##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.14-bioc/R/library --no-vignettes --timings HPiP_1.0.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.14-bioc/meat/HPiP.Rcheck’
* using R version 4.1.3 (2022-03-10)
* using platform: x86_64-pc-linux-gnu (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.0.0’
* 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
corr_plot     35.793  0.568  36.361
var_imp       34.596  0.760  35.357
FSmethod      31.435  0.740  32.176
pred_ensembel 14.780  0.416  11.299
enrichfindP    0.409  0.016   8.824
* 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
  ‘/home/biocbuild/bbs-3.14-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.14-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
** 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 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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 100.875444 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.549690 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.323700 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.794663 
final  value 94.354395 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.800979 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.669550 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.164509 
iter  10 value 93.927920
iter  20 value 86.248441
iter  30 value 85.667380
iter  40 value 85.666698
final  value 85.666693 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.963294 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.344565 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.886728 
final  value 93.205814 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.823749 
final  value 94.144481 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.823953 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.858853 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.638105 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.339581 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.014132 
iter  10 value 93.890539
iter  20 value 84.408230
iter  30 value 83.095762
iter  40 value 82.903737
iter  50 value 82.735823
iter  60 value 82.497326
final  value 82.494345 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.572234 
iter  10 value 94.260480
iter  20 value 89.823094
iter  30 value 87.858810
iter  40 value 86.017059
iter  50 value 85.561571
iter  60 value 83.864026
iter  70 value 83.199472
iter  80 value 83.178862
iter  90 value 82.976811
iter 100 value 82.500816
final  value 82.500816 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.727258 
iter  10 value 94.486410
iter  20 value 89.129914
iter  30 value 86.746106
iter  40 value 86.454520
iter  50 value 86.198698
iter  60 value 83.228037
iter  70 value 83.025570
iter  80 value 83.022427
final  value 83.022426 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.753080 
iter  10 value 94.461812
iter  20 value 87.595849
iter  30 value 83.608804
iter  40 value 83.448771
iter  50 value 83.291739
iter  60 value 83.106467
iter  70 value 83.022444
final  value 83.022421 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.573374 
iter  10 value 94.486214
iter  20 value 93.802492
iter  30 value 93.580017
iter  40 value 92.688530
iter  50 value 88.885097
iter  60 value 86.967766
iter  70 value 84.890627
iter  80 value 84.479643
iter  90 value 84.413143
final  value 84.413132 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.502237 
iter  10 value 87.828916
iter  20 value 86.263104
iter  30 value 83.271020
iter  40 value 82.790522
iter  50 value 81.791625
iter  60 value 81.536489
iter  70 value 81.069956
iter  80 value 80.219274
iter  90 value 79.974747
iter 100 value 79.863967
final  value 79.863967 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.267261 
iter  10 value 94.493851
iter  20 value 92.705863
iter  30 value 85.242887
iter  40 value 82.671879
iter  50 value 82.059454
iter  60 value 81.439467
iter  70 value 80.127923
iter  80 value 79.872910
iter  90 value 79.802178
iter 100 value 79.499732
final  value 79.499732 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 131.473780 
iter  10 value 94.543601
iter  20 value 86.701114
iter  30 value 83.526962
iter  40 value 83.099917
iter  50 value 82.792759
iter  60 value 81.815304
iter  70 value 79.752075
iter  80 value 79.448186
iter  90 value 79.402702
iter 100 value 79.337333
final  value 79.337333 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.575168 
iter  10 value 94.410169
iter  20 value 90.400345
iter  30 value 88.598576
iter  40 value 86.040566
iter  50 value 83.579969
iter  60 value 82.388923
iter  70 value 81.559921
iter  80 value 81.284802
iter  90 value 81.263921
iter 100 value 81.228730
final  value 81.228730 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.021834 
iter  10 value 94.579496
iter  20 value 92.882121
iter  30 value 85.542340
iter  40 value 85.169308
iter  50 value 84.318225
iter  60 value 80.736788
iter  70 value 79.709746
iter  80 value 79.416869
iter  90 value 79.359752
iter 100 value 79.186715
final  value 79.186715 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.193468 
iter  10 value 94.271099
iter  20 value 85.554686
iter  30 value 82.202702
iter  40 value 81.713573
iter  50 value 79.802472
iter  60 value 79.152969
iter  70 value 78.733915
iter  80 value 78.458082
iter  90 value 78.194140
iter 100 value 78.054101
final  value 78.054101 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.943801 
iter  10 value 94.619334
iter  20 value 92.823953
iter  30 value 83.964607
iter  40 value 82.206094
iter  50 value 81.331730
iter  60 value 80.718123
iter  70 value 79.796032
iter  80 value 78.755256
iter  90 value 78.369115
iter 100 value 78.298822
final  value 78.298822 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.098440 
iter  10 value 95.106308
iter  20 value 94.745669
iter  30 value 92.307514
iter  40 value 83.856862
iter  50 value 83.237075
iter  60 value 83.060832
iter  70 value 81.340411
iter  80 value 81.055013
iter  90 value 80.151731
iter 100 value 79.848849
final  value 79.848849 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.218908 
