381 
iter  10 value 92.609595
iter  20 value 92.605178
final  value 92.605128 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.801684 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.247387 
iter  10 value 94.487518
iter  20 value 94.402544
iter  30 value 89.899915
iter  40 value 88.948538
iter  50 value 88.810281
iter  60 value 88.380186
iter  70 value 86.942840
iter  80 value 85.121919
iter  90 value 84.121055
iter 100 value 83.488606
final  value 83.488606 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.299795 
iter  10 value 94.523308
iter  20 value 91.050228
iter  30 value 87.241210
iter  40 value 86.978880
iter  50 value 85.830022
iter  60 value 85.361549
iter  70 value 85.295459
iter  80 value 84.958781
iter  90 value 84.792829
iter  90 value 84.792828
iter  90 value 84.792828
final  value 84.792828 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.824124 
iter  10 value 94.495468
iter  20 value 94.489159
iter  30 value 94.297387
iter  40 value 84.646871
iter  50 value 84.533176
iter  60 value 84.159696
iter  70 value 83.923119
iter  80 value 83.916722
final  value 83.916715 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.797105 
iter  10 value 94.455695
iter  20 value 92.319820
iter  30 value 92.018591
iter  40 value 91.852082
iter  50 value 90.955797
iter  60 value 90.787549
iter  70 value 90.767129
final  value 90.766961 
converged
Fitting Repeat 5 

# weights:  103
initial  value 114.113021 
iter  10 value 94.489048
iter  20 value 89.443767
iter  30 value 86.124125
iter  40 value 84.939626
iter  50 value 84.459315
iter  60 value 84.357571
iter  70 value 84.322775
iter  80 value 84.312022
iter  80 value 84.312021
final  value 84.312021 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.791653 
iter  10 value 92.385493
iter  20 value 91.675542
iter  30 value 91.607948
iter  40 value 89.005621
iter  50 value 87.968398
iter  60 value 87.329718
iter  70 value 84.740689
iter  80 value 84.262230
iter  90 value 84.150889
iter 100 value 84.108321
final  value 84.108321 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.679126 
iter  10 value 94.522650
iter  20 value 93.774353
iter  30 value 87.877536
iter  40 value 85.902096
iter  50 value 84.114731
iter  60 value 83.474534
iter  70 value 81.904364
iter  80 value 81.416729
iter  90 value 81.130462
iter 100 value 80.863274
final  value 80.863274 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.795396 
iter  10 value 94.385522
iter  20 value 87.631992
iter  30 value 86.533556
iter  40 value 85.956535
iter  50 value 83.863125
iter  60 value 82.720600
iter  70 value 82.316779
iter  80 value 81.985140
iter  90 value 81.528976
iter 100 value 81.048287
final  value 81.048287 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.710933 
iter  10 value 92.888778
iter  20 value 85.506801
iter  30 value 83.632376
iter  40 value 82.523567
iter  50 value 81.634145
iter  60 value 81.387757
iter  70 value 81.227840
iter  80 value 81.149301
iter  90 value 81.124319
iter 100 value 81.087739
final  value 81.087739 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.086452 
iter  10 value 94.484295
iter  20 value 94.229010
iter  30 value 91.401758
iter  40 value 89.205833
iter  50 value 87.076718
iter  60 value 85.314725
iter  70 value 84.404722
iter  80 value 84.118761
iter  90 value 83.804529
iter 100 value 83.730653
final  value 83.730653 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 132.932084 
iter  10 value 94.481597
iter  20 value 91.100277
iter  30 value 87.849122
iter  40 value 84.389139
iter  50 value 84.218789
iter  60 value 84.130101
iter  70 value 83.561768
iter  80 value 82.548299
iter  90 value 82.243864
iter 100 value 82.027760
final  value 82.027760 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.568135 
iter  10 value 94.204100
iter  20 value 87.013533
iter  30 value 84.128691
iter  40 value 82.905638
iter  50 value 81.767152
iter  60 value 81.359331
iter  70 value 80.870557
iter  80 value 80.505337
iter  90 value 80.299699
iter 100 value 80.258636
final  value 80.258636 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.811849 
iter  10 value 94.773217
iter  20 value 94.173852
iter  30 value 92.051593
iter  40 value 91.871068
iter  50 value 91.822166
iter  60 value 91.806151
iter  70 value 91.646939
iter  80 value 88.345218
iter  90 value 86.501737
iter 100 value 83.956604
final  value 83.956604 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.940524 
iter  10 value 94.498145
iter  20 value 94.428649
iter  30 value 92.121492
iter  40 value 88.897041
iter  50 value 86.717416
iter  60 value 83.768607
iter  70 value 83.295668
iter  80 value 82.926313
iter  90 value 82.325005
iter 100 value 82.185529
final  value 82.185529 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.231652 
iter  10 value 92.689434
iter  20 value 84.514512
iter  30 value 83.883080
iter  40 value 83.257022
iter  50 value 82.927640
iter  60 value 82.713622
iter  70 value 82.528570
iter  80 value 82.395681
iter  90 value 82.309778
iter 100 value 82.225157
final  value 82.225157 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.537993 
final  value 94.485893 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.684619 
final  value 94.485941 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.687747 
final  value 94.485544 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.009199 
iter  10 value 90.803460
iter  20 value 90.416446
iter  30 value 88.068090
iter  40 value 86.348003
iter  50 value 86.300343
iter  60 value 86.283414
iter  70 value 86.282879
iter  80 value 86.282391
iter  90 value 86.280603
iter 100 value 86.274835
final  value 86.274835 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 95.078457 
final  value 94.485783 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.936673 
iter  10 value 94.488206
iter  20 value 94.408113
iter  30 value 87.023667
iter  40 value 86.958716
iter  50 value 86.958443
final  value 86.958438 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.493752 
iter  10 value 94.488826
iter  20 value 94.448150
iter  30 value 84.591242
iter  40 value 83.573982
iter  50 value 83.553457
iter  60 value 83.549116
final  value 83.540098 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.334192 
