##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.2.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.15-bioc/meat/HPiP.Rcheck’
* using R version 4.2.1 (2022-06-23)
* using platform: x86_64-apple-darwin17.0 (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 ‘1.2.0’
* 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
var_imp       51.677  0.937  52.804
corr_plot     49.880  0.931  50.965
FSmethod      49.185  1.027  50.310
pred_ensembel 22.232  0.373  17.514
enrichfindP    0.710  0.037  11.454
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.15-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.2/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.2.1 (2022-06-23) -- "Funny-Looking Kid"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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 96.329364 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.546918 
iter  10 value 89.881583
iter  20 value 88.896936
iter  30 value 88.893590
iter  40 value 88.893442
final  value 88.893434 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.750559 
final  value 94.484208 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.690059 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.922404 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.613340 
iter  10 value 94.252933
final  value 94.252920 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.033557 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.680756 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.893356 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.497184 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.862802 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.553363 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.396119 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.793428 
iter  10 value 93.684898
iter  20 value 93.332482
final  value 93.332475 
converged
Fitting Repeat 5 

# weights:  507
initial  value 125.051046 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.254748 
iter  10 value 94.488410
iter  20 value 93.688300
iter  30 value 93.634191
iter  40 value 93.619512
iter  50 value 90.960046
iter  60 value 85.279659
iter  70 value 85.104541
iter  80 value 84.562172
iter  90 value 84.390087
iter 100 value 84.388159
final  value 84.388159 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.806550 
iter  10 value 93.913022
iter  20 value 85.614214
iter  30 value 84.969050
iter  40 value 84.580709
iter  50 value 84.385873
iter  60 value 84.378601
final  value 84.378594 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.579666 
iter  10 value 94.522853
iter  20 value 93.110669
iter  30 value 89.030891
iter  40 value 87.584012
iter  50 value 87.373993
iter  60 value 85.224821
iter  70 value 85.095360
iter  80 value 84.606163
iter  90 value 84.384358
iter 100 value 84.378598
final  value 84.378598 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.535370 
iter  10 value 94.484855
iter  20 value 93.726878
iter  30 value 92.714490
iter  40 value 85.768861
iter  50 value 83.812710
iter  60 value 83.431295
iter  70 value 83.162152
iter  80 value 82.831719
iter  90 value 82.594173
iter 100 value 82.390819
final  value 82.390819 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.367284 
iter  10 value 94.486495
iter  20 value 93.655040
iter  30 value 93.620416
iter  40 value 92.216019
iter  50 value 86.413037
iter  60 value 85.723208
iter  70 value 85.509466
iter  80 value 85.164822
iter  90 value 83.029281
iter 100 value 82.095062
final  value 82.095062 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.731288 
iter  10 value 94.490593
iter  20 value 93.926898
iter  30 value 86.654121
iter  40 value 85.533097
iter  50 value 85.010682
iter  60 value 84.710888
iter  70 value 83.980736
iter  80 value 82.113917
iter  90 value 81.672867
iter 100 value 81.548069
final  value 81.548069 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.437300 
iter  10 value 94.534313
iter  20 value 93.536969
iter  30 value 91.526568
iter  40 value 88.717485
iter  50 value 85.362109
iter  60 value 83.259016
iter  70 value 82.124924
iter  80 value 80.936509
iter  90 value 80.886242
iter 100 value 80.548405
final  value 80.548405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.247259 
iter  10 value 94.022366
iter  20 value 85.302143
iter  30 value 84.658336
iter  40 value 84.293962
iter  50 value 84.153992
iter  60 value 84.107812
iter  70 value 83.199798
iter  80 value 81.343664
iter  90 value 81.109684
iter 100 value 81.077225
final  value 81.077225 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.011112 
iter  10 value 94.493242
iter  20 value 93.661862
iter  30 value 90.415164
iter  40 value 85.266866
iter  50 value 83.924252
iter  60 value 83.170183
iter  70 value 82.428690
iter  80 value 80.940519
iter  90 value 80.525283
iter 100 value 80.327908
final  value 80.327908 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.774692 
iter  10 value 96.651382
iter  20 value 93.462021
iter  30 value 85.264895
iter  40 value 84.943260
iter  50 value 84.708892
iter  60 value 83.569943
iter  70 value 82.879538
iter  80 value 82.366548
iter  90 value 81.876450
iter 100 value 81.296402
final  value 81.296402 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 154.518920 
iter  10 value 95.152664
iter  20 value 89.429683
iter  30 value 87.302372
iter  40 value 86.337995
iter  50 value 84.588109
iter  60 value 83.525647
iter  70 value 82.177941
iter  80 value 81.543368
iter  90 value 81.134944
iter 100 value 80.903699
final  value 80.903699 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.344101 
iter  10 value 93.300012
iter  20 value 88.154324
iter  30 value 86.050450
iter  40 value 83.103947
iter  50 value 82.083501
iter  60 value 81.765230
iter  70 value 81.501034
iter  80 value 81.074910
iter  90 value 80.947138
iter 100 value 80.918526
final  value 80.918526 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.393138 
iter  10 value 94.720386
iter  20 value 94.384272
iter  30 value 87.286988
iter  40 value 86.532591
iter  50 value 85.628268
iter  60 value 83.210572
iter  70 value 82.181389
iter  80 value 81.882753
iter  90 value 81.743998
iter 100 value 81.713610
