##############################################################################
##############################################################################
###
### 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_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 RC (2024-06-06 r86719)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.5
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* 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 ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code 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 ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* 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       18.490  0.602  19.105
FSmethod      17.844  0.676  18.716
corr_plot     17.194  0.603  17.827
pred_ensembel  6.159  0.478   4.761
enrichfindP    0.161  0.026   9.087
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-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/4.4-arm64/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 4.4.1 RC (2024-06-06 r86719) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 101.798839 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.414445 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.270536 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.878759 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.925325 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.787601 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.668283 
iter  10 value 92.887820
iter  20 value 92.856141
final  value 92.855906 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.765437 
iter  10 value 94.048472
iter  20 value 94.038252
iter  20 value 94.038251
iter  20 value 94.038251
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.071357 
iter  10 value 93.426574
iter  10 value 93.426573
iter  10 value 93.426573
final  value 93.426573 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.573389 
iter  10 value 93.411221
iter  20 value 93.410248
final  value 93.410247 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.679918 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.312212 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.363101 
final  value 93.944596 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.770826 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.661123 
iter  10 value 93.870633
iter  20 value 93.836066
iter  20 value 93.836066
iter  20 value 93.836066
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.298311 
iter  10 value 93.816430
iter  20 value 90.740010
iter  30 value 86.288796
iter  40 value 84.667794
iter  50 value 84.197401
iter  60 value 83.996871
iter  70 value 83.185907
iter  80 value 82.311993
iter  90 value 82.218809
final  value 82.218667 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.661751 
iter  10 value 93.896101
iter  20 value 93.822202
iter  30 value 91.286776
iter  40 value 89.690444
iter  50 value 87.482456
iter  60 value 86.225985
iter  70 value 84.296367
iter  80 value 82.534874
iter  90 value 82.504342
iter 100 value 82.452231
final  value 82.452231 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.164900 
iter  10 value 94.056134
iter  20 value 93.922354
iter  30 value 91.861227
iter  40 value 91.099007
iter  50 value 86.348972
iter  60 value 85.204407
iter  70 value 83.421444
iter  80 value 82.400052
iter  90 value 82.349303
final  value 82.349299 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.520461 
iter  10 value 94.041438
iter  20 value 87.423677
iter  30 value 85.896686
iter  40 value 85.655643
iter  50 value 85.531899
iter  60 value 85.491540
iter  70 value 85.469085
final  value 85.469081 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.974732 
iter  10 value 93.955966
iter  20 value 93.939658
iter  30 value 93.837158
iter  40 value 86.663947
iter  50 value 85.352438
iter  60 value 84.808137
iter  70 value 84.557902
iter  80 value 84.401885
iter  90 value 84.389536
iter 100 value 84.381616
final  value 84.381616 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.513930 
iter  10 value 92.863422
iter  20 value 86.711430
iter  30 value 85.955883
iter  40 value 85.605175
iter  50 value 85.498078
iter  60 value 85.240288
iter  70 value 83.692354
iter  80 value 82.782753
iter  90 value 82.575134
iter 100 value 82.189584
final  value 82.189584 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.469739 
iter  10 value 93.099263
iter  20 value 88.400492
iter  30 value 84.171403
iter  40 value 82.267691
iter  50 value 81.296296
iter  60 value 81.176873
iter  70 value 81.050556
iter  80 value 80.701183
iter  90 value 80.364399
iter 100 value 80.288264
final  value 80.288264 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.645236 
iter  10 value 94.086369
iter  20 value 94.054939
iter  30 value 93.502475
iter  40 value 90.902789
iter  50 value 88.812887
iter  60 value 85.522615
iter  70 value 84.821076
iter  80 value 84.645636
iter  90 value 84.423147
iter 100 value 84.290342
final  value 84.290342 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 127.498298 
iter  10 value 94.063040
iter  20 value 91.323133
iter  30 value 90.737265
iter  40 value 89.090382
iter  50 value 88.445469
iter  60 value 86.755417
iter  70 value 85.491448
iter  80 value 82.595217
iter  90 value 81.743606
iter 100 value 81.270363
final  value 81.270363 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.407144 
iter  10 value 93.900651
iter  20 value 92.702637
iter  30 value 90.753950
iter  40 value 86.056322
iter  50 value 85.022658