iter  10 value 94.488942
iter  20 value 94.413910
iter  30 value 91.327147
iter  40 value 91.323651
iter  50 value 91.323363
iter  60 value 91.322571
iter  70 value 91.322332
iter  70 value 91.322332
iter  70 value 91.322332
final  value 91.322332 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.622781 
iter  10 value 94.489493
iter  20 value 94.479558
iter  30 value 94.466829
iter  40 value 94.426985
iter  50 value 94.423682
final  value 94.423632 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.703919 
iter  10 value 94.489058
iter  20 value 94.444942
iter  30 value 88.491633
iter  40 value 86.858501
iter  50 value 83.692573
iter  60 value 83.102838
iter  70 value 82.890320
iter  80 value 82.887531
iter  90 value 81.938635
iter 100 value 81.262652
final  value 81.262652 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.644116 
iter  10 value 87.098676
iter  20 value 86.217134
iter  30 value 86.156432
iter  40 value 86.153742
iter  50 value 86.151563
iter  60 value 86.149586
iter  70 value 86.148652
iter  80 value 86.148148
iter  90 value 86.148023
iter  90 value 86.148023
iter  90 value 86.148023
final  value 86.148023 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.041374 
iter  10 value 94.489753
iter  20 value 93.726219
iter  30 value 88.051815
iter  40 value 86.044644
iter  50 value 86.029536
final  value 86.027412 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.730166 
iter  10 value 94.492325
iter  20 value 89.703458
iter  30 value 86.016799
iter  40 value 85.983021
final  value 85.982056 
converged
Fitting Repeat 4 

# weights:  507
initial  value 138.652972 
iter  10 value 94.657021
iter  20 value 94.574924
iter  30 value 86.608673
iter  40 value 84.955692
iter  50 value 84.634047
iter  60 value 84.303558
iter  70 value 84.277322
iter  80 value 84.271220
iter  90 value 84.268572
iter 100 value 83.245624
final  value 83.245624 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.583113 
iter  10 value 94.511703
iter  20 value 94.494915
iter  30 value 93.862785
iter  40 value 89.853712
iter  50 value 85.650310
iter  60 value 81.874353
iter  70 value 81.470927
iter  80 value 81.462303
iter  90 value 81.361026
iter 100 value 81.268599
final  value 81.268599 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.951005 
iter  10 value 92.945356
iter  10 value 92.945355
iter  10 value 92.945355
final  value 92.945355 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.443404 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.353042 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.810352 
final  value 94.052914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.746033 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.865209 
iter  10 value 92.894873
final  value 92.894611 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.379775 
iter  10 value 92.945357
iter  10 value 92.945357
iter  10 value 92.945357
final  value 92.945357 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.044761 
iter  10 value 92.890020
final  value 92.886891 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.294260 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.399794 
iter  10 value 93.318808
iter  20 value 93.090941
final  value 93.090910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.950124 
iter  10 value 92.945360
final  value 92.945355 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.777087 
iter  10 value 92.946503
final  value 92.945355 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.050606 
iter  10 value 92.948727
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  507
initial  value 127.114831 
iter  10 value 92.945355
iter  10 value 92.945355
iter  10 value 92.945355
final  value 92.945355 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.271210 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 119.147716 
iter  10 value 93.680077
iter  20 value 93.068097
iter  30 value 92.951668
iter  40 value 92.949218
iter  50 value 92.449061
iter  60 value 90.421901
iter  70 value 89.249741
iter  80 value 89.187798
iter  90 value 89.079041
iter 100 value 84.334022
final  value 84.334022 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.027636 
iter  10 value 94.055111
iter  20 value 93.614484
iter  30 value 93.079750
iter  40 value 92.950755
iter  50 value 92.949754
iter  60 value 92.946325
iter  70 value 92.942247
iter  80 value 91.157199
iter  90 value 85.929023
iter 100 value 84.304429
final  value 84.304429 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.095844 
iter  10 value 93.399002
iter  20 value 92.457740
iter  30 value 88.404037
iter  40 value 88.363238
iter  50 value 88.258936
iter  60 value 86.812894
iter  70 value 86.282263
iter  80 value 85.864131
iter  90 value 85.816734
iter 100 value 85.797360
final  value 85.797360 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.186839 
iter  10 value 94.059053
iter  20 value 93.844819
iter  30 value 93.165337
iter  40 value 93.045282
iter  50 value 92.165911
iter  60 value 89.912382
iter  70 value 84.664266
iter  80 value 84.355879
iter  90 value 84.298319
iter 100 value 84.246986
final  value 84.246986 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.438281 
iter  10 value 94.021576
iter  20 value 88.568953
iter  30 value 87.089895
iter  40 value 86.675786
iter  50 value 85.918184
iter  60 value 85.816948
iter  70 value 85.798564
final  value 85.797309 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.649567 
iter  10 value 94.347502
iter  20 value 90.689770
iter  30 value 88.603542
iter  40 value 87.796582
iter  50 value 86.504450
iter  60 value 84.670067
iter  70 value 84.160721
iter  80 value 83.771329
iter  90 value 83.591645
iter 100 value 83.242357
final  value 83.242357 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.450009 
iter  10 value 94.066024
iter  20 value 93.619199
iter  30 value 93.317057
iter  40 value 86.279196
iter  50 value 85.859402
iter  60 value 85.381046
iter  70 value 84.347421
iter  80 value 83.189265
iter  90 value 82.762589
iter 100 value 82.635463
final  value 82.635463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.260530 
iter  10 value 94.012274
iter  20 value 89.002297
iter  30 value 87.011099