final  value 81.713610 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.703712 
iter  10 value 94.560223
iter  20 value 88.422356
iter  30 value 86.215727
iter  40 value 85.104736
iter  50 value 84.291349
iter  60 value 83.179853
iter  70 value 80.924177
iter  80 value 80.418543
iter  90 value 80.346880
iter 100 value 80.310836
final  value 80.310836 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.140125 
iter  10 value 94.433372
iter  20 value 92.333908
iter  30 value 86.426511
iter  40 value 85.167937
iter  50 value 84.415844
iter  60 value 83.351798
iter  70 value 83.009350
iter  80 value 82.843312
iter  90 value 82.546109
iter 100 value 82.284620
final  value 82.284620 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.809211 
final  value 94.485535 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.035817 
final  value 94.485652 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.192790 
iter  10 value 94.485605
iter  20 value 94.482513
final  value 94.354435 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.356725 
iter  10 value 94.486019
iter  20 value 94.386783
iter  30 value 93.517391
final  value 93.517172 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.635489 
final  value 94.485700 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.952129 
iter  10 value 94.257212
iter  20 value 93.593072
iter  30 value 93.558692
iter  40 value 93.489413
final  value 93.489394 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.931859 
iter  10 value 94.488898
iter  20 value 94.157874
iter  30 value 93.574413
iter  40 value 93.559015
final  value 93.558651 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.183227 
iter  10 value 94.257843
iter  20 value 94.108808
iter  30 value 94.105593
iter  40 value 87.938997
iter  50 value 85.234388
iter  60 value 82.206476
iter  70 value 81.575234
iter  80 value 81.458918
iter  90 value 80.883497
iter 100 value 80.220276
final  value 80.220276 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.408854 
iter  10 value 93.563340
iter  20 value 93.536956
final  value 93.522275 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.576236 
iter  10 value 94.488593
iter  20 value 94.484273
iter  30 value 93.676602
iter  40 value 90.475507
iter  50 value 88.218904
iter  60 value 88.217392
iter  70 value 88.088933
iter  80 value 86.603438
iter  90 value 86.598175
iter 100 value 86.596048
final  value 86.596048 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.405899 
iter  10 value 94.362683
iter  20 value 90.678704
iter  30 value 86.396420
iter  40 value 83.954183
iter  50 value 83.217153
iter  60 value 82.959992
iter  70 value 82.932765
iter  80 value 82.900583
iter  90 value 82.897484
iter 100 value 82.895018
final  value 82.895018 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.014489 
iter  10 value 94.485845
iter  20 value 93.735114
final  value 93.558574 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.602538 
iter  10 value 94.491797
iter  20 value 94.425001
iter  30 value 93.558451
iter  40 value 93.450758
iter  50 value 93.333144
iter  50 value 93.333143
iter  50 value 93.333143
final  value 93.333143 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.791377 
iter  10 value 93.269113
iter  20 value 87.573942
iter  30 value 84.537944
iter  40 value 83.771968
iter  50 value 82.252739
iter  60 value 82.019657
iter  70 value 81.593276
iter  80 value 81.592171
iter  90 value 81.583226
final  value 81.583205 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.665153 
iter  10 value 93.787751
iter  20 value 93.728037
iter  30 value 93.721163
iter  40 value 93.570751
iter  50 value 84.451852
iter  60 value 83.006871
iter  70 value 82.954929
iter  80 value 82.954712
iter  90 value 82.954379
iter  90 value 82.954379
final  value 82.954379 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.620070 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.585344 
iter  10 value 93.672993
final  value 93.672973 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.651316 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.507414 
iter  10 value 93.369483
final  value 93.276243 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.252233 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.587803 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.501994 
iter  10 value 93.296874
iter  20 value 93.276257
final  value 93.276243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.019535 
iter  10 value 93.385167
final  value 93.346723 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.812780 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.540944 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.695993 
iter  10 value 93.672705
final  value 93.672553 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.748192 
iter  10 value 93.299022
iter  20 value 93.276390
final  value 93.276243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.958269 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.942655 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.523612 
final  value 92.211112 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.894884 
iter  10 value 94.052639
iter  20 value 88.469919
iter  30 value 81.614643
iter  40 value 81.351848
iter  50 value 81.081782
iter  60 value 80.726948
iter  70 value 80.664926
iter  80 value 80.650935
final  value 80.650931 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.153065 
iter  10 value 94.055078
iter  20 value 90.505020
iter  30 value 82.667697
iter  40 value 82.265989
iter  50 value 81.006005
iter  60 value 80.715832
iter  70 value 80.674521
iter  80 value 80.650932
final  value 80.650931 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.510685 
iter  10 value 94.056526
iter  20 value 93.632880
iter  30 value 86.847403
iter  40 value 84.033675
iter  50 value 83.663851
iter  60 value 82.707772
iter  70 value 81.045314
iter  80 value 80.724183
iter  90 value 80.651054
final  value 80.650931 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.880236 
iter  10 value 93.455544
iter  20 value 89.324530
iter  30 value 83.019730
iter  40 value 81.217098
iter  50 value 81.036615
iter  60 value 80.833872
iter  70 value 80.668469
iter  80 value 80.650934
final  value 80.650932 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.343853 
