##############################################################################
##############################################################################
###
### 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_1.0.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.14-bioc/meat/HPiP.Rcheck’
* using R version 4.1.3 (2022-03-10)
* 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 ‘1.0.0’
* 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     49.134  1.012  50.264
var_imp       46.925  1.109  48.096
FSmethod      45.306  1.153  46.627
pred_ensembel 20.676  0.356  16.014
calculateTC    6.796  0.398   7.202
enrichfindP    0.577  0.044   8.846
* 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-3.14-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/4.1/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 4.1.3 (2022-03-10) -- "One Push-Up"
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 98.049695 
final  value 93.394928 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.317614 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.721031 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.349170 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.643573 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.639386 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.239534 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 129.645738 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.734991 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.586611 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.952028 
iter  10 value 93.394097
iter  20 value 93.340415
final  value 93.340410 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.921345 
iter  10 value 93.394948
final  value 93.394928 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.553710 
iter  10 value 88.044279
iter  20 value 84.885081
iter  30 value 82.544520
iter  40 value 81.966833
final  value 81.966832 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.292088 
iter  10 value 93.701958
iter  20 value 93.386286
iter  30 value 93.371548
final  value 93.371545 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.848591 
iter  10 value 93.561431
iter  20 value 93.371978
final  value 93.371545 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.098807 
iter  10 value 94.488541
iter  20 value 92.761881
iter  30 value 89.877038
iter  40 value 85.827254
iter  50 value 83.461148
iter  60 value 83.130300
iter  70 value 82.639649
iter  80 value 82.513374
final  value 82.512766 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.659663 
iter  10 value 94.489805
iter  20 value 94.486731
iter  30 value 93.695854
iter  40 value 93.677741
iter  50 value 93.321915
iter  60 value 88.308007
iter  70 value 85.065134
iter  80 value 83.742609
iter  90 value 83.078770
iter 100 value 82.895674
final  value 82.895674 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 110.323291 
iter  10 value 94.482377
iter  20 value 92.139423
iter  30 value 91.099625
iter  40 value 90.066909
iter  50 value 81.404932
iter  60 value 80.516888
iter  70 value 80.285173
final  value 80.254187 
converged
Fitting Repeat 4 

# weights:  103
initial  value 120.033804 
iter  10 value 93.235911
iter  20 value 87.083809
iter  30 value 85.886478
iter  40 value 84.667742
iter  50 value 83.819501
iter  60 value 83.718953
iter  70 value 82.914582
final  value 82.894665 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.474992 
iter  10 value 94.485852
iter  20 value 92.342153
iter  30 value 87.479881
iter  40 value 82.850250
iter  50 value 81.630624
iter  60 value 81.423835
iter  70 value 80.467981
iter  80 value 80.254233
final  value 80.254187 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.777986 
iter  10 value 92.972170
iter  20 value 83.037466
iter  30 value 80.175515
iter  40 value 79.004106
iter  50 value 78.064348
iter  60 value 77.292715
iter  70 value 77.209603
iter  80 value 77.134484
iter  90 value 77.117922
iter 100 value 77.116500
final  value 77.116500 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.400456 
iter  10 value 93.628240
iter  20 value 85.564532
iter  30 value 85.271053
iter  40 value 84.013686
iter  50 value 79.223174
iter  60 value 78.972566
iter  70 value 78.907330
iter  80 value 78.295525
iter  90 value 77.997758
iter 100 value 77.891934
final  value 77.891934 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.124297 
iter  10 value 94.050547
iter  20 value 91.870993
iter  30 value 88.402289
iter  40 value 85.772488
iter  50 value 80.831880
iter  60 value 78.738442
iter  70 value 78.591583
iter  80 value 78.550849
iter  90 value 78.529891
iter 100 value 78.527176
final  value 78.527176 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.907737 
iter  10 value 95.247113
iter  20 value 94.252737
iter  30 value 92.128955
iter  40 value 87.209841
iter  50 value 87.107312
iter  60 value 86.306910
iter  70 value 82.363746
iter  80 value 80.871616
iter  90 value 79.234371
iter 100 value 78.690638
final  value 78.690638 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 126.352736 
iter  10 value 94.555405
iter  20 value 93.919849
iter  30 value 93.609767
iter  40 value 92.710846
iter  50 value 82.712012
iter  60 value 82.277514
iter  70 value 81.824679
iter  80 value 81.145538
iter  90 value 81.078003
iter 100 value 80.963480
final  value 80.963480 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.654523 
iter  10 value 93.990099
iter  20 value 86.327504
iter  30 value 83.154390
iter  40 value 81.104407
iter  50 value 79.406719
iter  60 value 79.005120
iter  70 value 78.365506
iter  80 value 78.346038
iter  90 value 78.284687
iter 100 value 78.272854
final  value 78.272854 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.774006 
iter  10 value 93.739890
iter  20 value 93.599466
iter  30 value 89.547640
iter  40 value 85.105327
iter  50 value 84.487973
iter  60 value 83.088089
iter  70 value 81.513570
iter  80 value 80.262605
iter  90 value 80.069606
iter 100 value 79.902308
final  value 79.902308 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.024498 
iter  10 value 94.396195
iter  20 value 87.961087
iter  30 value 85.621390