iter  40 value 86.683198
iter  50 value 86.208802
iter  60 value 85.806760
iter  70 value 85.567705
iter  80 value 85.472897
iter  90 value 85.415179
iter 100 value 85.379372
final  value 85.379372 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.477553 
iter  10 value 94.841412
iter  20 value 93.018172
iter  30 value 90.373170
iter  40 value 89.408779
iter  50 value 87.953246
iter  60 value 87.372405
iter  70 value 86.592503
iter  80 value 85.233834
iter  90 value 84.859592
iter 100 value 84.720537
final  value 84.720537 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.898921 
iter  10 value 93.920034
iter  20 value 93.591157
iter  30 value 92.156791
iter  40 value 89.941166
iter  50 value 88.835260
iter  60 value 85.419171
iter  70 value 84.973022
iter  80 value 84.345881
iter  90 value 83.089530
iter 100 value 82.277010
final  value 82.277010 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.388766 
iter  10 value 89.129508
iter  20 value 85.683221
iter  30 value 83.788580
iter  40 value 83.338580
iter  50 value 83.173330
iter  60 value 82.819539
iter  70 value 82.212721
iter  80 value 82.081448
iter  90 value 81.933845
iter 100 value 81.617466
final  value 81.617466 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.961085 
iter  10 value 93.347459
iter  20 value 92.979809
iter  30 value 91.790936
iter  40 value 87.645745
iter  50 value 86.850838
iter  60 value 85.903671
iter  70 value 83.187484
iter  80 value 82.358732
iter  90 value 81.759623
iter 100 value 81.002078
final  value 81.002078 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.091066 
iter  10 value 93.241821
iter  20 value 91.286234
iter  30 value 89.835953
iter  40 value 86.179014
iter  50 value 85.002558
iter  60 value 84.219805
iter  70 value 83.775150
iter  80 value 82.893134
iter  90 value 82.362626
iter 100 value 81.575262
final  value 81.575262 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.443272 
iter  10 value 93.647175
iter  20 value 91.984914
iter  30 value 89.311569
iter  40 value 86.181668
iter  50 value 85.405564
iter  60 value 83.330483
iter  70 value 81.935071
iter  80 value 81.297509
iter  90 value 81.172798
iter 100 value 81.063317
final  value 81.063317 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.563636 
iter  10 value 94.609340
iter  20 value 93.935580
iter  30 value 93.406691
iter  40 value 92.996982
iter  50 value 92.832599
iter  60 value 86.692891
iter  70 value 82.600083
iter  80 value 82.079421
iter  90 value 81.954958
iter 100 value 81.918892
final  value 81.918892 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.622958 
iter  10 value 93.362540
iter  20 value 92.947533
iter  30 value 92.945471
iter  40 value 92.887544
iter  40 value 92.887543
iter  40 value 92.887543
final  value 92.887543 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.348175 
final  value 94.054508 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.627008 
iter  10 value 94.056807
final  value 94.055120 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.311012 
iter  10 value 92.947915
iter  20 value 92.947558
iter  30 value 92.946424
iter  40 value 92.742521
iter  50 value 92.231996
iter  60 value 90.120709
iter  70 value 86.115882
iter  80 value 85.471136
iter  90 value 85.439958
iter  90 value 85.439957
iter  90 value 85.439957
final  value 85.439957 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.576716 
final  value 94.054754 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.770977 
iter  10 value 94.058168
iter  20 value 93.845966
iter  30 value 93.163848
iter  40 value 92.945938
iter  40 value 92.945938
iter  40 value 92.945938
final  value 92.945938 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.399810 
iter  10 value 94.057344
iter  20 value 94.044329
iter  30 value 89.918981
iter  40 value 87.608232
iter  50 value 87.424023
iter  60 value 87.336634
final  value 87.335898 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.994322 
iter  10 value 93.091471
iter  20 value 92.720813
iter  30 value 92.717768
iter  40 value 92.651794
iter  50 value 92.646082
iter  50 value 92.646081
iter  50 value 92.646081
final  value 92.646081 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.187098 
iter  10 value 94.058020
iter  20 value 94.042966
iter  30 value 90.956389
iter  40 value 90.802918
iter  50 value 90.364615
iter  50 value 90.364615
iter  50 value 90.364614
final  value 90.364614 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.254347 
iter  10 value 92.850593
iter  20 value 89.892741
iter  30 value 89.406751
iter  40 value 89.402378
iter  50 value 89.393140
iter  60 value 89.348813
iter  70 value 89.307262
iter  80 value 89.196807
iter  90 value 88.459777
iter 100 value 87.856734
final  value 87.856734 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.488540 
iter  10 value 94.269366
iter  20 value 94.039554
iter  30 value 88.874749
iter  40 value 88.845068
iter  50 value 88.838293
iter  60 value 88.584331
iter  70 value 87.245838
iter  80 value 87.198403
iter  90 value 85.197073
final  value 85.185764 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.613977 
iter  10 value 92.953818
iter  20 value 92.895495
iter  30 value 92.894250
iter  40 value 89.843563
iter  50 value 85.846482
iter  60 value 84.700175
iter  70 value 82.643674
iter  80 value 80.591679
iter  90 value 80.492413
iter 100 value 80.357371
final  value 80.357371 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.009301 
iter  10 value 93.824870
iter  20 value 93.823351
iter  30 value 92.978380
final  value 92.888056 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.274153 
iter  10 value 88.432702
iter  20 value 85.884861
iter  30 value 85.884182
final  value 85.884086 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.751749 
iter  10 value 93.211478
iter  20 value 92.091991
iter  30 value 91.958674
iter  40 value 91.500788
iter  50 value 91.426061
iter  60 value 90.714385
iter  70 value 90.655275
iter  80 value 90.653120
iter  90 value 90.054506
iter 100 value 85.733210
final  value 85.733210 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.313659 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.762688 
iter  10 value 94.443916
iter  20 value 94.443247