iter  10 value 94.056925
iter  20 value 88.420014
iter  30 value 84.879968
iter  40 value 82.994404
iter  50 value 82.445976
iter  60 value 82.073903
iter  70 value 79.222717
iter  80 value 78.554918
iter  90 value 78.346947
iter 100 value 77.980350
final  value 77.980350 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.606126 
iter  10 value 94.528675
iter  20 value 82.820675
iter  30 value 82.015077
iter  40 value 81.079737
iter  50 value 80.356883
iter  60 value 80.331506
iter  70 value 80.225866
iter  80 value 80.088357
iter  90 value 79.184107
iter 100 value 78.802875
final  value 78.802875 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.815731 
iter  10 value 93.817261
iter  20 value 92.636496
iter  30 value 83.687605
iter  40 value 82.463327
iter  50 value 80.935076
iter  60 value 80.693609
iter  70 value 80.612573
iter  80 value 80.488466
iter  90 value 80.338828
iter 100 value 80.255687
final  value 80.255687 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.331288 
iter  10 value 94.231112
iter  20 value 92.636163
iter  30 value 83.067608
iter  40 value 81.245426
iter  50 value 80.754570
iter  60 value 80.656097
iter  70 value 79.032514
iter  80 value 77.298360
iter  90 value 76.861935
iter 100 value 76.759316
final  value 76.759316 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.540730 
iter  10 value 94.725820
iter  20 value 92.865624
iter  30 value 85.668265
iter  40 value 84.843385
iter  50 value 84.039649
iter  60 value 82.210151
iter  70 value 78.293971
iter  80 value 76.913276
iter  90 value 76.621972
iter 100 value 76.551056
final  value 76.551056 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.188652 
iter  10 value 94.047403
iter  20 value 92.702850
iter  30 value 92.056011
iter  40 value 89.535307
iter  50 value 78.569343
iter  60 value 77.719788
iter  70 value 77.476833
iter  80 value 77.405141
iter  90 value 77.334004
iter 100 value 77.034877
final  value 77.034877 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.819788 
iter  10 value 94.455644
iter  20 value 92.275944
iter  30 value 91.136162
iter  40 value 90.861447
iter  50 value 90.744949
iter  60 value 88.279536
iter  70 value 80.630023
iter  80 value 79.799257
iter  90 value 79.254422
iter 100 value 78.547001
final  value 78.547001 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.188113 
iter  10 value 95.576094
iter  20 value 85.366448
iter  30 value 79.249035
iter  40 value 77.942839
iter  50 value 77.198181
iter  60 value 76.682694
iter  70 value 76.546170
iter  80 value 76.261740
iter  90 value 76.195751
iter 100 value 76.037709
final  value 76.037709 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.067465 
iter  10 value 93.996294
iter  20 value 87.769542
iter  30 value 81.987638
iter  40 value 79.943566
iter  50 value 77.236344
iter  60 value 76.806879
iter  70 value 76.438545
iter  80 value 76.280999
iter  90 value 76.070623
iter 100 value 75.960272
final  value 75.960272 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.238865 
iter  10 value 94.170389
iter  20 value 91.710835
iter  30 value 90.130151
iter  40 value 85.025927
iter  50 value 81.175785
iter  60 value 80.475474
iter  70 value 79.989116
iter  80 value 78.964557
iter  90 value 77.257900
iter 100 value 76.618299
final  value 76.618299 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.185143 
iter  10 value 92.346102
iter  20 value 81.838508
iter  30 value 81.603324
iter  40 value 80.334147
iter  50 value 79.773102
iter  60 value 79.744286
iter  70 value 79.561839
iter  80 value 78.757543
iter  90 value 78.092878
iter 100 value 77.491632
final  value 77.491632 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 112.534786 
final  value 94.054652 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.050254 
final  value 94.054371 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.645202 
final  value 94.054279 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.669469 
iter  10 value 93.674970
iter  20 value 93.673296
iter  30 value 93.650813
iter  40 value 92.393365
iter  50 value 86.170911
iter  60 value 84.021218
iter  70 value 83.998776
iter  80 value 83.995835
iter  90 value 83.995387
iter 100 value 83.994407
final  value 83.994407 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 94.179917 
final  value 94.054360 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.305395 
iter  10 value 93.678015
iter  20 value 93.451947
iter  30 value 84.321331
iter  40 value 83.845417
iter  50 value 83.759105
iter  60 value 83.753393
iter  70 value 82.198914
iter  80 value 81.214345
iter  90 value 79.083830
iter 100 value 78.816485
final  value 78.816485 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.818030 
iter  10 value 94.057705
iter  20 value 94.052932
final  value 94.052914 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.040913 
iter  10 value 94.043601
iter  20 value 84.414560
iter  30 value 83.967877
iter  40 value 82.612067
iter  50 value 82.159115
iter  60 value 79.837160
iter  70 value 79.541973
final  value 79.536274 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.088160 
iter  10 value 94.057613
iter  20 value 93.877332
iter  30 value 84.428312
iter  40 value 84.391157
iter  50 value 81.151215
iter  60 value 81.149460
final  value 81.149319 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.311992 
iter  10 value 93.678465
iter  20 value 93.677074
iter  30 value 82.965702
iter  40 value 79.512415
iter  50 value 77.157139
iter  60 value 76.561919
iter  70 value 76.521389
iter  80 value 76.457893
iter  90 value 76.456925
iter 100 value 75.469502
final  value 75.469502 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.476974 
iter  10 value 93.953194
iter  20 value 93.681196
iter  30 value 93.284635
iter  40 value 93.282729
iter  50 value 92.821774
iter  60 value 87.195106
iter  70 value 81.394630
iter  80 value 81.283491
iter  90 value 78.865278
iter 100 value 77.500537
final  value 77.500537 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.884105 
iter  10 value 93.681019
iter  20 value 93.674226
iter  30 value 93.275164
iter  40 value 93.245481
iter  50 value 79.775802
iter  60 value 79.327079
iter  70 value 79.283151