iter  40 value 81.097906
iter  50 value 79.685643
iter  60 value 78.716476
iter  70 value 78.600446
iter  80 value 78.516096
iter  90 value 78.442499
iter 100 value 78.101963
final  value 78.101963 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.878009 
iter  10 value 94.894299
iter  20 value 94.276020
iter  30 value 86.486845
iter  40 value 85.276105
iter  50 value 83.208172
iter  60 value 79.282890
iter  70 value 78.006179
iter  80 value 77.895360
iter  90 value 77.866017
iter 100 value 77.848599
final  value 77.848599 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.970931 
iter  10 value 96.646295
iter  20 value 96.485511
iter  30 value 88.042870
iter  40 value 82.741382
iter  50 value 81.849448
iter  60 value 79.802745
iter  70 value 79.149102
iter  80 value 78.922748
iter  90 value 78.748352
iter 100 value 78.324115
final  value 78.324115 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.131243 
final  value 94.485881 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.446445 
final  value 94.485939 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.755221 
final  value 94.485769 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.482897 
final  value 94.485656 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.883415 
iter  10 value 94.485720
final  value 94.484281 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.991349 
iter  10 value 87.429647
iter  20 value 81.986222
iter  30 value 81.881617
iter  40 value 81.880705
iter  50 value 81.880059
iter  60 value 81.515546
iter  70 value 78.381550
iter  80 value 78.095863
iter  90 value 78.079919
iter 100 value 78.078978
final  value 78.078978 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.889211 
iter  10 value 94.489155
iter  20 value 94.484280
iter  30 value 93.932523
iter  40 value 85.187556
iter  50 value 84.597900
iter  60 value 83.424400
iter  70 value 82.514432
iter  80 value 80.686354
iter  90 value 80.651315
iter 100 value 80.598244
final  value 80.598244 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.048630 
iter  10 value 94.488568
final  value 94.484228 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.884443 
iter  10 value 93.400593
iter  20 value 93.397421
iter  30 value 93.394401
final  value 93.394225 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.805112 
iter  10 value 93.400178
iter  20 value 93.345633
iter  30 value 93.343047
iter  40 value 92.097543
iter  50 value 91.364741
iter  60 value 91.354929
iter  70 value 91.354110
iter  80 value 91.351946
final  value 91.351944 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.048480 
iter  10 value 94.492667
iter  20 value 94.444104
iter  30 value 93.395660
final  value 93.395653 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.472317 
iter  10 value 93.543035
iter  20 value 93.539732
iter  30 value 93.341217
final  value 93.341095 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.117647 
iter  10 value 93.755549
iter  20 value 85.054029
iter  30 value 83.496520
iter  40 value 83.474025
final  value 83.473906 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.301248 
iter  10 value 94.492288
iter  20 value 94.485309
iter  30 value 93.472545
iter  40 value 93.397181
iter  40 value 93.397180
iter  40 value 93.397180
final  value 93.397180 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.221883 
iter  10 value 94.451225
iter  20 value 94.129305
iter  30 value 93.311735
iter  40 value 93.129588
final  value 93.010154 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.361147 
iter  10 value 92.088953
final  value 92.088889 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.940629 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.152506 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.513312 
final  value 93.701657 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.144295 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.029001 
iter  10 value 94.252911
iter  20 value 94.026501
iter  30 value 89.964372
iter  40 value 89.795818
iter  50 value 89.787551
iter  60 value 89.671407
iter  60 value 89.671407
iter  60 value 89.671407
final  value 89.671407 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.114731 
final  value 93.701657 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.363159 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 121.014891 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.677169 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.975784 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.449574 
iter  10 value 94.121210
iter  20 value 91.509222
iter  30 value 87.201207
iter  40 value 83.437065
iter  50 value 83.364811
iter  60 value 81.485704
iter  70 value 80.752673
iter  80 value 80.535817
iter  90 value 80.532233
final  value 80.532215 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.122723 
iter  10 value 93.288347
iter  20 value 93.264624
final  value 93.264615 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.043326 
iter  10 value 93.554163
iter  20 value 93.550659
iter  30 value 93.544404
final  value 93.544373 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.228939 
iter  10 value 94.275367
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 115.047118 
iter  10 value 94.466516
iter  20 value 87.646943
iter  30 value 86.219870
iter  40 value 83.834682
iter  50 value 83.333399
iter  60 value 82.488148
iter  70 value 82.223299
iter  80 value 81.872628
iter  90 value 81.839632
iter 100 value 81.832709
final  value 81.832709 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.367330 
iter  10 value 94.501468
iter  20 value 94.147609
iter  30 value 90.970685
iter  40 value 90.670082
iter  50 value 90.660658
final  value 90.660629 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.508745 
iter  10 value 94.489554
iter  20 value 93.892551
iter  30 value 93.814576
iter  40 value 93.696536
iter  50 value 90.517261
iter  60 value 85.099942
iter  70 value 85.006584
iter  80 value 83.491725
iter  90 value 83.102891
iter 100 value 81.913874
final  value 81.913874 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.057257 
iter  10 value 94.283128
iter  20 value 93.751648