iter  10 value 94.740251
iter  20 value 92.633874
iter  30 value 89.568306
iter  40 value 83.814826
iter  50 value 82.764133
iter  60 value 80.654791
iter  70 value 79.858429
iter  80 value 79.360193
iter  90 value 78.682855
iter 100 value 78.319002
final  value 78.319002 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 131.795801 
iter  10 value 95.916128
iter  20 value 85.589212
iter  30 value 83.402001
iter  40 value 82.679867
iter  50 value 81.008202
iter  60 value 79.734183
iter  70 value 79.682702
iter  80 value 78.727664
iter  90 value 78.414514
iter 100 value 78.237009
final  value 78.237009 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 93.042711 
iter  10 value 89.276173
iter  20 value 88.468486
iter  30 value 88.006137
iter  40 value 87.963761
final  value 87.963757 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.128585 
iter  10 value 94.485856
iter  20 value 94.484182
iter  30 value 92.434640
iter  40 value 90.883585
iter  50 value 90.882674
iter  50 value 90.882674
iter  50 value 90.882674
final  value 90.882674 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.956572 
final  value 94.486141 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.441153 
iter  10 value 94.485765
iter  20 value 94.420400
iter  30 value 84.634061
iter  40 value 84.402492
final  value 84.387964 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.626953 
iter  10 value 94.147009
iter  20 value 93.779012
iter  30 value 93.746706
iter  40 value 93.620183
iter  50 value 93.615587
iter  60 value 90.225428
iter  70 value 85.877746
iter  80 value 84.198046
iter  90 value 84.130836
iter 100 value 84.130165
final  value 84.130165 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 96.580601 
iter  10 value 94.489441
final  value 94.484682 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.605517 
iter  10 value 94.488669
iter  20 value 94.382171
final  value 93.300498 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.561987 
iter  10 value 85.419906
iter  20 value 85.180791
iter  30 value 85.170659
iter  40 value 85.015022
iter  50 value 85.014289
iter  60 value 85.002439
iter  70 value 84.375895
iter  80 value 83.974063
iter  90 value 83.970884
iter 100 value 83.968932
final  value 83.968932 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.325866 
iter  10 value 94.358677
iter  20 value 94.354943
iter  30 value 94.131447
iter  40 value 94.131049
iter  50 value 93.720434
final  value 93.720353 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.577149 
iter  10 value 94.489273
iter  20 value 92.326454
iter  30 value 84.679259
iter  40 value 84.632492
iter  50 value 84.632138
iter  60 value 84.632009
iter  70 value 84.540835
final  value 84.388589 
converged
Fitting Repeat 1 

# weights:  507
initial  value 141.125234 
iter  10 value 94.492805
iter  20 value 94.486103
iter  30 value 93.749727
final  value 93.746268 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.643112 
iter  10 value 94.492431
iter  20 value 94.413021
iter  30 value 90.421360
iter  40 value 82.825039
iter  50 value 82.637195
iter  60 value 82.335753
iter  70 value 82.168836
iter  80 value 81.675492
iter  90 value 80.584312
iter 100 value 80.529734
final  value 80.529734 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 129.747275 
iter  10 value 94.586024
iter  20 value 94.515930
iter  30 value 93.811517
iter  40 value 93.095838
iter  50 value 92.926187
iter  60 value 92.758769
iter  70 value 92.731459
iter  80 value 92.709437
iter  90 value 89.247300
iter 100 value 88.707539
final  value 88.707539 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.080159 
iter  10 value 91.149911
iter  20 value 89.555458
iter  30 value 87.277837
iter  40 value 81.768602
iter  50 value 81.374486
iter  60 value 81.001747
iter  70 value 80.810620
iter  80 value 80.806263
iter  90 value 80.798836
iter 100 value 80.796416
final  value 80.796416 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.185999 
iter  10 value 86.954257
iter  20 value 82.173132
iter  30 value 82.168518
iter  40 value 82.166742
iter  50 value 82.165432
iter  60 value 82.163683
iter  70 value 82.161737
iter  80 value 81.937935
iter  90 value 81.935681
iter 100 value 81.934925
final  value 81.934925 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.418653 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.362574 
iter  10 value 94.038536
iter  20 value 94.035099
iter  30 value 93.582421
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.859455 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.994600 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.276701 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.166916 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.387598 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.662194 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 117.360615 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.320076 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.236367 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.119875 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.790973 
iter  10 value 93.178579
iter  10 value 93.178579
final  value 93.178572 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.471502 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.070778 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.835798 
iter  10 value 94.034539
iter  20 value 90.756084
iter  30 value 87.503235
iter  40 value 82.659402
iter  50 value 82.559463
iter  60 value 82.533037
iter  70 value 82.392552
iter  80 value 82.269390
iter  90 value 80.494278
iter 100 value 79.434651
final  value 79.434651 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.532995 
iter  10 value 85.967488
iter  20 value 85.624655
iter  30 value 85.538096
iter  40 value 83.148797
iter  50 value 82.285305
iter  60 value 81.950561
iter  70 value 81.829542
iter  80 value 79.662146
iter  90 value 78.832679
iter 100 value 78.668408
final  value 78.668408 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.705429 
iter  10 value 93.044766
iter  20 value 92.503386
iter  30 value 85.601524
iter  40 value 85.173695
iter  50 value 83.103110