final  value 79.283135 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.185479 
iter  10 value 93.680690
iter  20 value 93.674895
final  value 93.674460 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.166998 
iter  10 value 94.060619
iter  20 value 93.922846
iter  30 value 86.050325
iter  40 value 82.160081
iter  50 value 82.158977
iter  60 value 82.017078
iter  70 value 81.803921
iter  80 value 81.798095
iter  90 value 81.797452
iter 100 value 80.453247
final  value 80.453247 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.915195 
iter  10 value 84.296517
iter  20 value 84.088072
iter  30 value 84.084976
iter  40 value 84.083358
iter  50 value 82.105060
iter  60 value 81.432575
iter  70 value 81.355401
iter  80 value 80.737318
iter  90 value 79.017004
iter 100 value 76.124371
final  value 76.124371 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.506993 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.039630 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.673650 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.287496 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.747606 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.908997 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.559274 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.382955 
final  value 94.482932 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.541354 
iter  10 value 94.325662
iter  20 value 94.252982
final  value 94.252921 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.149890 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.269336 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.120361 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.296435 
iter  10 value 92.069355
final  value 92.068571 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.369048 
final  value 94.322897 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.955356 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.930882 
iter  10 value 94.528212
iter  20 value 94.476785
iter  30 value 86.784464
iter  40 value 85.248622
iter  50 value 84.350304
iter  60 value 84.155440
iter  70 value 84.005571
iter  80 value 83.988084
final  value 83.988065 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.416154 
iter  10 value 94.404362
iter  20 value 86.769360
iter  30 value 86.316653
iter  40 value 85.030646
iter  50 value 84.563315
iter  60 value 84.494731
iter  70 value 84.419298
iter  80 value 84.405216
final  value 84.405135 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.279621 
iter  10 value 94.488045
iter  20 value 92.969718
iter  30 value 88.885184
iter  40 value 88.235209
iter  50 value 88.199704
iter  60 value 88.056421
iter  70 value 87.825265
iter  80 value 87.722475
iter  90 value 85.708176
iter 100 value 85.472177
final  value 85.472177 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.009800 
iter  10 value 94.439042
iter  20 value 94.087148
iter  30 value 92.746525
iter  40 value 85.668831
iter  50 value 84.835229
iter  60 value 84.438683
iter  70 value 84.407331
final  value 84.405135 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.121568 
iter  10 value 95.466158
iter  20 value 94.471536
iter  30 value 93.087973
iter  40 value 92.680360
iter  50 value 90.976609
iter  60 value 90.937375
final  value 90.937372 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.833056 
iter  10 value 94.409330
iter  20 value 90.870389
iter  30 value 85.283052
iter  40 value 83.186303
iter  50 value 81.509871
iter  60 value 81.166950
iter  70 value 80.311988
iter  80 value 79.894351
iter  90 value 79.790198
iter 100 value 79.758620
final  value 79.758620 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.689691 
iter  10 value 94.792244
iter  20 value 90.447718
iter  30 value 88.139884
iter  40 value 86.334212
iter  50 value 85.044189
iter  60 value 84.577898
iter  70 value 84.368431
iter  80 value 84.188535
iter  90 value 83.924548
iter 100 value 82.529106
final  value 82.529106 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.089417 
iter  10 value 94.413349
iter  20 value 93.149572
iter  30 value 84.578165
iter  40 value 83.767259
iter  50 value 82.576479
iter  60 value 81.704032
iter  70 value 81.627633
iter  80 value 81.208126
iter  90 value 80.924030
iter 100 value 80.521253
final  value 80.521253 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.888973 
iter  10 value 94.533240
iter  20 value 94.326016
iter  30 value 93.812443
iter  40 value 84.874338
iter  50 value 83.477306
iter  60 value 81.271530
iter  70 value 81.060764
iter  80 value 80.697789
iter  90 value 80.498334
iter 100 value 80.365904
final  value 80.365904 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 122.767166 
iter  10 value 94.511654
iter  20 value 93.190625
iter  30 value 86.064631
iter  40 value 84.026940
iter  50 value 82.091638
iter  60 value 81.663165
iter  70 value 81.523177
iter  80 value 81.401063
iter  90 value 80.912824
iter 100 value 80.520108
final  value 80.520108 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.004709 
iter  10 value 94.510213
iter  20 value 87.850815
iter  30 value 86.098526
iter  40 value 85.534099
iter  50 value 83.371482
iter  60 value 82.750392
iter  70 value 82.043099
iter  80 value 81.422586
iter  90 value 80.940943
iter 100 value 80.125888
final  value 80.125888 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.321795 
iter  10 value 94.536684
iter  20 value 88.813685
iter  30 value 87.807903
iter  40 value 87.487966
iter  50 value 84.041041
iter  60 value 82.917734
iter  70 value 82.619257
iter  80 value 81.504731
iter  90 value 80.543613
iter 100 value 79.929490
final  value 79.929490 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.487062 
iter  10 value 94.766479
iter  20 value 94.340025
iter  30 value 86.863505
iter  40 value 84.756013
iter  50 value 84.356754
iter  60 value 84.304791
iter  70 value 84.075738
iter  80 value 83.824511
iter  90 value 82.847898
iter 100 value 82.317937
final  value 82.317937 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.316851 
iter  10 value 94.602248
iter  20 value 94.192962
iter  30 value 93.816696
iter  40 value 85.483871
iter  50 value 84.542927
iter  60 value 84.097863
iter  70 value 83.922552
iter  80 value 83.685264
iter  90 value 82.155324