final  value 94.443244 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.793903 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.598661 
iter  10 value 93.701667
final  value 93.701657 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.126189 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.507640 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.467731 
final  value 94.482150 
converged
Fitting Repeat 3 

# weights:  305
initial  value 122.157009 
iter  10 value 94.444287
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.112575 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.607083 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 140.404551 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.249647 
final  value 94.449438 
converged
Fitting Repeat 3 

# weights:  507
initial  value 134.526592 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.332405 
iter  10 value 85.278026
final  value 84.806308 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.829573 
iter  10 value 94.443861
iter  20 value 94.443245
iter  20 value 94.443244
iter  20 value 94.443244
final  value 94.443244 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.199707 
iter  10 value 93.629224
iter  20 value 83.244259
iter  30 value 82.726921
iter  40 value 82.245358
iter  50 value 82.084575
iter  60 value 82.044921
final  value 82.044754 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.081053 
iter  10 value 94.408052
iter  20 value 93.294283
iter  30 value 93.210370
iter  40 value 93.196378
iter  50 value 89.574688
iter  60 value 83.338744
iter  70 value 82.871958
iter  80 value 82.199236
iter  90 value 81.893351
iter 100 value 80.902537
final  value 80.902537 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.393299 
iter  10 value 94.488729
iter  20 value 93.635892
iter  30 value 93.221018
iter  40 value 83.991727
iter  50 value 82.968205
iter  60 value 82.098393
iter  70 value 81.770762
iter  80 value 81.736795
iter  90 value 80.433902
iter 100 value 80.256397
final  value 80.256397 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.427944 
iter  10 value 94.342914
iter  20 value 87.867162
iter  30 value 86.002742
iter  40 value 85.777858
iter  50 value 82.767909
iter  60 value 82.328919
iter  70 value 81.898722
iter  80 value 81.720187
iter  90 value 81.533681
iter 100 value 80.464066
final  value 80.464066 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.790044 
iter  10 value 88.619976
iter  20 value 82.760896
iter  30 value 82.526680
iter  40 value 82.076482
iter  50 value 81.783387
iter  60 value 81.757639
iter  70 value 81.745561
final  value 81.745559 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.303939 
iter  10 value 94.466734
iter  20 value 83.551684
iter  30 value 81.825451
iter  40 value 80.993721
iter  50 value 79.778270
iter  60 value 79.155977
iter  70 value 78.739655
iter  80 value 78.625252
iter  90 value 78.551659
iter 100 value 78.532191
final  value 78.532191 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.569585 
iter  10 value 94.349689
iter  20 value 93.517664
iter  30 value 93.343661
iter  40 value 87.029621
iter  50 value 84.522208
iter  60 value 83.027979
iter  70 value 81.204985
iter  80 value 80.130292
iter  90 value 79.642287
iter 100 value 79.528694
final  value 79.528694 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.709066 
iter  10 value 94.430806
iter  20 value 93.506968
iter  30 value 85.546737
iter  40 value 84.113619
iter  50 value 83.889022
iter  60 value 83.203439
iter  70 value 81.641825
iter  80 value 81.502953
iter  90 value 81.204217
iter 100 value 80.719504
final  value 80.719504 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.262750 
iter  10 value 94.539390
iter  20 value 90.649252
iter  30 value 83.786728
iter  40 value 83.213753
iter  50 value 81.617480
iter  60 value 80.380459
iter  70 value 79.561564
iter  80 value 78.664436
iter  90 value 78.432733
iter 100 value 78.289378
final  value 78.289378 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.325851 
iter  10 value 94.659480
iter  20 value 94.479580
iter  30 value 84.424874
iter  40 value 83.074660
iter  50 value 82.482520
iter  60 value 81.681504
iter  70 value 79.497494
iter  80 value 78.916390
iter  90 value 78.742830
iter 100 value 78.666604
final  value 78.666604 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.777745 
iter  10 value 94.136669
iter  20 value 89.940338
iter  30 value 87.343915
iter  40 value 85.563819
iter  50 value 83.044679
iter  60 value 80.422198
iter  70 value 79.356760
iter  80 value 79.098552
iter  90 value 78.804953
iter 100 value 78.413874
final  value 78.413874 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.889319 
iter  10 value 90.478969
iter  20 value 84.054378
iter  30 value 82.400136
iter  40 value 81.274998
iter  50 value 80.745456
iter  60 value 79.890418
iter  70 value 79.088944
iter  80 value 78.735332
iter  90 value 78.651957
iter 100 value 78.591246
final  value 78.591246 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.182249 
iter  10 value 89.365568
iter  20 value 85.609869
iter  30 value 84.868504
iter  40 value 84.739091
iter  50 value 82.652279
iter  60 value 81.642007
iter  70 value 81.187042
iter  80 value 80.280440
iter  90 value 79.045358
iter 100 value 78.735548
final  value 78.735548 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.355166 
iter  10 value 97.649329
iter  20 value 89.215892
iter  30 value 85.864964
iter  40 value 85.255726
iter  50 value 82.629588
iter  60 value 81.694238
iter  70 value 81.094404
iter  80 value 78.986917
iter  90 value 78.621725
iter 100 value 78.418546
final  value 78.418546 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.965304 
iter  10 value 94.535843
iter  20 value 87.160597
iter  30 value 83.677984
iter  40 value 82.142715
iter  50 value 81.616971
iter  60 value 80.911716
iter  70 value 80.234519
iter  80 value 79.557319
iter  90 value 79.221807
iter 100 value 79.133346
final  value 79.133346 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.832001 
iter  10 value 94.486101
iter  20 value 94.484236
final  value 94.484213 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.191818 
final  value 94.486003 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.351664 