iter  60 value 82.215940
iter  70 value 80.265733
iter  80 value 79.466443
iter  90 value 79.278947
iter 100 value 78.875627
final  value 78.875627 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.616327 
iter  10 value 93.823625
iter  20 value 83.833531
iter  30 value 83.142259
iter  40 value 82.643935
iter  50 value 82.408408
iter  60 value 82.285804
iter  70 value 82.244258
iter  80 value 80.141052
iter  90 value 79.393527
iter 100 value 78.909394
final  value 78.909394 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.493481 
iter  10 value 94.045243
iter  20 value 93.892107
iter  30 value 85.394755
iter  40 value 83.803926
iter  50 value 82.843879
iter  60 value 80.375464
iter  70 value 80.074563
iter  80 value 79.880270
iter  90 value 79.748297
iter 100 value 79.299095
final  value 79.299095 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.908729 
iter  10 value 93.242495
iter  20 value 92.423399
iter  30 value 92.309515
iter  40 value 89.064859
iter  50 value 86.837618
iter  60 value 86.318965
iter  70 value 85.177612
iter  80 value 84.736515
iter  90 value 81.695141
iter 100 value 80.214585
final  value 80.214585 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.883192 
iter  10 value 93.140186
iter  20 value 87.490379
iter  30 value 86.159018
iter  40 value 85.855495
iter  50 value 83.328723
iter  60 value 79.885144
iter  70 value 78.936738
iter  80 value 78.131645
iter  90 value 77.711082
iter 100 value 77.313799
final  value 77.313799 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.626696 
iter  10 value 94.013158
iter  20 value 83.462591
iter  30 value 82.493124
iter  40 value 80.408737
iter  50 value 79.963643
iter  60 value 79.140242
iter  70 value 78.750747
iter  80 value 78.587741
iter  90 value 78.558493
iter 100 value 78.530017
final  value 78.530017 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.495007 
iter  10 value 94.056206
iter  20 value 93.691238
iter  30 value 89.418840
iter  40 value 86.534060
iter  50 value 83.068847
iter  60 value 81.589069
iter  70 value 80.907629
iter  80 value 79.624597
iter  90 value 78.971609
iter 100 value 78.390644
final  value 78.390644 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 148.133838 
iter  10 value 93.945200
iter  20 value 86.769825
iter  30 value 83.166120
iter  40 value 82.491890
iter  50 value 80.581108
iter  60 value 80.170992
iter  70 value 80.043614
iter  80 value 79.973422
iter  90 value 79.693546
iter 100 value 78.301902
final  value 78.301902 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.913745 
iter  10 value 94.122145
iter  20 value 91.216479
iter  30 value 82.569148
iter  40 value 81.722004
iter  50 value 81.303886
iter  60 value 81.126898
iter  70 value 80.517935
iter  80 value 79.063930
iter  90 value 77.585296
iter 100 value 76.843985
final  value 76.843985 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.633816 
iter  10 value 93.842021
iter  20 value 87.417778
iter  30 value 84.320692
iter  40 value 80.793980
iter  50 value 77.851790
iter  60 value 77.688355
iter  70 value 77.608904
iter  80 value 77.371871
iter  90 value 77.288059
iter 100 value 77.208912
final  value 77.208912 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.548564 
iter  10 value 93.883583
iter  20 value 92.515518
iter  30 value 92.372955
iter  40 value 89.179394
iter  50 value 85.096080
iter  60 value 82.049145
iter  70 value 80.926440
iter  80 value 79.522788
iter  90 value 78.873775
iter 100 value 78.208124
final  value 78.208124 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.904200 
iter  10 value 93.808811
iter  20 value 91.964384
iter  30 value 90.555007
iter  40 value 85.304114
iter  50 value 84.223492
iter  60 value 82.413077
iter  70 value 81.572987
iter  80 value 80.550950
iter  90 value 80.153938
iter 100 value 79.210305
final  value 79.210305 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.635019 
iter  10 value 94.020768
iter  20 value 92.636926
iter  30 value 90.406267
iter  40 value 82.939005
iter  50 value 81.868726
iter  60 value 80.434843
iter  70 value 78.130722
iter  80 value 77.550426
iter  90 value 77.174096
iter 100 value 76.887734
final  value 76.887734 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.248307 
final  value 94.054597 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.437051 
final  value 94.054532 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.462232 
final  value 93.583989 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.114578 
final  value 94.054794 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.799913 
final  value 94.054513 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.024724 
iter  10 value 89.628033
iter  20 value 89.626795
iter  30 value 89.622065
iter  40 value 89.433510
iter  50 value 88.319014
iter  60 value 85.881979
iter  70 value 81.326872
iter  80 value 79.337182
iter  90 value 79.137551
iter 100 value 79.130782
final  value 79.130782 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.515864 
iter  10 value 94.057656
iter  20 value 94.053291
iter  30 value 88.388430
iter  40 value 81.144193
iter  50 value 80.918733
iter  60 value 80.770122
final  value 80.767754 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.363014 
iter  10 value 93.587629
iter  20 value 93.129537
iter  30 value 92.239083
iter  40 value 92.238629
iter  50 value 92.208162
iter  60 value 92.150641
iter  70 value 92.149821
iter  80 value 92.147277
final  value 92.147251 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.582842 
iter  10 value 94.057505
iter  20 value 93.858599
iter  30 value 93.241560
iter  40 value 93.226625
iter  50 value 93.194406
final  value 93.179139 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.061509 
iter  10 value 94.058234
iter  20 value 93.455575
iter  30 value 85.105054
iter  40 value 84.730772
iter  50 value 84.730202
iter  60 value 84.354474
iter  70 value 84.334264
iter  80 value 83.619734
iter  90 value 78.470006
iter 100 value 78.384677
final  value 78.384677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.145863 
iter  10 value 92.260995
iter  20 value 90.660169
iter  30 value 90.580773
iter  40 value 90.289362