iter  30 value 93.698267
iter  40 value 90.435579
iter  50 value 87.215716
iter  60 value 87.060168
iter  70 value 85.996896
iter  80 value 84.014807
iter  90 value 83.696799
iter 100 value 83.692041
final  value 83.692041 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.452939 
iter  10 value 88.935618
iter  20 value 84.687425
iter  30 value 83.726542
iter  40 value 83.385786
iter  50 value 83.274311
final  value 83.272555 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.256646 
iter  10 value 94.491426
iter  20 value 93.120091
iter  30 value 85.345941
iter  40 value 83.688851
iter  50 value 83.290454
iter  60 value 81.997108
iter  70 value 81.432185
iter  80 value 81.073442
iter  90 value 80.683539
iter 100 value 80.335529
final  value 80.335529 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.216769 
iter  10 value 94.466000
iter  20 value 90.631952
iter  30 value 86.407834
iter  40 value 84.565610
iter  50 value 83.938091
iter  60 value 83.689582
iter  70 value 83.314446
iter  80 value 82.341896
iter  90 value 81.626212
iter 100 value 80.955418
final  value 80.955418 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 136.118886 
iter  10 value 94.267107
iter  20 value 89.045794
iter  30 value 84.070683
iter  40 value 83.750842
iter  50 value 83.323017
iter  60 value 83.258694
iter  70 value 83.240738
iter  80 value 83.193594
iter  90 value 83.059150
iter 100 value 82.269381
final  value 82.269381 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.320426 
iter  10 value 94.469111
iter  20 value 88.013170
iter  30 value 86.357613
iter  40 value 84.554922
iter  50 value 83.788511
iter  60 value 83.748018
iter  70 value 83.505418
iter  80 value 82.284062
iter  90 value 81.894945
iter 100 value 81.422635
final  value 81.422635 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.457978 
iter  10 value 94.455604
iter  20 value 91.968309
iter  30 value 91.280186
iter  40 value 90.533833
iter  50 value 88.823317
iter  60 value 85.866854
iter  70 value 84.645297
iter  80 value 83.995915
iter  90 value 82.198076
iter 100 value 81.657720
final  value 81.657720 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.393301 
iter  10 value 94.524214
iter  20 value 86.454884
iter  30 value 84.631799
iter  40 value 83.589487
iter  50 value 83.284485
iter  60 value 82.742211
iter  70 value 82.196571
iter  80 value 81.792694
iter  90 value 81.425508
iter 100 value 80.857960
final  value 80.857960 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.060805 
iter  10 value 94.631824
iter  20 value 87.031286
iter  30 value 86.414317
iter  40 value 85.942855
iter  50 value 82.489922
iter  60 value 81.493866
iter  70 value 80.626216
iter  80 value 80.254803
iter  90 value 80.173501
iter 100 value 80.049406
final  value 80.049406 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.992690 
iter  10 value 94.578736
iter  20 value 93.906586
iter  30 value 93.306002
iter  40 value 87.571696
iter  50 value 87.312564
iter  60 value 86.983561
iter  70 value 85.887354
iter  80 value 83.981165
iter  90 value 83.040980
iter 100 value 82.415583
final  value 82.415583 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.619381 
iter  10 value 94.491099
iter  20 value 90.344002
iter  30 value 85.526546
iter  40 value 84.720157
iter  50 value 82.245922
iter  60 value 81.789366
iter  70 value 81.525485
iter  80 value 81.192717
iter  90 value 80.795229
iter 100 value 80.665167
final  value 80.665167 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.204423 
iter  10 value 94.466163
iter  20 value 92.140036
iter  30 value 84.146851
iter  40 value 83.252737
iter  50 value 82.861497
iter  60 value 82.188321
iter  70 value 81.850092
iter  80 value 81.145318
iter  90 value 80.500091
iter 100 value 80.177498
final  value 80.177498 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.841486 
final  value 94.485774 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.831229 
final  value 94.486105 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.131790 
iter  10 value 87.702698
iter  20 value 87.622384
iter  30 value 87.017018
iter  40 value 86.959339
iter  50 value 86.897617
iter  60 value 86.334161
iter  70 value 86.322262
final  value 86.309475 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.332710 
final  value 94.485711 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.978328 
final  value 94.485967 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.716310 
iter  10 value 93.706989
iter  20 value 85.746163
iter  30 value 83.028610
final  value 83.028598 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.518009 
iter  10 value 93.706428
iter  20 value 88.097221
iter  30 value 86.321367
iter  40 value 86.310174
iter  50 value 86.309859
final  value 86.309775 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.945388 
iter  10 value 94.489375
iter  20 value 94.484408
iter  30 value 93.691280
final  value 93.691279 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.116034 
iter  10 value 94.489055
iter  20 value 87.835417
iter  30 value 86.920731
iter  40 value 86.374275
iter  50 value 86.345376
iter  60 value 86.271208
iter  70 value 85.573598
iter  80 value 85.502026
iter  90 value 85.437340
iter 100 value 85.147975
final  value 85.147975 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 131.603614 
iter  10 value 94.489982
iter  20 value 94.485448
final  value 94.485441 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.084575 
iter  10 value 93.639517
iter  20 value 93.499049
iter  30 value 93.498459
iter  40 value 93.485803
iter  50 value 91.311280
iter  60 value 90.070621
iter  70 value 89.923332
iter  80 value 86.936269
iter  90 value 84.114879
iter 100 value 81.762397
final  value 81.762397 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.011025 
iter  10 value 86.272162
iter  20 value 86.251831
iter  30 value 86.250258
iter  40 value 86.148137
iter  50 value 86.142987
iter  60 value 85.456728
iter  70 value 85.298565
iter  80 value 85.298188
iter  90 value 85.016128
iter 100 value 83.105948
final  value 83.105948 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 137.004644 
iter  10 value 94.286308
iter  20 value 91.313137