iter 100 value 81.255314
final  value 81.255314 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.559829 
iter  10 value 94.704958
iter  20 value 91.775936
iter  30 value 88.137645
iter  40 value 85.424155
iter  50 value 82.188997
iter  60 value 80.683674
iter  70 value 80.068282
iter  80 value 79.646625
iter  90 value 79.573351
iter 100 value 79.528964
final  value 79.528964 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.554510 
iter  10 value 92.781247
iter  20 value 92.605133
iter  30 value 92.604646
iter  30 value 92.604646
iter  30 value 92.604646
final  value 92.604646 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.624649 
final  value 94.485508 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.865229 
final  value 94.485706 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.347162 
final  value 94.485730 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.609568 
final  value 94.486041 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.176370 
iter  10 value 94.103078
iter  20 value 94.101152
final  value 94.100837 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.555757 
iter  10 value 94.489297
iter  20 value 94.484433
iter  30 value 94.127100
iter  40 value 94.113208
iter  50 value 94.112175
iter  60 value 91.569665
iter  70 value 90.322190
iter  80 value 90.318308
iter  90 value 90.245580
iter 100 value 90.241256
final  value 90.241256 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.925370 
iter  10 value 94.489120
iter  20 value 94.420381
iter  30 value 85.001669
iter  40 value 83.410682
iter  50 value 82.801117
iter  60 value 82.276583
iter  70 value 82.268559
iter  70 value 82.268558
final  value 82.268558 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.676524 
iter  10 value 94.488630
iter  20 value 94.483733
iter  30 value 85.920144
final  value 85.706908 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.204036 
iter  10 value 94.488641
iter  20 value 94.395112
iter  30 value 86.004407
iter  40 value 85.596697
final  value 85.592634 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.754582 
iter  10 value 94.261034
iter  20 value 94.080580
iter  30 value 90.941781
iter  40 value 90.594924
final  value 90.566664 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.041346 
iter  10 value 94.313924
iter  20 value 94.311473
iter  30 value 94.099736
iter  40 value 93.531214
iter  50 value 91.786788
iter  60 value 91.616638
iter  70 value 91.615496
final  value 91.615483 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.723870 
iter  10 value 94.451307
iter  20 value 94.392268
iter  30 value 85.721910
iter  40 value 85.710140
iter  50 value 85.653506
iter  60 value 84.508035
final  value 84.501656 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.658170 
iter  10 value 91.024492
iter  20 value 86.829057
iter  30 value 86.798491
iter  40 value 86.216353
iter  50 value 86.079990
iter  60 value 86.077649
iter  70 value 86.074888
iter  80 value 80.223178
iter  90 value 79.801379
iter 100 value 79.302486
final  value 79.302486 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.686736 
iter  10 value 94.362495
iter  20 value 94.354655
iter  30 value 87.963756
iter  40 value 85.813464
iter  50 value 85.622275
iter  60 value 85.619219
final  value 85.619096 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.474794 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 115.448556 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.759701 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.858835 
iter  10 value 94.029287
iter  20 value 93.963572
final  value 93.963388 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.673187 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.023211 
final  value 94.305882 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.938834 
iter  10 value 94.442072
iter  10 value 94.442072
iter  10 value 94.442072
final  value 94.442072 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.798937 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.390321 
iter  10 value 89.044531
iter  20 value 87.027178
iter  30 value 85.718076
iter  40 value 85.695389
final  value 85.695387 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.276410 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.836193 
iter  10 value 86.867644
iter  20 value 85.696608
iter  30 value 85.695366
final  value 85.695035 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.479372 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.984421 
iter  10 value 92.275878
iter  20 value 83.989202
iter  30 value 83.669339
final  value 83.669318 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.854812 
final  value 94.461539 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.360783 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.892527 
iter  10 value 94.449857
iter  20 value 88.103323
iter  30 value 85.454375
iter  40 value 85.072391
iter  50 value 85.030276
iter  60 value 83.939294
iter  70 value 83.806133
iter  80 value 83.076124
iter  90 value 82.837430
iter 100 value 82.820333
final  value 82.820333 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.098451 
iter  10 value 94.357236
iter  20 value 89.382374
iter  30 value 88.193135
iter  40 value 86.550241
iter  50 value 86.322915
iter  60 value 86.314948
iter  70 value 86.314618
iter  70 value 86.314617
iter  70 value 86.314617
final  value 86.314617 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.155529 
iter  10 value 94.503474
iter  20 value 92.887447
iter  30 value 91.513044
iter  40 value 91.329348
iter  50 value 87.145832
iter  60 value 86.770201
iter  70 value 85.593447
iter  80 value 85.499603
iter  90 value 85.450466
final  value 85.450437 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.680797 
iter  10 value 94.476693
iter  20 value 89.928361
iter  30 value 88.272304
iter  40 value 86.629622
iter  50 value 85.755223
iter  60 value 85.065342
iter  70 value 84.530010
iter  80 value 84.340528
iter  90 value 84.329869
iter 100 value 84.231115
final  value 84.231115 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 110.990546 
iter  10 value 94.287150
iter  20 value 88.349116
iter  30 value 86.734974
iter  40 value 86.456368
iter  50 value 86.315445