iter  50 value 90.288214
final  value 90.287585 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.989117 
iter  10 value 90.562716
iter  20 value 78.845140
iter  30 value 78.273100
iter  40 value 78.133774
iter  50 value 78.131890
iter  60 value 77.927105
iter  70 value 77.921252
iter  80 value 77.780663
iter  90 value 77.579743
iter 100 value 77.574998
final  value 77.574998 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.019043 
iter  10 value 94.061228
iter  20 value 94.051153
iter  30 value 91.928788
iter  40 value 84.634261
iter  50 value 84.467227
iter  60 value 84.466996
iter  70 value 84.465865
iter  80 value 84.167176
iter  90 value 82.926591
iter 100 value 80.244345
final  value 80.244345 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.246748 
iter  10 value 91.020000
iter  20 value 89.441361
iter  30 value 89.411760
final  value 89.407961 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.162357 
iter  10 value 94.054993
iter  20 value 93.860581
iter  30 value 86.717083
iter  40 value 80.180290
iter  50 value 80.155649
iter  60 value 80.134152
iter  70 value 80.125415
iter  80 value 80.099076
iter  90 value 79.569446
iter 100 value 77.405738
final  value 77.405738 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.551362 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.877413 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.136869 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.687132 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.972772 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.067235 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.718147 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.725793 
final  value 94.443182 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.682194 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.407633 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.325606 
final  value 94.476190 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.768244 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.803344 
iter  10 value 94.304608
iter  10 value 94.304608
iter  10 value 94.304608
final  value 94.304608 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.517179 
iter  10 value 94.457469
final  value 94.457409 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.685286 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.855328 
iter  10 value 92.410553
iter  20 value 86.233185
iter  30 value 85.917070
iter  40 value 85.767926
iter  50 value 85.354496
iter  60 value 84.846167
iter  70 value 84.679215
iter  80 value 84.551975
iter  90 value 84.504874
final  value 84.504493 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.324434 
iter  10 value 93.912552
iter  20 value 86.010611
iter  30 value 85.714343
iter  40 value 85.474251
iter  50 value 85.117161
iter  60 value 84.771868
iter  70 value 84.678971
iter  80 value 84.667067
iter  90 value 84.542477
iter 100 value 84.504493
final  value 84.504493 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.155940 
iter  10 value 94.487710
iter  20 value 86.704579
iter  30 value 85.863733
iter  40 value 85.576464
iter  50 value 85.162262
iter  60 value 84.714873
iter  70 value 84.665796
iter  80 value 84.527627
final  value 84.504493 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.867752 
iter  10 value 89.826276
iter  20 value 85.522827
iter  30 value 84.732127
iter  40 value 83.965030
iter  50 value 83.558626
iter  60 value 83.195137
iter  70 value 83.157947
final  value 83.157299 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.041114 
iter  10 value 92.375611
iter  20 value 87.782808
iter  30 value 86.274753
iter  40 value 86.255430
iter  50 value 85.982689
iter  60 value 85.887893
final  value 85.887890 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.313567 
iter  10 value 94.318542
iter  20 value 86.940891
iter  30 value 86.020961
iter  40 value 85.572325
iter  50 value 84.438552
iter  60 value 83.267267
iter  70 value 82.828662
iter  80 value 82.532770
iter  90 value 82.464751
iter 100 value 82.405587
final  value 82.405587 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.031766 
iter  10 value 94.537351
iter  20 value 91.272294
iter  30 value 85.989707
iter  40 value 85.515210
iter  50 value 84.315479
iter  60 value 82.849254
iter  70 value 82.561545
iter  80 value 82.283202
iter  90 value 82.201552
iter 100 value 82.098277
final  value 82.098277 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 131.987270 
iter  10 value 94.501003
iter  20 value 89.517038
iter  30 value 86.743546
iter  40 value 84.648939
iter  50 value 83.340896
iter  60 value 83.099509
iter  70 value 83.009603
iter  80 value 82.828901
iter  90 value 82.613609
iter 100 value 82.474183
final  value 82.474183 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.115821 
iter  10 value 94.950045
iter  20 value 94.196289
iter  30 value 86.943956
iter  40 value 86.481945
iter  50 value 84.482416
iter  60 value 83.889433
iter  70 value 83.458889
iter  80 value 82.934449
iter  90 value 82.212110
iter 100 value 82.163659
final  value 82.163659 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.084281 
iter  10 value 94.481232
iter  20 value 93.926283
iter  30 value 92.402483
iter  40 value 91.600645
iter  50 value 87.752051
iter  60 value 87.444219
iter  70 value 86.890959
iter  80 value 86.767100
iter  90 value 86.151108
iter 100 value 85.846538
final  value 85.846538 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.451018 
iter  10 value 94.494189
iter  20 value 93.092028
iter  30 value 87.124762
iter  40 value 85.234986
iter  50 value 84.336646
iter  60 value 82.665854
iter  70 value 82.388325
iter  80 value 82.157381
iter  90 value 82.053684
iter 100 value 82.048191
final  value 82.048191 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.489856 
iter  10 value 95.322625
iter  20 value 91.445997
iter  30 value 86.435703
iter  40 value 85.602648
iter  50 value 85.372104
iter  60 value 85.276471
iter  70 value 84.815401
iter  80 value 84.062548
iter  90 value 82.466710
iter 100 value 82.199772
final  value 82.199772 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.372137 