iter  30 value 82.399088
iter  40 value 82.260458
iter  50 value 82.165869
iter  60 value 82.054643
iter  70 value 81.986885
iter  80 value 81.971760
iter  90 value 81.953746
iter 100 value 81.953103
final  value 81.953103 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.157738 
iter  10 value 88.727558
iter  20 value 88.718910
iter  30 value 86.187518
iter  40 value 84.693078
iter  50 value 82.915702
iter  60 value 81.710464
iter  70 value 81.535283
iter  80 value 81.478777
iter  90 value 80.972173
iter 100 value 80.650751
final  value 80.650751 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.270918 
iter  10 value 94.492422
iter  20 value 94.445500
iter  30 value 86.136496
iter  40 value 82.933488
iter  50 value 82.826575
iter  60 value 82.822523
iter  70 value 82.802519
final  value 82.801706 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.842163 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.035769 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.586710 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.504982 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.424600 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.107745 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.459454 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.789866 
iter  10 value 93.592761
iter  20 value 93.165079
final  value 93.164741 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.515847 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.180276 
iter  10 value 93.366128
iter  20 value 92.794746
iter  30 value 92.757627
final  value 92.757313 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.168810 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.084404 
iter  10 value 92.893511
final  value 92.892737 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.912741 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.736728 
final  value 92.864740 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.846265 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.568274 
iter  10 value 94.056506
iter  20 value 93.802776
iter  30 value 88.091905
iter  40 value 85.675629
iter  50 value 80.918305
iter  60 value 80.400694
iter  70 value 80.204752
final  value 80.202200 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.966194 
iter  10 value 92.681037
iter  20 value 85.672313
iter  30 value 84.977821
iter  40 value 82.541734
iter  50 value 80.247522
iter  60 value 80.211315
iter  70 value 80.203819
iter  80 value 80.202709
final  value 80.202200 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.281770 
iter  10 value 94.027704
iter  20 value 91.408812
iter  30 value 87.075316
iter  40 value 84.572264
iter  50 value 83.565967
iter  60 value 82.968756
iter  70 value 82.167538
iter  80 value 82.081818
final  value 82.081786 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.527526 
iter  10 value 94.056760
iter  20 value 93.615675
iter  30 value 88.521745
iter  40 value 84.345944
iter  50 value 83.314121
iter  60 value 81.589814
iter  70 value 80.293072
iter  80 value 80.126104
iter  90 value 80.073440
iter 100 value 79.888775
final  value 79.888775 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 95.844476 
iter  10 value 94.059248
iter  20 value 93.897110
iter  30 value 89.464186
iter  40 value 88.877630
iter  50 value 84.915588
iter  60 value 82.628214
iter  70 value 82.072969
iter  80 value 81.895986
iter  90 value 81.745919
iter 100 value 81.741296
final  value 81.741296 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.018908 
iter  10 value 94.253653
iter  20 value 92.557405
iter  30 value 88.456088
iter  40 value 83.755150
iter  50 value 81.445801
iter  60 value 80.761509
iter  70 value 79.548076
iter  80 value 79.393950
iter  90 value 79.306184
iter 100 value 78.991756
final  value 78.991756 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.636781 
iter  10 value 84.822624
iter  20 value 82.328173
iter  30 value 81.405131
iter  40 value 80.504652
iter  50 value 79.961257
iter  60 value 79.856249
iter  70 value 79.243425
iter  80 value 78.714722
iter  90 value 78.472882
iter 100 value 78.199874
final  value 78.199874 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.790909 
iter  10 value 94.110953
iter  20 value 83.972862
iter  30 value 82.518689
iter  40 value 81.897916
iter  50 value 81.312301
iter  60 value 80.129789
iter  70 value 80.066735
iter  80 value 79.460161
iter  90 value 78.505576
iter 100 value 78.082408
final  value 78.082408 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.786752 
iter  10 value 94.098515
iter  20 value 84.634898
iter  30 value 82.834803
iter  40 value 82.042651
iter  50 value 81.208888
iter  60 value 80.746427
iter  70 value 79.688795
iter  80 value 79.130014
iter  90 value 78.379092
iter 100 value 78.138312
final  value 78.138312 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.346691 
iter  10 value 94.084183
iter  20 value 93.798212
iter  30 value 86.717584
iter  40 value 86.276023
iter  50 value 85.481182
iter  60 value 85.042465
iter  70 value 83.903092
iter  80 value 81.119723
iter  90 value 80.743805
iter 100 value 80.475449
final  value 80.475449 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.566902 
iter  10 value 92.704861
iter  20 value 88.689561
iter  30 value 85.381582
iter  40 value 84.814958
iter  50 value 80.919166
iter  60 value 80.476458
iter  70 value 79.976850
iter  80 value 79.821061
iter  90 value 79.779187
iter 100 value 79.767087
final  value 79.767087 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.738910 
iter  10 value 94.568944
iter  20 value 89.964442
iter  30 value 82.478175
iter  40 value 81.644695
iter  50 value 80.977948
iter  60 value 80.496925
iter  70 value 80.418872
iter  80 value 80.343323
iter  90 value 79.114847
iter 100 value 78.579662
final  value 78.579662 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.657242 
iter  10 value 94.270311
iter  20 value 91.339989
iter  30 value 83.733880
iter  40 value 81.198800
iter  50 value 78.380731
iter  60 value 77.892291
iter  70 value 77.694472
iter  80 value 77.608133
iter  90 value 77.531871
iter 100 value 77.480504