final  value 86.314617 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.507631 
iter  10 value 96.230011
iter  20 value 94.647458
iter  30 value 94.327747
iter  40 value 88.622304
iter  50 value 87.896782
iter  60 value 85.982322
iter  70 value 85.562767
iter  80 value 85.462943
iter  90 value 85.450326
iter 100 value 85.423823
final  value 85.423823 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.117206 
iter  10 value 98.906118
iter  20 value 91.329492
iter  30 value 87.787164
iter  40 value 84.600362
iter  50 value 83.197925
iter  60 value 82.799091
iter  70 value 82.661038
iter  80 value 82.037937
iter  90 value 81.758006
iter 100 value 81.756273
final  value 81.756273 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.581806 
iter  10 value 94.613625
iter  20 value 89.670175
iter  30 value 86.849918
iter  40 value 85.647144
iter  50 value 84.410663
iter  60 value 83.961754
iter  70 value 83.211252
iter  80 value 82.636959
iter  90 value 82.521124
iter 100 value 82.449971
final  value 82.449971 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.058607 
iter  10 value 94.993586
iter  20 value 91.740561
iter  30 value 87.115174
iter  40 value 85.188449
iter  50 value 84.989748
iter  60 value 84.868912
iter  70 value 84.465220
iter  80 value 84.337199
iter  90 value 83.997142
iter 100 value 82.636330
final  value 82.636330 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.409851 
iter  10 value 94.501021
iter  20 value 94.093453
iter  30 value 90.961594
iter  40 value 89.175233
iter  50 value 87.475770
iter  60 value 86.099869
iter  70 value 85.516743
iter  80 value 85.276906
iter  90 value 85.097480
iter 100 value 85.012413
final  value 85.012413 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.159231 
iter  10 value 95.590817
iter  20 value 89.828902
iter  30 value 86.088018
iter  40 value 83.892404
iter  50 value 83.349537
iter  60 value 83.183108
iter  70 value 82.884500
iter  80 value 82.328339
iter  90 value 81.904443
iter 100 value 81.709214
final  value 81.709214 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.286431 
iter  10 value 98.489470
iter  20 value 88.950837
iter  30 value 87.403586
iter  40 value 84.643943
iter  50 value 84.347172
iter  60 value 83.724174
iter  70 value 82.777245
iter  80 value 81.974117
iter  90 value 81.720554
iter 100 value 81.654699
final  value 81.654699 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.674391 
iter  10 value 94.502412
iter  20 value 92.539696
iter  30 value 88.731146
iter  40 value 86.970151
iter  50 value 86.170327
iter  60 value 85.081323
iter  70 value 83.159225
iter  80 value 82.587033
iter  90 value 82.106686
iter 100 value 81.624478
final  value 81.624478 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.636150 
iter  10 value 93.619295
iter  20 value 88.616024
iter  30 value 85.478978
iter  40 value 85.000225
iter  50 value 83.616563
iter  60 value 83.318873
iter  70 value 83.011217
iter  80 value 82.776802
iter  90 value 82.231450
iter 100 value 82.011473
final  value 82.011473 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.794529 
iter  10 value 94.395749
iter  20 value 86.610071
iter  30 value 84.391799
iter  40 value 83.634685
iter  50 value 83.296030
iter  60 value 83.050107
iter  70 value 82.976217
iter  80 value 82.320456
iter  90 value 82.076413
iter 100 value 81.962779
final  value 81.962779 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.479469 
final  value 94.485735 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.214173 
iter  10 value 94.468490
iter  20 value 94.466918
final  value 94.466844 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.521733 
iter  10 value 94.486195
final  value 94.484280 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.670645 
final  value 94.485848 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.232535 
final  value 94.486019 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.716285 
iter  10 value 94.471561
iter  20 value 93.973616
iter  30 value 90.839666
iter  40 value 89.836006
iter  50 value 87.830878
iter  60 value 87.754626
iter  70 value 87.742673
iter  80 value 87.466922
iter  90 value 87.137584
iter 100 value 85.217413
final  value 85.217413 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.034967 
iter  10 value 94.489232
iter  20 value 94.479206
iter  30 value 94.308661
iter  40 value 94.288525
iter  50 value 93.947617
iter  60 value 89.919400
iter  70 value 88.435429
iter  80 value 88.308874
iter  90 value 88.308795
iter 100 value 88.190097
final  value 88.190097 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.655278 
iter  10 value 94.499065
iter  20 value 94.470938
iter  30 value 94.466905
iter  40 value 91.832342
iter  50 value 89.437570
iter  60 value 89.221815
iter  70 value 85.208348
iter  80 value 84.828371
iter  90 value 84.828147
iter 100 value 84.823558
final  value 84.823558 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.941561 
iter  10 value 94.488925
iter  20 value 94.443676
iter  30 value 91.790321
iter  40 value 89.392004
iter  50 value 88.221126
iter  60 value 87.732100
iter  70 value 87.714693
iter  80 value 87.697346
iter  90 value 87.685754
iter 100 value 87.680229
final  value 87.680229 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 135.575098 
iter  10 value 94.473221
iter  20 value 94.342330
iter  30 value 94.307934
iter  40 value 94.302495
final  value 94.288373 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.153033 
iter  10 value 94.492044
iter  20 value 94.413616
iter  30 value 87.684643
iter  40 value 87.611597
iter  50 value 85.046451
iter  60 value 83.920714
iter  70 value 83.302867
iter  80 value 83.300310
iter  90 value 83.162152
iter 100 value 82.667182
final  value 82.667182 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.879710 
iter  10 value 94.413805
iter  20 value 93.773492
iter  30 value 87.894314
iter  40 value 87.852570
iter  50 value 87.849973
iter  60 value 87.758193
iter  70 value 87.747027
iter  80 value 87.745448
iter  90 value 84.415873
iter 100 value 82.586844
final  value 82.586844 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.290666 
iter  10 value 94.225975
iter  20 value 94.221306
iter  30 value 94.218228
iter  40 value 94.059676
iter  50 value 94.054165