iter  10 value 91.400135
iter  20 value 86.488558
iter  30 value 86.074889
iter  40 value 85.440933
iter  50 value 83.684666
iter  60 value 82.866725
iter  70 value 82.412836
iter  80 value 82.052495
iter  90 value 81.845329
iter 100 value 81.764124
final  value 81.764124 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.825309 
iter  10 value 94.464515
iter  20 value 86.623505
iter  30 value 85.626101
iter  40 value 85.220128
iter  50 value 84.978138
iter  60 value 84.847741
iter  70 value 84.701702
iter  80 value 84.084673
iter  90 value 83.523267
iter 100 value 83.353210
final  value 83.353210 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.932233 
iter  10 value 94.547122
iter  20 value 92.373459
iter  30 value 91.107146
iter  40 value 89.665111
iter  50 value 88.897807
iter  60 value 86.250427
iter  70 value 83.142237
iter  80 value 82.493759
iter  90 value 82.439851
iter 100 value 82.086750
final  value 82.086750 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.726049 
final  value 94.485929 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.996892 
final  value 94.485877 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.638337 
final  value 94.485844 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.410357 
final  value 94.485871 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.755599 
final  value 94.485641 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.289937 
iter  10 value 94.488880
iter  20 value 94.028282
iter  30 value 87.821216
iter  40 value 87.738449
iter  50 value 87.283885
iter  60 value 85.198068
iter  70 value 85.057009
iter  80 value 85.053051
iter  90 value 85.052428
iter 100 value 84.891828
final  value 84.891828 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.689457 
iter  10 value 94.489271
iter  20 value 87.607472
final  value 86.940863 
converged
Fitting Repeat 3 

# weights:  305
initial  value 130.226603 
iter  10 value 94.487836
iter  20 value 94.466862
iter  30 value 85.352254
iter  40 value 84.993763
iter  50 value 84.991645
iter  60 value 84.910302
iter  70 value 84.861013
iter  80 value 83.805409
iter  90 value 83.585419
iter 100 value 83.583341
final  value 83.583341 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.468029 
iter  10 value 94.471660
iter  20 value 94.329030
iter  30 value 87.539975
iter  40 value 87.538775
iter  50 value 87.524540
iter  60 value 87.081670
iter  70 value 87.070712
final  value 87.070675 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.605863 
iter  10 value 94.484852
iter  20 value 94.362889
iter  30 value 91.173851
iter  40 value 91.172500
iter  50 value 90.421070
iter  60 value 85.372030
iter  70 value 83.558019
iter  80 value 83.468357
iter  90 value 83.467095
iter 100 value 83.466358
final  value 83.466358 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.543709 
iter  10 value 91.699416
iter  20 value 90.746524
iter  30 value 87.977727
iter  40 value 85.004923
iter  50 value 84.755591
iter  60 value 84.734663
iter  70 value 84.412453
iter  80 value 84.128653
iter  90 value 84.126213
iter 100 value 84.055413
final  value 84.055413 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.870995 
iter  10 value 94.492152
iter  20 value 94.476716
iter  30 value 94.473060
iter  40 value 94.461719
iter  50 value 90.851757
iter  60 value 85.680812
iter  70 value 85.095473
iter  80 value 84.977720
iter  90 value 84.860913
iter 100 value 84.806644
final  value 84.806644 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.668922 
iter  10 value 94.274345
iter  20 value 94.260936
iter  30 value 94.255071
iter  40 value 94.254500
iter  50 value 94.253702
iter  50 value 94.253701
final  value 94.253701 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.917104 
iter  10 value 94.492320
iter  20 value 94.484399
iter  30 value 93.719880
iter  40 value 91.426638
iter  50 value 91.357944
iter  60 value 86.579030
iter  70 value 85.706059
iter  80 value 85.085226
iter  90 value 85.053288
iter 100 value 84.995750
final  value 84.995750 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.864735 
iter  10 value 94.492312
iter  20 value 94.289838
iter  30 value 89.617550
iter  40 value 87.703702
iter  50 value 87.195060
iter  60 value 87.131025
iter  70 value 87.128781
iter  80 value 87.127958
iter  90 value 87.127409
iter 100 value 87.117661
final  value 87.117661 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.846626 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.728391 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.596589 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.464835 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.704167 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.767060 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.785706 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.324571 
final  value 94.114232 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.925194 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.765904 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.673454 
final  value 94.114232 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.551726 
iter  10 value 94.473131
final  value 94.473118 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.643717 
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.341095 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.995870 
iter  10 value 94.473775
iter  20 value 94.473130
final  value 94.473119 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.174224 
iter  10 value 94.523300
iter  20 value 94.488596
iter  30 value 94.438957
iter  40 value 84.979583
iter  50 value 84.059097
iter  60 value 83.215766
iter  70 value 82.585261
iter  80 value 82.517749
iter  90 value 82.507040
iter  90 value 82.507040
iter  90 value 82.507040
final  value 82.507040 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.750186 
iter  10 value 94.286401
iter  20 value 94.122077
iter  30 value 92.637217
iter  40 value 86.857754
iter  50 value 83.224690
iter  60 value 82.893909
iter  70 value 82.689877
iter  80 value 82.003320
iter  90 value 81.478882
iter 100 value 81.401544
final  value 81.401544 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.135932 