final  value 77.480504 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.422027 
iter  10 value 94.162623
iter  20 value 92.020385
iter  30 value 82.469331
iter  40 value 80.836321
iter  50 value 79.761648
iter  60 value 78.904968
iter  70 value 78.705277
iter  80 value 78.561451
iter  90 value 78.497384
iter 100 value 78.200343
final  value 78.200343 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.158750 
iter  10 value 93.922156
iter  20 value 90.140486
iter  30 value 86.744778
iter  40 value 81.557795
iter  50 value 79.364201
iter  60 value 78.979799
iter  70 value 78.153821
iter  80 value 77.805033
iter  90 value 77.645485
iter 100 value 77.570641
final  value 77.570641 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.976132 
final  value 94.054741 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.332627 
final  value 94.054619 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.471340 
final  value 94.054403 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.074912 
final  value 94.054393 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.662009 
final  value 94.040037 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.558915 
iter  10 value 94.057769
iter  20 value 94.031537
iter  30 value 84.384044
iter  40 value 82.032566
iter  50 value 80.569948
iter  60 value 80.473777
iter  70 value 80.469054
final  value 80.469049 
converged
Fitting Repeat 2 

# weights:  305
initial  value 126.138011 
iter  10 value 94.058002
iter  20 value 94.053311
final  value 94.038307 
converged
Fitting Repeat 3 

# weights:  305
initial  value 117.733771 
iter  10 value 94.058252
iter  20 value 94.027047
iter  30 value 90.665152
iter  40 value 84.249810
iter  50 value 84.214956
iter  60 value 84.212807
iter  70 value 84.210088
iter  80 value 81.599072
iter  90 value 80.850813
iter 100 value 80.847323
final  value 80.847323 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.609998 
iter  10 value 94.057708
final  value 94.052928 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.634586 
iter  10 value 94.058062
iter  20 value 94.053206
iter  30 value 90.736430
iter  40 value 90.668212
iter  50 value 84.690560
iter  60 value 83.909336
final  value 83.909274 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.229108 
iter  10 value 93.979408
iter  20 value 93.870417
iter  30 value 93.865786
iter  40 value 90.577382
iter  50 value 84.666002
iter  60 value 84.660906
iter  70 value 84.658389
iter  80 value 84.656730
final  value 84.656641 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.693711 
iter  10 value 93.173145
iter  20 value 92.873621
iter  30 value 92.869634
iter  40 value 86.201588
iter  50 value 81.341863
iter  60 value 81.232794
final  value 81.232674 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.766827 
iter  10 value 94.046746
iter  20 value 94.046230
iter  30 value 92.938325
iter  40 value 85.243440
iter  50 value 85.232798
iter  60 value 85.210019
iter  70 value 82.237073
iter  80 value 82.236432
iter  90 value 80.987833
iter 100 value 80.069895
final  value 80.069895 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.770384 
iter  10 value 94.060730
iter  20 value 93.967766
iter  30 value 84.303147
iter  40 value 80.561746
iter  50 value 79.246210
iter  60 value 79.220642
iter  70 value 79.220222
final  value 79.218476 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.582070 
iter  10 value 94.046046
iter  20 value 82.206847
iter  30 value 82.073504
iter  40 value 82.066890
iter  50 value 81.142172
iter  60 value 79.072915
iter  70 value 78.813886
iter  80 value 78.341312
iter  90 value 77.380387
iter 100 value 76.926245
final  value 76.926245 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.216339 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 116.537122 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.882809 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.953525 
iter  10 value 93.474338
final  value 93.473918 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.929020 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.187863 
final  value 94.038252 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.276393 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.362852 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.849219 
iter  10 value 93.093560
iter  20 value 92.831473
iter  30 value 92.830052
iter  40 value 92.829819
iter  50 value 92.764553
final  value 92.763916 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.684527 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.085855 
iter  10 value 94.613334
final  value 91.944444 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.324104 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.963327 
iter  10 value 94.038010
iter  10 value 94.038009
iter  10 value 94.038009
final  value 94.038009 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.499611 
final  value 94.038009 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.149816 
iter  10 value 94.044348
final  value 94.038251 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.954295 
iter  10 value 94.056967
iter  20 value 94.056364
iter  30 value 93.912436
iter  40 value 87.578678
iter  50 value 87.236258
iter  60 value 86.752443
iter  70 value 86.006372
iter  80 value 85.405673
final  value 85.395052 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.857140 
iter  10 value 93.943641
iter  20 value 88.941051
iter  30 value 86.806058
iter  40 value 85.793591
iter  50 value 85.593837
iter  60 value 85.591445
iter  60 value 85.591445
iter  60 value 85.591445
final  value 85.591445 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.858506 
iter  10 value 94.066856
iter  20 value 94.055899
iter  30 value 90.282417
iter  40 value 89.114506
iter  50 value 87.353457
iter  60 value 85.835002
iter  70 value 85.773674
iter  80 value 85.631318
iter  90 value 84.566423
iter 100 value 83.628530
final  value 83.628530 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.465388 
iter  10 value 92.699526
iter  20 value 87.238678
iter  30 value 86.252824
iter  40 value 85.928344
iter  50 value 85.898035
iter  60 value 85.684791
iter  70 value 85.402572