final  value 94.054109 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.181439 
iter  10 value 94.474216
iter  20 value 94.198921
iter  30 value 89.467504
iter  40 value 89.142700
iter  50 value 87.821386
iter  60 value 83.222723
iter  70 value 82.583049
iter  80 value 82.404655
iter  90 value 81.831510
iter 100 value 80.516667
final  value 80.516667 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.015020 
iter  10 value 94.463301
iter  20 value 93.716419
iter  30 value 93.494195
iter  40 value 93.173877
iter  50 value 93.067793
iter  60 value 93.059546
final  value 93.059499 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.555331 
final  value 94.005848 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.475921 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.473649 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.560174 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.847496 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.129824 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.244438 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.700286 
iter  10 value 93.288778
iter  20 value 93.212951
iter  20 value 93.212951
iter  20 value 93.212951
final  value 93.212951 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.023514 
final  value 93.671508 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.853196 
final  value 94.005848 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.821747 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.080085 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 125.647809 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 140.273138 
iter  10 value 93.915748
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.405147 
iter  10 value 91.526283
iter  20 value 89.284036
final  value 89.283951 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.818077 
iter  10 value 93.944072
iter  20 value 91.774759
iter  30 value 84.732287
iter  40 value 84.236560
iter  50 value 84.145060
iter  60 value 83.608633
iter  70 value 82.946530
iter  80 value 82.888150
final  value 82.888032 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.634882 
iter  10 value 94.054515
iter  20 value 90.957276
iter  30 value 87.732136
iter  40 value 83.352006
iter  50 value 83.186641
iter  60 value 83.039345
iter  70 value 82.925166
iter  80 value 82.803417
iter  90 value 82.772600
final  value 82.772598 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.418455 
iter  10 value 92.820952
iter  20 value 85.484088
iter  30 value 84.192746
iter  40 value 83.508639
iter  50 value 82.908879
iter  60 value 82.887518
iter  70 value 82.801046
final  value 82.786318 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.695119 
iter  10 value 94.054945
iter  20 value 93.983850
iter  30 value 89.271779
iter  40 value 85.665223
iter  50 value 85.143489
iter  60 value 84.616153
iter  70 value 84.216492
iter  80 value 83.961801
final  value 83.954178 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.316912 
iter  10 value 93.811042
iter  20 value 91.455622
iter  30 value 90.614952
iter  40 value 90.560097
iter  50 value 90.452504
final  value 90.451400 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.947476 
iter  10 value 94.280949
iter  20 value 94.081842
iter  30 value 91.237867
iter  40 value 87.494671
iter  50 value 87.231639
iter  60 value 86.860390
iter  70 value 86.123338
iter  80 value 82.447355
iter  90 value 82.078896
iter 100 value 81.853844
final  value 81.853844 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.117383 
iter  10 value 93.638540
iter  20 value 84.995664
iter  30 value 82.315437
iter  40 value 81.961567
iter  50 value 81.762340
iter  60 value 81.591808
iter  70 value 81.362547
iter  80 value 81.358793
iter  90 value 81.331890
iter 100 value 81.275026
final  value 81.275026 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.626400 
iter  10 value 94.304828
iter  20 value 86.900305
iter  30 value 85.815004
iter  40 value 84.538483
iter  50 value 84.460562
iter  60 value 82.993898
iter  70 value 82.080459
iter  80 value 81.788662
iter  90 value 81.640523
iter 100 value 81.564767
final  value 81.564767 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.095352 
iter  10 value 91.403882
iter  20 value 86.369836
iter  30 value 85.208938
iter  40 value 84.593277
iter  50 value 84.020266
iter  60 value 83.615358
iter  70 value 83.465533
iter  80 value 82.712377
iter  90 value 82.418213
iter 100 value 82.206246
final  value 82.206246 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 138.752032 
iter  10 value 95.309393
iter  20 value 92.556481
iter  30 value 88.329364
iter  40 value 87.898073
iter  50 value 85.680844
iter  60 value 83.279519
iter  70 value 83.024475
iter  80 value 82.408332
iter  90 value 81.607163
iter 100 value 81.339776
final  value 81.339776 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.275668 
iter  10 value 95.155207
iter  20 value 92.567042
iter  30 value 91.969661
iter  40 value 86.432101
iter  50 value 86.007649
iter  60 value 85.135300
iter  70 value 84.935924
iter  80 value 84.859314
iter  90 value 84.667754
iter 100 value 83.337532
final  value 83.337532 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.133350 
iter  10 value 94.163084
iter  20 value 93.009285
iter  30 value 85.113635
iter  40 value 83.016202
iter  50 value 82.266616
iter  60 value 81.452225
iter  70 value 81.317537
iter  80 value 81.117752
iter  90 value 80.957418
iter 100 value 80.887931
final  value 80.887931 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.321359 
iter  10 value 94.443427
iter  20 value 91.481032
iter  30 value 85.947135
iter  40 value 85.096615
iter  50 value 82.896175
iter  60 value 82.584921
iter  70 value 82.438647
iter  80 value 82.344905
iter  90 value 81.731469
iter 100 value 81.376746
final  value 81.376746 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.716200 
iter  10 value 94.626953
iter  20 value 87.273058
iter  30 value 85.463766
iter  40 value 84.024614
iter  50 value 83.886962
iter  60 value 82.622598
iter  70 value 82.201071
iter  80 value 81.953901
iter  90 value 81.838529
iter 100 value 81.532234
final  value 81.532234 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.570637 