iter  10 value 94.414691
iter  20 value 91.961642
iter  30 value 88.291607
iter  40 value 84.582420
iter  50 value 83.525233
iter  60 value 83.382210
final  value 83.376742 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.443801 
iter  10 value 94.414768
iter  20 value 91.536592
iter  30 value 83.787845
iter  40 value 82.980962
iter  50 value 82.862036
iter  60 value 81.956073
iter  70 value 81.488678
final  value 81.484066 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.068949 
iter  10 value 94.501795
iter  20 value 93.020427
iter  30 value 89.491135
iter  40 value 88.765677
iter  50 value 83.519518
iter  60 value 83.229295
iter  70 value 82.764656
iter  80 value 81.828804
iter  90 value 81.352471
iter 100 value 80.845914
final  value 80.845914 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.691664 
iter  10 value 94.496928
iter  20 value 94.291373
iter  30 value 92.011185
iter  40 value 91.337565
iter  50 value 91.050327
iter  60 value 90.876098
iter  70 value 90.831252
iter  80 value 85.031218
iter  90 value 83.681506
iter 100 value 82.433196
final  value 82.433196 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 134.590505 
iter  10 value 94.487195
iter  20 value 90.891555
iter  30 value 86.266107
iter  40 value 84.308742
iter  50 value 82.771160
iter  60 value 81.401838
iter  70 value 80.502138
iter  80 value 79.739009
iter  90 value 79.675370
iter 100 value 79.573497
final  value 79.573497 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 121.321189 
iter  10 value 94.481089
iter  20 value 86.437683
iter  30 value 83.967509
iter  40 value 82.375306
iter  50 value 81.899867
iter  60 value 80.707048
iter  70 value 80.438179
iter  80 value 80.347587
iter  90 value 80.161737
iter 100 value 79.750189
final  value 79.750189 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.422120 
iter  10 value 94.478450
iter  20 value 87.251162
iter  30 value 85.443473
iter  40 value 84.792450
iter  50 value 84.271346
iter  60 value 82.999523
iter  70 value 82.519131
iter  80 value 82.258597
iter  90 value 82.137214
iter 100 value 81.321756
final  value 81.321756 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.672872 
iter  10 value 88.084755
iter  20 value 83.538106
iter  30 value 82.962084
iter  40 value 82.881426
iter  50 value 82.674093
iter  60 value 81.692227
iter  70 value 81.283386
iter  80 value 80.452497
iter  90 value 79.715927
iter 100 value 79.427752
final  value 79.427752 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.903849 
iter  10 value 98.422635
iter  20 value 92.708038
iter  30 value 91.725659
iter  40 value 90.981876
iter  50 value 90.516296
iter  60 value 83.313149
iter  70 value 82.076227
iter  80 value 80.801258
iter  90 value 80.645746
iter 100 value 80.417035
final  value 80.417035 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.775071 
iter  10 value 95.202846
iter  20 value 94.499990
iter  30 value 92.306907
iter  40 value 83.254535
iter  50 value 82.611251
iter  60 value 82.139894
iter  70 value 81.635236
iter  80 value 81.352524
iter  90 value 80.926584
iter 100 value 80.101636
final  value 80.101636 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.937910 
iter  10 value 94.599802
iter  20 value 91.314985
iter  30 value 88.964728
iter  40 value 86.448273
iter  50 value 85.831078
iter  60 value 85.739013
iter  70 value 83.040983
iter  80 value 82.642309
iter  90 value 82.583855
iter 100 value 82.549054
final  value 82.549054 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.773061 
iter  10 value 92.770578
iter  20 value 85.743745
iter  30 value 85.357949
iter  40 value 83.614771
iter  50 value 81.698860
iter  60 value 81.478128
iter  70 value 81.279288
iter  80 value 80.831427
iter  90 value 79.948604
iter 100 value 79.394237
final  value 79.394237 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.203648 
iter  10 value 94.393869
iter  20 value 91.992034
iter  30 value 85.796882
iter  40 value 83.932385
iter  50 value 83.117666
iter  60 value 82.592791
iter  70 value 81.077539
iter  80 value 79.588119
iter  90 value 79.287542
iter 100 value 79.156792
final  value 79.156792 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.650019 
iter  10 value 93.346112
iter  20 value 92.990111
iter  30 value 91.796853
iter  40 value 91.791471
iter  50 value 91.436342
final  value 91.089332 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.875876 
final  value 94.485928 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.589482 
final  value 94.485726 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.959754 
final  value 94.485795 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.579160 
final  value 94.485896 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.927027 
iter  10 value 94.447254
iter  20 value 91.825588
iter  30 value 91.694517
iter  40 value 91.277763
iter  50 value 91.257387
iter  60 value 91.255695
iter  70 value 90.590318
iter  80 value 90.502951
iter  90 value 90.486083
final  value 90.486078 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.731322 
iter  10 value 94.487238
iter  20 value 94.484234
iter  30 value 93.087546
iter  40 value 88.193976
iter  50 value 84.353874
final  value 84.231333 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.830642 
iter  10 value 94.490599
iter  20 value 94.472820
iter  30 value 84.866557
iter  40 value 84.837517
iter  50 value 84.832208
iter  60 value 83.099596
iter  70 value 80.368650
iter  80 value 80.009056
iter  90 value 79.352340
iter 100 value 79.352166
final  value 79.352166 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.622676 
iter  10 value 94.488975
iter  20 value 94.283470
iter  30 value 90.973771
iter  40 value 84.286969
iter  50 value 84.232010
iter  60 value 82.276053
iter  70 value 82.181673
final  value 82.173972 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.894531 
iter  10 value 94.477892
iter  20 value 94.470224
iter  30 value 93.663776
iter  40 value 93.377616
iter  50 value 91.810487
iter  60 value 91.266661
iter  70 value 91.262455
iter  80 value 91.259099
iter  90 value 91.248460
iter 100 value 91.062706