iter  80 value 85.291692
iter  90 value 85.236075
iter 100 value 85.212018
final  value 85.212018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.662352 
iter  10 value 93.951026
iter  20 value 88.910551
iter  30 value 87.745226
iter  40 value 86.910998
iter  50 value 86.742469
iter  60 value 86.169998
iter  70 value 85.516120
iter  80 value 84.384552
iter  90 value 83.420137
iter 100 value 83.392947
final  value 83.392947 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.634387 
iter  10 value 93.828231
iter  20 value 87.291533
iter  30 value 87.094801
iter  40 value 86.270077
iter  50 value 85.657121
iter  60 value 84.217428
iter  70 value 83.514027
iter  80 value 83.315543
iter  90 value 82.931979
iter 100 value 82.237653
final  value 82.237653 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.525455 
iter  10 value 94.044547
iter  20 value 87.422451
iter  30 value 87.009471
iter  40 value 86.460009
iter  50 value 86.099861
iter  60 value 85.639259
iter  70 value 83.931701
iter  80 value 82.602470
iter  90 value 82.521957
iter 100 value 82.101147
final  value 82.101147 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.028518 
iter  10 value 94.081669
iter  20 value 93.010390
iter  30 value 89.498429
iter  40 value 85.324799
iter  50 value 84.005885
iter  60 value 83.724868
iter  70 value 83.589128
iter  80 value 83.379379
iter  90 value 83.243936
iter 100 value 82.834053
final  value 82.834053 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.051555 
iter  10 value 94.002201
iter  20 value 89.149305
iter  30 value 87.753249
iter  40 value 87.152723
iter  50 value 86.720379
iter  60 value 86.033248
iter  70 value 85.357822
iter  80 value 85.091932
iter  90 value 84.036823
iter 100 value 83.676997
final  value 83.676997 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.632731 
iter  10 value 93.935572
iter  20 value 90.120692
iter  30 value 87.067798
iter  40 value 84.480219
iter  50 value 83.612892
iter  60 value 83.231958
iter  70 value 83.124458
iter  80 value 82.496194
iter  90 value 82.460366
iter 100 value 82.355864
final  value 82.355864 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.864993 
iter  10 value 94.793238
iter  20 value 92.909960
iter  30 value 91.857711
iter  40 value 90.789021
iter  50 value 89.510651
iter  60 value 88.730927
iter  70 value 88.616011
iter  80 value 88.331798
iter  90 value 84.849302
iter 100 value 83.475503
final  value 83.475503 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.374739 
iter  10 value 94.722079
iter  20 value 87.858082
iter  30 value 86.025204
iter  40 value 85.799391
iter  50 value 85.673727
iter  60 value 85.264470
iter  70 value 84.134721
iter  80 value 83.280730
iter  90 value 82.684072
iter 100 value 82.658597
final  value 82.658597 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.090838 
iter  10 value 94.297322
iter  20 value 88.676142
iter  30 value 86.477393
iter  40 value 84.138893
iter  50 value 83.598825
iter  60 value 83.253312
iter  70 value 82.721033
iter  80 value 82.150376
iter  90 value 81.919035
iter 100 value 81.866238
final  value 81.866238 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.546008 
iter  10 value 95.150536
iter  20 value 93.600587
iter  30 value 91.800339
iter  40 value 88.446811
iter  50 value 85.818862
iter  60 value 85.542055
iter  70 value 84.957787
iter  80 value 84.534946
iter  90 value 83.942187
iter 100 value 83.020876
final  value 83.020876 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.702801 
iter  10 value 95.395471
iter  20 value 94.087147
iter  30 value 94.046020
iter  40 value 92.944719
iter  50 value 86.546967
iter  60 value 85.310246
iter  70 value 85.052607
iter  80 value 84.879483
iter  90 value 84.341517
iter 100 value 84.168342
final  value 84.168342 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.762323 
final  value 94.054533 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.376196 
final  value 94.054764 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.627329 
iter  10 value 94.054669
iter  20 value 89.223969
iter  30 value 88.550040
final  value 88.549202 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.466569 
iter  10 value 93.674899
iter  20 value 93.674356
iter  30 value 91.151171
iter  40 value 84.750524
iter  50 value 83.541911
iter  60 value 83.093770
iter  70 value 82.977105
final  value 82.977080 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.506231 
final  value 94.054249 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.387133 
iter  10 value 94.043001
iter  20 value 94.024740
iter  30 value 89.707782
iter  40 value 85.808124
iter  50 value 83.452504
iter  60 value 82.084960
iter  70 value 81.677939
iter  80 value 81.647729
final  value 81.632905 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.017718 
iter  10 value 91.332841
iter  20 value 88.654117
iter  30 value 88.128876
iter  40 value 88.002389
iter  50 value 87.794517
iter  60 value 87.792118
iter  70 value 87.779815
iter  80 value 87.138313
iter  90 value 85.467686
iter 100 value 84.853934
final  value 84.853934 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.321479 
iter  10 value 94.057673
iter  20 value 94.043428
iter  30 value 93.690908
iter  40 value 88.191801
iter  50 value 87.411799
iter  60 value 85.594325
iter  70 value 84.649867
iter  80 value 84.647117
iter  90 value 84.464325
iter 100 value 84.340266
final  value 84.340266 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.347669 
iter  10 value 94.057331
iter  20 value 94.015284
iter  30 value 88.752956
iter  40 value 88.490065
iter  50 value 88.487736
iter  60 value 88.452174
iter  70 value 88.378284
iter  80 value 88.378063
iter  80 value 88.378063
iter  80 value 88.378063
final  value 88.378063 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.312034 
iter  10 value 94.057258
iter  20 value 94.053025
iter  30 value 94.051532
iter  40 value 90.565671
iter  50 value 87.920097
iter  60 value 86.849859
iter  70 value 86.303832
iter  80 value 85.983173
iter  90 value 85.757499
iter 100 value 85.756855
final  value 85.756855 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.963545 
iter  10 value 94.046039