final  value 94.485669 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.312021 
final  value 94.485663 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.710832 
final  value 94.486155 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.896880 
iter  10 value 94.489095
iter  20 value 94.256231
iter  30 value 89.968960
iter  40 value 89.174388
iter  50 value 87.691230
iter  60 value 87.669896
final  value 86.524710 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.194613 
iter  10 value 93.929060
iter  20 value 93.677694
iter  30 value 91.717447
iter  40 value 91.338918
iter  50 value 91.336647
iter  60 value 91.173567
final  value 91.051536 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.866595 
iter  10 value 92.112908
iter  20 value 83.808981
iter  30 value 83.783148
iter  40 value 83.369172
iter  50 value 83.112864
iter  60 value 82.934208
iter  70 value 82.932727
iter  80 value 82.868317
iter  90 value 82.711166
iter 100 value 80.608866
final  value 80.608866 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.804151 
iter  10 value 94.488956
iter  20 value 94.416974
iter  30 value 93.386825
iter  40 value 83.771250
iter  50 value 81.871425
iter  60 value 81.506476
final  value 81.504234 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.013151 
iter  10 value 94.448140
iter  20 value 94.444270
iter  30 value 89.822017
iter  40 value 83.176934
iter  50 value 82.446338
iter  60 value 81.427487
iter  70 value 81.394684
iter  80 value 81.243902
iter  90 value 81.213849
iter 100 value 81.213796
final  value 81.213796 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.435159 
iter  10 value 94.451414
iter  20 value 91.439398
iter  30 value 85.306477
iter  40 value 84.937258
iter  50 value 82.870601
iter  60 value 81.225691
final  value 81.198962 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.378648 
iter  10 value 94.451382
iter  20 value 94.445133
iter  30 value 94.351546
iter  40 value 93.227435
iter  50 value 93.220605
final  value 93.220591 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.482983 
iter  10 value 94.492612
iter  20 value 94.484242
iter  30 value 93.839289
iter  40 value 92.730956
iter  50 value 85.886822
iter  60 value 82.582534
iter  70 value 82.527336
iter  80 value 81.966452
iter  90 value 81.949393
iter 100 value 81.863143
final  value 81.863143 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.557083 
iter  10 value 84.871035
iter  20 value 84.547573
iter  30 value 81.812664
iter  40 value 81.367553
iter  50 value 81.363367
iter  60 value 81.359010
iter  70 value 81.358222
iter  80 value 81.261798
iter  90 value 81.217023
iter 100 value 81.216757
final  value 81.216757 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.710344 
iter  10 value 94.452368
iter  20 value 94.445036
iter  30 value 85.059031
iter  40 value 84.910131
iter  50 value 84.834800
iter  60 value 82.578494
iter  70 value 81.946848
iter  80 value 81.873395
iter  90 value 81.667545
iter 100 value 81.638408
final  value 81.638408 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.660712 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.710579 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.440596 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.069898 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  103
initial  value 115.135290 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.409204 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.862884 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.073695 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.351845 
iter  10 value 90.159962
iter  20 value 87.242745
iter  30 value 87.236617
final  value 87.236597 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.804608 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.825134 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.170617 
final  value 94.050000 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.283945 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.962120 
final  value 94.050051 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.184434 
iter  10 value 86.347288
iter  20 value 85.202844
iter  30 value 85.050655
iter  40 value 85.010386
iter  50 value 85.002977
iter  60 value 84.985052
iter  70 value 84.967993
iter  80 value 82.666420
iter  90 value 82.638558
final  value 82.638405 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.366540 
iter  10 value 94.056185
iter  20 value 92.933327
iter  30 value 92.595610
iter  40 value 92.552620
iter  50 value 92.342297
iter  60 value 92.234171
iter  70 value 89.572867
iter  80 value 86.045622
iter  90 value 85.899345
iter 100 value 85.212144
final  value 85.212144 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.377953 
iter  10 value 94.056185
iter  20 value 93.612814
iter  30 value 92.635465
iter  40 value 89.736627
iter  50 value 87.255333
iter  60 value 85.996058
iter  70 value 84.731644
iter  80 value 84.574055
iter  90 value 84.468537
iter 100 value 84.352793
final  value 84.352793 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.864336 
iter  10 value 94.042510
iter  20 value 91.394847
iter  30 value 90.544466
iter  40 value 86.277389
iter  50 value 84.856327
iter  60 value 84.696813
iter  70 value 84.448583
iter  80 value 84.406194
iter  90 value 84.293243
final  value 84.282959 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.768140 
iter  10 value 94.054355
iter  20 value 93.589481
iter  30 value 90.772386
iter  40 value 88.684541
iter  50 value 88.584392
iter  60 value 87.945205
iter  70 value 85.043103
iter  80 value 84.221826
iter  90 value 82.435971
iter 100 value 81.932873
final  value 81.932873 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.100157 
iter  10 value 94.051888
iter  20 value 93.574275
iter  30 value 90.378304
iter  40 value 89.061563
iter  50 value 87.763080
iter  60 value 86.192943
iter  70 value 85.871305
iter  80 value 85.787036
iter  90 value 85.658881
iter 100 value 85.482700
final  value 85.482700 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.505552 
iter  10 value 90.748303
iter  20 value 88.613691
iter  30 value 88.124804
iter  40 value 85.070817
iter  50 value 83.121512