final  value 91.062706 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.032021 
iter  10 value 94.461042
iter  20 value 94.451778
final  value 94.450953 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.545732 
iter  10 value 94.440912
iter  20 value 94.433729
iter  30 value 93.128797
iter  40 value 87.474365
iter  50 value 83.214154
iter  60 value 82.577548
iter  70 value 81.961691
iter  80 value 81.947820
iter  90 value 81.947176
final  value 81.946993 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.974152 
iter  10 value 94.491778
iter  20 value 94.343850
iter  30 value 91.146251
iter  40 value 84.504067
iter  50 value 84.052674
iter  60 value 83.943492
iter  70 value 83.941496
iter  80 value 83.806512
iter  90 value 81.130529
iter 100 value 79.483024
final  value 79.483024 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.997717 
iter  10 value 94.042214
iter  20 value 94.039562
iter  30 value 94.032595
iter  40 value 94.032230
iter  50 value 94.031734
final  value 94.031296 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.668619 
iter  10 value 94.492415
iter  20 value 94.448048
iter  30 value 90.794034
iter  40 value 84.873312
iter  50 value 83.462997
iter  60 value 82.552864
iter  70 value 81.385289
iter  80 value 79.731209
iter  90 value 79.228889
iter 100 value 79.201536
final  value 79.201536 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.420312 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.808597 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.237205 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.244167 
iter  10 value 93.861027
final  value 93.860355 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.890467 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.918588 
iter  10 value 93.836073
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.226185 
final  value 94.052874 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.094533 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.978746 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.348874 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.877681 
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.552274 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.934649 
iter  10 value 88.237116
iter  20 value 85.969460
iter  30 value 85.873446
iter  40 value 85.852396
final  value 85.852310 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.905644 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.336614 
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.232147 
iter  10 value 92.951014
iter  20 value 86.020932
iter  30 value 85.242654
iter  40 value 84.585555
iter  50 value 84.344626
iter  60 value 84.151231
iter  70 value 84.079852
iter  80 value 84.061258
iter  80 value 84.061258
iter  80 value 84.061258
final  value 84.061258 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.947458 
iter  10 value 94.043293
iter  20 value 90.501590
iter  30 value 86.487814
iter  40 value 85.096993
iter  50 value 84.671298
iter  60 value 84.593325
iter  70 value 84.507621
iter  80 value 84.446100
iter  90 value 84.441427
final  value 84.441399 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.419076 
iter  10 value 94.056797
iter  20 value 93.894240
iter  30 value 93.891300
iter  40 value 93.646433
iter  50 value 91.234593
iter  60 value 90.101196
iter  70 value 87.919361
iter  80 value 85.636813
iter  90 value 84.886702
iter 100 value 84.483326
final  value 84.483326 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.375795 
iter  10 value 94.052509
iter  20 value 88.216205
iter  30 value 85.508021
iter  40 value 85.289401
iter  50 value 85.026507
iter  60 value 84.520116
iter  70 value 84.442103
final  value 84.441400 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.691445 
iter  10 value 94.055156
iter  20 value 90.946611
iter  30 value 85.948047
iter  40 value 84.099218
iter  50 value 83.903987
iter  60 value 83.844486
iter  70 value 83.706221
iter  80 value 83.690197
final  value 83.680567 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.907820 
iter  10 value 94.306130
iter  20 value 89.227004
iter  30 value 84.149445
iter  40 value 83.065592
iter  50 value 82.059571
iter  60 value 81.901524
iter  70 value 81.803176
iter  80 value 81.771231
iter  90 value 81.758189
iter 100 value 81.747556
final  value 81.747556 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.327922 
iter  10 value 94.290691
iter  20 value 88.658017
iter  30 value 87.832285
iter  40 value 86.447911
iter  50 value 85.898695
iter  60 value 85.382088
iter  70 value 84.450986
iter  80 value 83.533453
iter  90 value 83.182167
iter 100 value 83.176831
final  value 83.176831 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.221646 
iter  10 value 94.129788
iter  20 value 93.976091
iter  30 value 87.283657
iter  40 value 85.981869
iter  50 value 85.788100
iter  60 value 85.077348
iter  70 value 84.865322
iter  80 value 84.738859
iter  90 value 84.127818
iter 100 value 84.043117
final  value 84.043117 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.033871 
iter  10 value 94.044777
iter  20 value 86.966096
iter  30 value 86.106635
iter  40 value 84.742818
iter  50 value 84.541045
iter  60 value 84.302634
iter  70 value 84.168686
iter  80 value 84.154785
iter  90 value 84.141501
iter 100 value 84.033238
final  value 84.033238 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.857525 
iter  10 value 94.011331
iter  20 value 93.863224
iter  30 value 93.228851
iter  40 value 87.536289
iter  50 value 85.520306
iter  60 value 84.685076
iter  70 value 83.482593
iter  80 value 82.785535
iter  90 value 82.590920
iter 100 value 82.003761
final  value 82.003761 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.209098 
iter  10 value 95.449987
iter  20 value 89.882201
iter  30 value 86.751963
iter  40 value 85.434013
iter  50 value 84.077381
iter  60 value 83.220417
iter  70 value 82.409324
iter  80 value 81.935632
iter  90 value 81.879772
iter 100 value 81.814390
final  value 81.814390 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.819754 
iter  10 value 94.002883
iter  20 value 87.333025
iter  30 value 85.891184
iter  40 value 84.523596