iter  20 value 94.038657
iter  30 value 93.853603
iter  40 value 91.451782
iter  50 value 85.783480
iter  60 value 85.652364
iter  70 value 84.864042
final  value 84.820580 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.884842 
iter  10 value 94.060296
iter  20 value 94.045381
iter  30 value 91.619021
final  value 91.618862 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.363679 
iter  10 value 93.891955
iter  20 value 93.598436
iter  30 value 93.591047
iter  40 value 93.523312
iter  50 value 93.480876
iter  60 value 93.479710
iter  70 value 92.219899
iter  80 value 88.258971
iter  90 value 88.075154
iter 100 value 88.074118
final  value 88.074118 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.656858 
iter  10 value 94.060714
iter  20 value 92.263828
iter  30 value 87.017582
iter  40 value 86.998046
iter  50 value 86.981689
final  value 86.981461 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.665390 
iter  10 value 94.058182
iter  20 value 93.804973
iter  30 value 90.098344
iter  40 value 89.875342
iter  50 value 89.875042
iter  60 value 88.996204
iter  70 value 87.531950
iter  80 value 85.249615
final  value 85.249348 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.687078 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.707574 
final  value 94.112570 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.740689 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.657380 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.328295 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.155159 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.569203 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.482049 
iter  10 value 94.112775
iter  20 value 93.805428
iter  30 value 93.804881
final  value 93.804879 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.661765 
iter  10 value 94.328618
iter  20 value 94.308198
final  value 94.308193 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.903585 
iter  10 value 94.475592
iter  20 value 93.853295
iter  30 value 93.376203
iter  40 value 93.253185
final  value 93.244978 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.068995 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.642999 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.776969 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.576612 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.117463 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.964045 
iter  10 value 94.419519
iter  20 value 92.696485
iter  30 value 86.873140
iter  40 value 86.605405
iter  50 value 86.332782
iter  60 value 85.486643
iter  70 value 85.391006
iter  80 value 85.227570
iter  90 value 84.949224
iter 100 value 84.936057
final  value 84.936057 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 112.678906 
iter  10 value 94.430645
iter  20 value 93.927815
iter  30 value 93.896682
iter  40 value 93.875538
iter  50 value 91.138110
iter  60 value 87.184793
iter  70 value 86.506152
iter  80 value 85.546385
iter  90 value 85.463068
iter 100 value 85.169120
final  value 85.169120 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.171639 
iter  10 value 94.486298
iter  20 value 94.182197
iter  30 value 94.100201
iter  40 value 93.757046
iter  50 value 91.896531
iter  60 value 91.808399
iter  70 value 90.663031
iter  80 value 85.346058
iter  90 value 84.800957
iter 100 value 84.346920
final  value 84.346920 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 116.150396 
iter  10 value 98.786953
iter  20 value 94.487148
iter  30 value 94.486536
iter  40 value 94.424438
iter  50 value 93.947051
iter  60 value 93.246666
iter  70 value 87.740037
iter  80 value 85.198715
iter  90 value 85.137692
iter 100 value 84.933232
final  value 84.933232 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.021094 
iter  10 value 93.689371
iter  20 value 85.386923
iter  30 value 84.970160
iter  40 value 84.415919
iter  50 value 84.357453
final  value 84.357366 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.061122 
iter  10 value 94.240948
iter  20 value 87.080337
iter  30 value 86.680026
iter  40 value 85.183009
iter  50 value 83.677319
iter  60 value 83.217154
iter  70 value 82.576203
iter  80 value 82.269655
iter  90 value 81.607622
iter 100 value 81.423262
final  value 81.423262 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.132039 
iter  10 value 95.561045
iter  20 value 92.634303
iter  30 value 86.550114
iter  40 value 82.726533
iter  50 value 82.049957
iter  60 value 81.465513
iter  70 value 81.362391
iter  80 value 81.250932
iter  90 value 80.843208
iter 100 value 80.611391
final  value 80.611391 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.429721 
iter  10 value 94.457555
iter  20 value 87.324087
iter  30 value 85.434046
iter  40 value 85.100294
iter  50 value 84.321768
iter  60 value 83.267584
iter  70 value 82.155356
iter  80 value 81.418879
iter  90 value 81.203228
iter 100 value 80.561446
final  value 80.561446 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.712207 
iter  10 value 95.266887
iter  20 value 93.465902
iter  30 value 88.936326
iter  40 value 85.421061
iter  50 value 83.879593
iter  60 value 83.300238
iter  70 value 83.136516
iter  80 value 82.982179
iter  90 value 82.863784
iter 100 value 82.620079
final  value 82.620079 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.909646 
iter  10 value 94.461079
iter  20 value 89.513601
iter  30 value 87.205567
iter  40 value 86.555294
iter  50 value 86.393950
iter  60 value 86.304249
iter  70 value 86.250143
iter  80 value 84.394356
iter  90 value 82.791511
iter 100 value 82.603960
final  value 82.603960 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.238682 
iter  10 value 94.727475
iter  20 value 91.621586
iter  30 value 86.615660
iter  40 value 84.673349
iter  50 value 83.484886
iter  60 value 82.476148
iter  70 value 81.766581
iter  80 value 81.491164
iter  90 value 81.205507
iter 100 value 80.625279
final  value 80.625279 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.791557 
iter  10 value 94.485076
iter  20 value 89.871748
iter  30 value 87.843741
iter  40 value 84.529114
iter  50 value 83.240658