iter  60 value 81.699855
iter  70 value 81.363954
iter  80 value 80.926143
iter  90 value 80.257326
iter 100 value 80.158693
final  value 80.158693 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.848633 
iter  10 value 92.502523
iter  20 value 85.648599
iter  30 value 84.332051
iter  40 value 83.869658
iter  50 value 83.341889
iter  60 value 81.235888
iter  70 value 80.583091
iter  80 value 80.535520
iter  90 value 80.505580
iter 100 value 80.431931
final  value 80.431931 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.757308 
iter  10 value 93.933353
iter  20 value 89.100601
iter  30 value 87.032982
iter  40 value 83.579169
iter  50 value 81.497920
iter  60 value 81.240725
iter  70 value 80.633866
iter  80 value 80.536301
iter  90 value 80.401005
iter 100 value 80.036365
final  value 80.036365 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.213170 
iter  10 value 93.857947
iter  20 value 89.484609
iter  30 value 88.052976
iter  40 value 87.025595
iter  50 value 86.756418
iter  60 value 86.594301
iter  70 value 86.226485
iter  80 value 85.465441
iter  90 value 84.365259
iter 100 value 81.800453
final  value 81.800453 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.168686 
iter  10 value 94.042173
iter  20 value 89.391800
iter  30 value 86.168791
iter  40 value 84.909583
iter  50 value 84.511281
iter  60 value 82.657243
iter  70 value 81.869065
iter  80 value 81.285830
iter  90 value 80.920040
iter 100 value 80.802941
final  value 80.802941 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.722855 
iter  10 value 94.342607
iter  20 value 93.526061
iter  30 value 90.027838
iter  40 value 86.512404
iter  50 value 84.617351
iter  60 value 83.920599
iter  70 value 83.649415
iter  80 value 83.271882
iter  90 value 83.230934
iter 100 value 83.123638
final  value 83.123638 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.370007 
iter  10 value 95.189816
iter  20 value 94.541970
iter  30 value 87.823345
iter  40 value 86.346557
iter  50 value 85.854911
iter  60 value 84.740823
iter  70 value 84.281524
iter  80 value 84.092789
iter  90 value 83.086904
iter 100 value 82.600162
final  value 82.600162 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.070495 
iter  10 value 94.230321
iter  20 value 90.095014
iter  30 value 86.653635
iter  40 value 86.249094
iter  50 value 82.728353
iter  60 value 82.052209
iter  70 value 80.935160
iter  80 value 80.190422
iter  90 value 80.024599
iter 100 value 79.971919
final  value 79.971919 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.321943 
iter  10 value 93.715001
iter  20 value 87.896823
iter  30 value 84.383544
iter  40 value 81.185261
iter  50 value 80.583480
iter  60 value 80.503449
iter  70 value 80.205314
iter  80 value 79.954441
iter  90 value 79.871677
iter 100 value 79.772554
final  value 79.772554 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.690522 
iter  10 value 94.045979
iter  20 value 89.949500
iter  30 value 88.460673
iter  40 value 85.193480
iter  50 value 82.059446
iter  60 value 80.951379
iter  70 value 80.562323
iter  80 value 80.457811
iter  90 value 80.166921
iter 100 value 79.751371
final  value 79.751371 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.456290 
iter  10 value 94.054524
iter  20 value 94.052712
iter  30 value 93.918579
iter  40 value 89.687338
iter  50 value 88.591058
iter  60 value 87.283949
iter  70 value 87.281500
final  value 87.281343 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.607008 
iter  10 value 92.498483
iter  20 value 92.497134
iter  30 value 92.496764
iter  40 value 92.495761
final  value 92.495759 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.044839 
iter  10 value 94.034804
iter  20 value 93.688987
iter  30 value 92.668722
iter  40 value 92.667634
iter  50 value 92.412605
iter  60 value 92.411085
final  value 92.411072 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.411412 
iter  10 value 94.043588
iter  20 value 94.034350
final  value 94.033018 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.486024 
iter  10 value 94.054702
final  value 94.052914 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.574251 
iter  10 value 89.288841
iter  20 value 89.014208
iter  30 value 87.525041
iter  40 value 86.937545
iter  50 value 86.841051
iter  60 value 86.840049
iter  70 value 86.839070
iter  80 value 86.593697
iter  90 value 84.626486
iter 100 value 83.721387
final  value 83.721387 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.553085 
iter  10 value 94.038299
iter  20 value 94.033132
final  value 94.033033 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.277630 
iter  10 value 94.037778
iter  20 value 94.033748
iter  30 value 87.754177
iter  40 value 87.249966
iter  50 value 85.535453
iter  60 value 85.424733
iter  60 value 85.424733
iter  60 value 85.424733
final  value 85.424733 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.392007 
iter  10 value 94.084234
iter  20 value 94.047019
iter  30 value 93.023432
iter  40 value 93.010254
iter  50 value 92.859412
iter  60 value 92.804468
iter  70 value 92.767042
iter  80 value 92.762338
final  value 92.762336 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.332044 
iter  10 value 94.057331
iter  20 value 93.858699
iter  30 value 86.890019
iter  40 value 84.818165
iter  50 value 80.880938
iter  60 value 79.980231
iter  70 value 79.943028
iter  80 value 79.888080
iter  90 value 79.878828
iter 100 value 79.859997
final  value 79.859997 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.335162 
iter  10 value 94.058382
iter  20 value 94.056272
iter  30 value 94.003889
iter  40 value 93.555996
iter  50 value 85.224108
iter  60 value 82.488550
iter  70 value 82.189504
iter  80 value 81.858123
iter  90 value 81.629426
iter 100 value 81.448090
final  value 81.448090 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.911335 
iter  10 value 94.063178
iter  20 value 88.433899
iter  30 value 86.337000
iter  40 value 85.127682
iter  50 value 84.847884
iter  60 value 84.512513
iter  70 value 84.510737
iter  80 value 84.510224
iter  80 value 84.510224
final  value 84.510222 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.419196 
iter  10 value 94.041705
iter  20 value 94.034151