iter  10 value 94.352451
iter  20 value 93.413974
iter  30 value 89.673335
iter  40 value 84.303801
iter  50 value 82.835666
iter  60 value 82.012608
iter  70 value 81.784162
iter  80 value 81.597659
iter  90 value 81.333718
iter 100 value 81.149826
final  value 81.149826 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.060376 
final  value 94.054621 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.355002 
final  value 94.054561 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.453947 
iter  10 value 94.054530
iter  20 value 93.793269
iter  30 value 84.860502
iter  40 value 84.857989
iter  50 value 84.844428
iter  60 value 83.918586
iter  60 value 83.918585
iter  70 value 83.658434
iter  80 value 83.595642
final  value 83.595624 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.860506 
iter  10 value 94.054622
iter  20 value 92.016577
iter  30 value 87.796722
iter  40 value 85.297856
iter  50 value 83.919733
iter  60 value 83.919101
iter  70 value 83.917755
iter  80 value 83.916515
final  value 83.916488 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.934628 
iter  10 value 94.054603
iter  20 value 93.760574
iter  30 value 87.689720
iter  40 value 87.671181
iter  50 value 87.298171
iter  60 value 87.280370
iter  70 value 87.151221
iter  80 value 87.107437
iter  90 value 86.718241
iter 100 value 86.414909
final  value 86.414909 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.206282 
iter  10 value 94.057605
iter  20 value 93.986395
iter  30 value 86.367161
iter  40 value 84.595986
iter  50 value 84.581244
iter  60 value 84.577905
iter  70 value 84.275530
final  value 84.271273 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.214546 
iter  10 value 94.057163
iter  20 value 94.052938
iter  30 value 86.231706
iter  40 value 86.035225
iter  50 value 85.601119
iter  60 value 84.663702
iter  70 value 84.536993
iter  80 value 84.536519
final  value 84.536517 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.664296 
iter  10 value 90.003123
iter  20 value 85.867542
iter  30 value 85.857707
iter  40 value 85.771334
iter  50 value 85.116512
iter  60 value 85.087260
iter  70 value 85.085773
final  value 85.085645 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.251270 
iter  10 value 86.964056
iter  20 value 85.007812
iter  30 value 83.792843
iter  40 value 83.737894
iter  50 value 83.383537
iter  60 value 83.320499
iter  70 value 83.294834
iter  80 value 83.290168
iter  90 value 83.289754
iter 100 value 83.284979
final  value 83.284979 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.329256 
iter  10 value 94.058243
iter  20 value 94.008733
iter  30 value 92.331078
iter  40 value 88.664698
iter  50 value 88.647158
iter  60 value 88.645136
iter  70 value 88.642345
iter  80 value 87.138459
iter  90 value 87.046261
final  value 87.045543 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.562406 
iter  10 value 94.055273
iter  20 value 85.590570
iter  30 value 84.839056
iter  40 value 83.395995
iter  50 value 82.237371
iter  60 value 81.607646
iter  70 value 81.323883
iter  80 value 81.318168
iter  90 value 81.073895
iter 100 value 80.934461
final  value 80.934461 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.856618 
iter  10 value 93.954931
iter  20 value 93.929127
iter  30 value 93.724238
iter  40 value 93.690453
iter  50 value 93.685914
iter  60 value 92.901646
iter  70 value 89.510471
iter  80 value 83.658675
iter  90 value 82.346440
iter 100 value 81.660167
final  value 81.660167 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.176323 
iter  10 value 93.924167
iter  20 value 90.391505
iter  30 value 85.742025
iter  40 value 85.353193
iter  50 value 82.369921
iter  60 value 82.001458
iter  70 value 81.919412
iter  80 value 81.790746
iter  90 value 81.749942
iter 100 value 81.745646
final  value 81.745646 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.566671 
iter  10 value 94.059300
iter  20 value 94.052945
final  value 94.052900 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.292787 
iter  10 value 93.924416
iter  20 value 93.801313
iter  30 value 91.207777
iter  40 value 88.967920
iter  50 value 85.626743
iter  60 value 85.071352
iter  70 value 85.066255
iter  80 value 83.632046
iter  90 value 83.443743
iter 100 value 83.443431
final  value 83.443431 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 124.041984 
iter  10 value 117.903945
iter  20 value 117.894374
iter  30 value 117.651352
iter  40 value 111.874925
iter  50 value 108.999593
iter  60 value 105.822411
iter  70 value 105.222626
iter  80 value 104.962268
iter  90 value 104.818009
iter 100 value 104.780952
final  value 104.780952 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 121.386797 
iter  10 value 116.308601
iter  20 value 106.647653
iter  30 value 104.794034
iter  40 value 103.619423
iter  50 value 103.495505
iter  60 value 102.602255
iter  70 value 102.344846
iter  80 value 102.325296
final  value 102.325293 
converged
Fitting Repeat 3 

# weights:  103
initial  value 121.727921 
iter  10 value 117.896407
final  value 117.892494 
converged
Fitting Repeat 4 

# weights:  103
initial  value 122.032757 
iter  10 value 117.922309
iter  20 value 117.892578
iter  30 value 113.962199
iter  40 value 106.244318
iter  50 value 105.149693
iter  60 value 103.687207
iter  70 value 103.546371
iter  80 value 103.269845
iter  90 value 102.554914
iter 100 value 102.326334
final  value 102.326334 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 132.974028 
iter  10 value 117.859025
iter  20 value 117.613649
iter  30 value 116.634733
iter  40 value 114.534206
iter  50 value 108.393549
iter  60 value 106.812475
iter  70 value 106.160760
iter  80 value 105.587410
iter  90 value 105.566341
iter  90 value 105.566340
iter  90 value 105.566340
final  value 105.566340 
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 -- Wed Oct 19 03:38:28 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.
ℹ Use `.name_repair = "minimal"`.
ℹ The deprecated feature was likely used in the tibble package.
  Please report the issue at <https://github.com/tidyverse/tibble/issues>. 
2: `repeats` has no meaning for this resampling method. 
3: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 69.774   1.942  71.367