iter  60 value 81.701270
iter  70 value 81.374406
iter  80 value 81.021770
iter  90 value 80.982195
iter 100 value 80.932015
final  value 80.932015 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.092086 
iter  10 value 91.562785
iter  20 value 85.684444
iter  30 value 85.206401
iter  40 value 84.679505
iter  50 value 82.939684
iter  60 value 81.577384
iter  70 value 81.241292
iter  80 value 81.126596
iter  90 value 81.022595
iter 100 value 80.905926
final  value 80.905926 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.762544 
iter  10 value 94.707225
iter  20 value 92.553163
iter  30 value 87.731154
iter  40 value 85.892901
iter  50 value 83.683174
iter  60 value 83.089112
iter  70 value 82.213200
iter  80 value 81.380628
iter  90 value 81.076320
iter 100 value 80.952259
final  value 80.952259 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.829523 
iter  10 value 95.559372
iter  20 value 94.294909
iter  30 value 93.724958
iter  40 value 86.965749
iter  50 value 85.713275
iter  60 value 84.937062
iter  70 value 82.689574
iter  80 value 82.193794
iter  90 value 81.609717
iter 100 value 81.112058
final  value 81.112058 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.586323 
final  value 94.486032 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.911124 
final  value 94.485904 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.740730 
final  value 94.485573 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.564136 
final  value 94.485997 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.776085 
iter  10 value 86.545837
iter  20 value 86.311846
iter  30 value 86.203212
iter  40 value 85.230610
final  value 85.223080 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.680816 
iter  10 value 94.486254
iter  20 value 93.934007
iter  30 value 85.508611
iter  40 value 85.461867
iter  50 value 84.429297
iter  60 value 84.381253
iter  70 value 84.352652
final  value 84.350373 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.737893 
iter  10 value 94.358791
iter  20 value 93.845753
iter  30 value 90.997278
final  value 90.993470 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.646056 
iter  10 value 94.488910
iter  20 value 93.986923
iter  30 value 88.004766
iter  40 value 84.461766
iter  50 value 84.017988
iter  60 value 83.966014
iter  70 value 83.955577
iter  80 value 83.955470
iter  90 value 83.955332
iter 100 value 83.955220
final  value 83.955220 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.150587 
iter  10 value 94.491689
iter  20 value 94.486694
iter  30 value 94.321881
iter  40 value 93.510710
iter  50 value 93.504526
final  value 93.496687 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.855998 
iter  10 value 94.489215
iter  20 value 94.484266
iter  30 value 94.354553
final  value 94.354443 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.365168 
iter  10 value 94.362789
iter  20 value 94.358025
iter  30 value 90.329979
iter  40 value 86.295408
iter  50 value 86.287426
iter  60 value 86.112352
iter  70 value 84.995826
iter  80 value 83.398039
iter  90 value 81.891684
iter 100 value 81.306082
final  value 81.306082 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.935893 
iter  10 value 94.362746
iter  20 value 94.357936
iter  30 value 94.199766
iter  40 value 85.122834
iter  50 value 84.246472
iter  60 value 84.134006
iter  70 value 84.133882
final  value 84.133353 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.419125 
iter  10 value 94.363596
iter  20 value 94.360509
iter  30 value 94.359874
iter  40 value 91.847588
iter  50 value 87.060380
iter  60 value 86.795081
iter  70 value 86.774590
iter  80 value 86.015747
iter  90 value 85.781688
iter 100 value 85.580306
final  value 85.580306 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.265800 
iter  10 value 94.365917
iter  20 value 94.361121
iter  30 value 94.360028
iter  40 value 94.356988
iter  50 value 94.356333
iter  60 value 94.355621
iter  70 value 94.353902
iter  80 value 93.811258
iter  90 value 93.805400
iter 100 value 93.804047
final  value 93.804047 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.433897 
iter  10 value 94.491099
iter  20 value 94.107768
iter  30 value 83.695796
iter  40 value 82.644152
iter  50 value 82.435846
final  value 82.435570 
converged
Fitting Repeat 1 

# weights:  507
initial  value 148.096614 
iter  10 value 118.448029
iter  20 value 116.588413
iter  30 value 111.605757
iter  40 value 109.291386
iter  50 value 108.262096
iter  60 value 105.160841
iter  70 value 104.924356
iter  80 value 104.758860
iter  90 value 103.495890
iter 100 value 102.242558
final  value 102.242558 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 137.212873 
iter  10 value 117.994905
iter  20 value 107.216880
iter  30 value 105.974944
iter  40 value 105.789203
iter  50 value 103.637376
iter  60 value 103.143854
iter  70 value 102.701145
iter  80 value 102.131509
iter  90 value 101.451408
iter 100 value 100.916157
final  value 100.916157 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.570581 
iter  10 value 118.996430
iter  20 value 112.292282
iter  30 value 106.594487
iter  40 value 105.823384
iter  50 value 103.281108
iter  60 value 102.746846
iter  70 value 102.423963
iter  80 value 101.799174
iter  90 value 101.132829
iter 100 value 100.651855
final  value 100.651855 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.267900 
iter  10 value 118.430656
iter  20 value 112.286632
iter  30 value 108.627610
iter  40 value 107.957178
iter  50 value 106.899675
iter  60 value 103.992848
iter  70 value 101.534431
iter  80 value 101.350305
iter  90 value 101.043569
iter 100 value 100.831069
final  value 100.831069 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.785625 
iter  10 value 117.870469
iter  20 value 117.241482
iter  30 value 114.040013
iter  40 value 110.322306
iter  50 value 105.761746
iter  60 value 104.387973
iter  70 value 103.706308
iter  80 value 102.186380
iter  90 value 101.250332
iter 100 value 101.070522
final  value 101.070522 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Apr 12 14:26:13 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 
 60.466   1.559  57.101