iter  30 value 94.032157
iter  40 value 93.095303
iter  50 value 92.670498
iter  60 value 92.465867
iter  70 value 92.425130
iter  80 value 92.389074
iter  90 value 92.388832
iter 100 value 92.387675
final  value 92.387675 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.295234 
iter  10 value 93.892891
iter  20 value 93.887903
iter  30 value 93.423060
iter  40 value 92.280750
final  value 92.181123 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.457974 
iter  10 value 94.040406
iter  20 value 93.423677
iter  30 value 85.307568
iter  40 value 84.185359
iter  50 value 83.824724
iter  60 value 83.824616
final  value 83.824473 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.488670 
iter  10 value 87.922197
iter  20 value 85.412582
iter  20 value 85.412581
iter  20 value 85.412581
final  value 85.412581 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.254457 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.955581 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.406685 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.512950 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.213067 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.308480 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.622337 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.979092 
iter  10 value 87.431233
iter  20 value 83.574205
iter  30 value 83.414990
iter  40 value 82.559197
final  value 82.279001 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.262171 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.299353 
iter  10 value 94.467011
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.329182 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.551674 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.601512 
iter  10 value 86.344017
iter  20 value 84.072511
iter  30 value 84.043878
final  value 84.042678 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.023988 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.050836 
iter  10 value 94.540308
iter  20 value 94.488566
iter  30 value 94.195349
iter  40 value 87.272542
iter  50 value 86.110127
iter  60 value 85.879162
iter  70 value 85.396234
iter  80 value 83.692211
final  value 83.685163 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.676514 
iter  10 value 94.409279
iter  20 value 92.757144
iter  30 value 86.813390
iter  40 value 86.617978
iter  50 value 85.744846
iter  60 value 84.764869
final  value 84.754153 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.520514 
iter  10 value 94.488316
iter  20 value 94.271225
iter  30 value 94.157128
iter  40 value 94.142419
iter  50 value 93.669876
iter  60 value 88.692324
iter  70 value 87.282426
iter  80 value 86.671858
iter  90 value 82.766518
iter 100 value 81.637934
final  value 81.637934 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.737498 
iter  10 value 94.302166
iter  20 value 87.792175
iter  30 value 83.863716
iter  40 value 83.702279
iter  50 value 83.653761
iter  60 value 83.643458
final  value 83.643055 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.338052 
iter  10 value 93.981389
iter  20 value 87.289380
iter  30 value 85.557658
iter  40 value 85.283257
iter  50 value 84.351359
iter  60 value 83.879265
iter  70 value 83.648247
iter  80 value 83.646890
iter  80 value 83.646890
final  value 83.646890 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.492427 
iter  10 value 95.384048
iter  20 value 93.418221
iter  30 value 93.285935
iter  40 value 91.606931
iter  50 value 85.922863
iter  60 value 85.415947
iter  70 value 85.058881
iter  80 value 84.986972
iter  90 value 84.935781
iter 100 value 84.858483
final  value 84.858483 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.129454 
iter  10 value 94.817607
iter  20 value 94.199843
iter  30 value 86.876227
iter  40 value 86.352795
iter  50 value 83.012980
iter  60 value 82.362309
iter  70 value 81.703509
iter  80 value 81.315415
iter  90 value 80.805027
iter 100 value 80.750309
final  value 80.750309 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.876133 
iter  10 value 94.521485
iter  20 value 86.339857
iter  30 value 85.673236
iter  40 value 84.937936
iter  50 value 83.707287
iter  60 value 83.408850
iter  70 value 83.341766
iter  80 value 82.921854
iter  90 value 81.994773
iter 100 value 80.293972
final  value 80.293972 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.104993 
iter  10 value 94.267523
iter  20 value 89.988061
iter  30 value 88.760486
iter  40 value 84.090904
iter  50 value 81.312481
iter  60 value 81.089479
iter  70 value 80.685890
iter  80 value 80.570163
iter  90 value 80.345061
iter 100 value 80.168014
final  value 80.168014 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.423339 
iter  10 value 94.485353
iter  20 value 94.174490
iter  30 value 94.129931
iter  40 value 93.469629
iter  50 value 86.969695
iter  60 value 83.131249
iter  70 value 82.513275
iter  80 value 82.353567
iter  90 value 82.182028
iter 100 value 81.330224
final  value 81.330224 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.484729 
iter  10 value 94.282040
iter  20 value 85.790820
iter  30 value 83.559583
iter  40 value 82.789083
iter  50 value 82.653814
iter  60 value 81.752176
iter  70 value 81.166171
iter  80 value 80.973814
iter  90 value 80.500537
iter 100 value 80.405894
final  value 80.405894 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.681359 
iter  10 value 100.700720
iter  20 value 87.194481
iter  30 value 82.253254
iter  40 value 81.494964
iter  50 value 80.307442
iter  60 value 80.182647
iter  70 value 80.042609
iter  80 value 79.725540
iter  90 value 79.521841
iter 100 value 79.390159
final  value 79.390159 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.552096 
iter  10 value 94.434079
iter  20 value 87.785631
iter  30 value 85.907199
iter  40 value 84.747382
iter  50 value 83.618834
iter  60 value 81.380185
iter  70 value 80.365040
iter  80 value 80.300337
iter  90 value 80.176973
iter 100 value 79.889707
final  value 79.889707 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.927507 
iter  10 value 94.794402
iter  20 value 94.603886
iter  30 value 86.442357
iter  40 value 85.581228
iter  50 value 84.880592
iter  60 value 82.795149