iter  50 value 84.125012
iter  60 value 83.674491
iter  70 value 82.784771
iter  80 value 82.314262
iter  90 value 82.281890
iter 100 value 82.233435
final  value 82.233435 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.345908 
iter  10 value 97.451815
iter  20 value 89.702390
iter  30 value 86.005124
iter  40 value 84.745786
iter  50 value 83.114886
iter  60 value 82.686254
iter  70 value 82.438709
iter  80 value 82.152699
iter  90 value 82.062066
iter 100 value 82.051673
final  value 82.051673 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.521285 
iter  10 value 94.696331
iter  20 value 94.055492
iter  30 value 92.817088
iter  40 value 92.651772
iter  50 value 87.515527
iter  60 value 86.387755
iter  70 value 83.449681
iter  80 value 82.601806
iter  90 value 82.184216
iter 100 value 82.113342
final  value 82.113342 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.946189 
iter  10 value 94.035503
iter  20 value 90.545077
iter  30 value 85.676055
iter  40 value 84.597900
iter  50 value 83.780212
iter  60 value 82.982563
iter  70 value 82.433529
iter  80 value 82.310821
iter  90 value 82.170117
iter 100 value 82.160464
final  value 82.160464 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.487273 
final  value 94.054755 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.273378 
iter  10 value 93.862196
iter  20 value 93.837259
iter  30 value 93.784990
iter  30 value 93.784990
iter  30 value 93.784990
final  value 93.784990 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.818726 
final  value 94.054814 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.801479 
iter  10 value 94.054824
iter  20 value 93.999342
iter  30 value 90.121146
iter  40 value 85.994840
iter  50 value 85.989798
iter  60 value 85.779066
iter  70 value 85.696339
iter  80 value 85.695811
final  value 85.695795 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.305341 
iter  10 value 93.837721
iter  20 value 93.836708
iter  30 value 93.836245
final  value 93.836242 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.662952 
iter  10 value 94.016165
iter  20 value 94.015130
iter  30 value 94.011431
iter  40 value 93.815472
iter  50 value 87.089422
iter  60 value 86.203309
iter  70 value 85.811890
iter  80 value 84.021486
iter  90 value 83.107311
iter 100 value 82.757452
final  value 82.757452 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.248496 
iter  10 value 89.924484
iter  20 value 89.024203
iter  30 value 87.881274
iter  40 value 86.228048
iter  50 value 86.027152
iter  60 value 85.636771
iter  70 value 85.636260
iter  80 value 85.635295
iter  90 value 85.631725
iter 100 value 85.512275
final  value 85.512275 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.773219 
iter  10 value 94.058137
iter  20 value 94.036950
iter  30 value 85.909837
final  value 85.672434 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.088784 
iter  10 value 94.057904
iter  20 value 94.052949
iter  30 value 94.038928
iter  40 value 93.504486
iter  50 value 89.844730
iter  60 value 89.779148
iter  70 value 89.763717
iter  80 value 89.763279
iter  80 value 89.763278
iter  80 value 89.763278
final  value 89.763278 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.934154 
iter  10 value 94.057918
iter  20 value 93.995078
iter  30 value 86.202919
final  value 86.202873 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.664319 
iter  10 value 91.809353
iter  20 value 90.336454
iter  30 value 90.332519
iter  40 value 90.262161
iter  50 value 90.257279
iter  60 value 89.397089
iter  70 value 89.280205
iter  80 value 89.279972
final  value 89.279311 
converged
Fitting Repeat 2 

# weights:  507
initial  value 92.945246 
iter  10 value 89.069357
iter  20 value 87.651495
iter  30 value 87.615023
iter  40 value 87.517333
iter  50 value 86.366878
iter  60 value 84.563230
iter  70 value 82.952737
iter  80 value 82.948790
iter  90 value 82.947956
iter 100 value 82.946285
final  value 82.946285 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.941550 
iter  10 value 94.061598
iter  20 value 93.908280
iter  30 value 93.265806
iter  40 value 89.514568
iter  50 value 88.285116
iter  60 value 88.250386
iter  70 value 88.173885
iter  80 value 87.829507
iter  90 value 87.670124
final  value 87.667200 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.685229 
iter  10 value 88.267387
iter  20 value 84.654242
iter  30 value 84.185551
final  value 84.185310 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.649530 
iter  10 value 94.021251
iter  20 value 94.015611
iter  30 value 94.012368
iter  40 value 90.040103
iter  50 value 88.121426
iter  60 value 87.951006
iter  70 value 86.561649
iter  80 value 86.518795
iter  90 value 86.517189
iter 100 value 84.168816
final  value 84.168816 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 138.667411 
iter  10 value 117.763739
iter  20 value 117.728301
iter  30 value 113.117167
iter  40 value 112.787434
iter  50 value 112.786313
iter  60 value 112.778764
final  value 112.778419 
converged
Fitting Repeat 2 

# weights:  305
initial  value 141.920115 
iter  10 value 117.895008
iter  20 value 117.869437
iter  30 value 117.604630
iter  40 value 117.511541
final  value 117.511389 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.742695 
iter  10 value 117.764347
iter  20 value 117.737611
iter  30 value 116.230649
iter  40 value 108.479041
iter  50 value 106.258454
iter  60 value 106.224114
iter  70 value 106.220718
iter  80 value 106.219414
final  value 106.216898 
converged
Fitting Repeat 4 

# weights:  305
initial  value 119.366651 
iter  10 value 117.894504
iter  20 value 112.407813
iter  30 value 107.645752
iter  40 value 104.262163
iter  50 value 102.503821
iter  60 value 101.285140
iter  70 value 101.221991
iter  80 value 101.219597
final  value 101.217794 
converged
Fitting Repeat 5 

# weights:  305
initial  value 123.534199 
iter  10 value 117.210957
iter  20 value 117.207000
final  value 117.206757 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Apr 12 07:53:22 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 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 42.028   1.702  50.196