iter  70 value 80.618272
iter  80 value 80.194828
iter  90 value 79.731104
iter 100 value 79.486275
final  value 79.486275 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.483974 
iter  10 value 95.068612
iter  20 value 88.559939
iter  30 value 86.052518
iter  40 value 84.122114
iter  50 value 83.224838
iter  60 value 82.828533
iter  70 value 81.431708
iter  80 value 81.158364
iter  90 value 81.063749
iter 100 value 80.996839
final  value 80.996839 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.346894 
final  value 94.485839 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.809866 
final  value 94.485948 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.919840 
iter  10 value 93.112090
iter  20 value 93.103665
iter  30 value 84.738574
iter  40 value 84.586966
iter  50 value 84.586857
iter  60 value 84.571554
iter  70 value 84.030819
iter  80 value 84.030752
final  value 84.030750 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.824441 
final  value 94.485896 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.335994 
final  value 94.485619 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.741455 
iter  10 value 94.488195
iter  20 value 94.374049
iter  30 value 85.138042
iter  40 value 84.564716
iter  50 value 83.307547
final  value 83.300616 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.154751 
iter  10 value 94.489510
iter  20 value 94.237007
iter  30 value 90.551150
iter  40 value 90.314803
iter  50 value 90.302988
iter  60 value 90.111187
iter  60 value 90.111186
iter  60 value 90.111186
final  value 90.111186 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.546107 
iter  10 value 94.472180
iter  20 value 94.280680
final  value 94.113151 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.204511 
iter  10 value 94.489229
iter  20 value 94.484701
iter  30 value 87.752175
iter  40 value 84.269800
iter  50 value 83.160492
iter  60 value 80.960314
iter  70 value 80.611580
iter  80 value 80.595037
iter  90 value 80.590989
iter 100 value 80.586049
final  value 80.586049 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 94.949869 
iter  10 value 94.489123
iter  20 value 94.342225
iter  30 value 88.927226
iter  40 value 87.046656
iter  50 value 85.900452
iter  60 value 85.741279
iter  70 value 85.737900
iter  80 value 85.737455
iter  80 value 85.737454
iter  80 value 85.737454
final  value 85.737454 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.433063 
iter  10 value 93.118623
iter  20 value 88.858329
iter  30 value 83.870149
iter  40 value 83.832127
iter  50 value 83.831946
iter  60 value 82.909637
iter  70 value 82.249865
final  value 82.231683 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.447256 
iter  10 value 94.474567
iter  20 value 94.242448
iter  30 value 89.144561
iter  40 value 82.784290
iter  50 value 82.619131
iter  60 value 82.616395
iter  70 value 82.615199
iter  80 value 82.605356
iter  90 value 82.388460
iter 100 value 82.042098
final  value 82.042098 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.595636 
iter  10 value 94.492124
iter  20 value 88.223639
iter  30 value 83.091348
iter  40 value 83.038238
final  value 83.038051 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.587704 
iter  10 value 94.319461
iter  20 value 94.300601
iter  30 value 93.567125
iter  40 value 86.842974
iter  50 value 86.332771
iter  60 value 84.529281
iter  70 value 83.855051
iter  80 value 83.851748
iter  90 value 83.851209
iter 100 value 83.608126
final  value 83.608126 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.676790 
iter  10 value 94.488533
iter  20 value 94.471409
iter  30 value 85.140379
iter  40 value 84.053053
iter  50 value 84.034509
final  value 84.033762 
converged
Fitting Repeat 1 

# weights:  507
initial  value 149.602672 
iter  10 value 118.106556
iter  20 value 117.526906
iter  30 value 114.051172
iter  40 value 106.702551
iter  50 value 102.626098
iter  60 value 101.125037
iter  70 value 100.845466
iter  80 value 100.718319
iter  90 value 100.398531
iter 100 value 100.350609
final  value 100.350609 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 143.683342 
iter  10 value 120.130155
iter  20 value 117.962516
iter  30 value 107.486789
iter  40 value 107.273492
iter  50 value 107.162413
iter  60 value 104.908022
iter  70 value 104.016293
iter  80 value 102.430125
iter  90 value 101.623504
iter 100 value 101.530706
final  value 101.530706 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 141.258006 
iter  10 value 118.013794
iter  20 value 117.737575
iter  30 value 108.899930
iter  40 value 107.850811
iter  50 value 104.874037
iter  60 value 103.777779
iter  70 value 103.056083
iter  80 value 102.725384
iter  90 value 102.548823
iter 100 value 101.599546
final  value 101.599546 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 124.590304 
iter  10 value 117.190938
iter  20 value 106.383775
iter  30 value 105.577581
iter  40 value 104.844812
iter  50 value 104.187986
iter  60 value 103.540653
iter  70 value 103.049226
iter  80 value 102.416892
iter  90 value 102.021231
iter 100 value 101.303336
final  value 101.303336 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.574044 
iter  10 value 117.835087
iter  20 value 108.024012
iter  30 value 107.785902
iter  40 value 107.276762
iter  50 value 104.973832
iter  60 value 103.417890
iter  70 value 103.092874
iter  80 value 102.491724
iter  90 value 102.192074
iter 100 value 101.943758
final  value 101.943758 
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 -- Thu Mar 17 19:24:23 2022 
*********************************************** 
Number of test functions: 8 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures
Number of test functions: 8 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: The `.data` argument of `add_column()` must have unique names as of tibble 3.0.0.
Use `.name_repair = "minimal"`.
This warning is displayed once every 8 hours.
Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated. 
2: `repeats` has no meaning for this resampling method. 
3: executing %dopar% sequentially: no parallel backend registered 
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> proc.time()
   user  system elapsed 
  75.15    2.34   47.34