iter  60 value 84.367316
iter  70 value 84.096086
iter  80 value 83.657299
iter  90 value 83.272380
iter 100 value 82.315825
final  value 82.315825 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.262311 
iter  10 value 94.019769
iter  20 value 92.882950
iter  30 value 88.545464
iter  40 value 86.662429
iter  50 value 85.577175
iter  60 value 85.103609
iter  70 value 83.092264
iter  80 value 82.760802
iter  90 value 82.315894
iter 100 value 82.281094
final  value 82.281094 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.172226 
iter  10 value 94.133842
iter  20 value 91.088947
iter  30 value 86.419456
iter  40 value 85.494980
iter  50 value 82.976129
iter  60 value 81.725782
iter  70 value 81.546934
iter  80 value 81.452146
iter  90 value 81.245696
iter 100 value 80.635845
final  value 80.635845 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.303448 
iter  10 value 95.484940
iter  20 value 94.012778
iter  30 value 90.438602
iter  40 value 87.831084
iter  50 value 83.398096
iter  60 value 82.744099
iter  70 value 82.030380
iter  80 value 81.370335
iter  90 value 81.237659
iter 100 value 80.846523
final  value 80.846523 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.441704 
iter  10 value 95.473455
iter  20 value 91.450251
iter  30 value 87.038109
iter  40 value 85.760692
iter  50 value 84.993519
iter  60 value 84.349798
iter  70 value 83.633453
iter  80 value 82.097190
iter  90 value 81.662049
iter 100 value 81.522822
final  value 81.522822 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.893341 
iter  10 value 94.049599
iter  20 value 88.499027
iter  30 value 86.434516
iter  40 value 85.988401
iter  50 value 84.637585
iter  60 value 83.553314
iter  70 value 82.652362
iter  80 value 81.954086
iter  90 value 81.633671
iter 100 value 81.527853
final  value 81.527853 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.192988 
final  value 94.054508 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.487301 
iter  10 value 94.054532
iter  20 value 94.052920
final  value 94.052918 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.987627 
iter  10 value 88.652825
iter  20 value 85.864233
iter  30 value 85.861568
iter  40 value 85.745250
iter  50 value 85.518093
iter  60 value 85.515115
iter  70 value 85.514888
iter  80 value 85.514336
iter  90 value 85.513871
final  value 85.513760 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.436826 
final  value 94.054757 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.532129 
iter  10 value 94.060870
iter  20 value 93.895357
final  value 93.803240 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.291671 
iter  10 value 94.057842
iter  20 value 94.052925
final  value 94.052920 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.341560 
iter  10 value 93.671540
iter  20 value 93.482304
iter  30 value 93.478171
iter  40 value 88.695186
iter  50 value 84.233725
iter  60 value 83.904852
iter  70 value 83.410087
iter  80 value 83.409076
iter  90 value 83.289589
iter 100 value 83.260821
final  value 83.260821 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.980522 
iter  10 value 93.841010
iter  20 value 93.836718
iter  30 value 93.356219
iter  40 value 93.192967
final  value 93.192756 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.166999 
iter  10 value 93.841235
iter  20 value 93.833255
iter  30 value 93.791511
iter  40 value 93.780120
iter  50 value 93.779556
iter  50 value 93.779555
iter  50 value 93.779555
final  value 93.779555 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.851279 
iter  10 value 93.841462
iter  20 value 93.840329
iter  30 value 93.251353
iter  40 value 85.454956
iter  50 value 83.874572
iter  60 value 82.519996
iter  70 value 81.431404
iter  80 value 81.273914
iter  90 value 81.265960
iter 100 value 81.251346
final  value 81.251346 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.368949 
iter  10 value 94.041444
iter  20 value 93.849946
iter  30 value 93.838853
iter  40 value 93.787131
iter  50 value 93.775572
iter  60 value 85.382659
iter  70 value 84.665394
iter  80 value 83.994833
iter  90 value 83.147717
iter 100 value 83.139732
final  value 83.139732 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.157650 
iter  10 value 94.061704
iter  20 value 93.910042
iter  30 value 86.744841
iter  40 value 86.407775
iter  50 value 86.384477
iter  60 value 86.383756
final  value 86.382937 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.942783 
iter  10 value 94.061339
iter  20 value 93.964458
iter  30 value 86.983154
iter  40 value 86.382496
iter  50 value 86.238185
final  value 86.236629 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.059830 
iter  10 value 94.060632
iter  20 value 94.025976
iter  30 value 86.601531
iter  40 value 86.043021
iter  50 value 86.041117
iter  60 value 86.036911
iter  70 value 85.941936
iter  80 value 83.860336
final  value 83.857268 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.647719 
iter  10 value 93.894872
iter  20 value 93.884245
iter  30 value 86.645392
iter  40 value 86.379058
iter  50 value 86.377059
iter  60 value 84.995060
iter  70 value 81.887923
iter  80 value 81.123510
iter  90 value 79.895717
iter 100 value 79.356836
final  value 79.356836 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.061398 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.260451 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.739030 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.860959 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.183375 
iter  10 value 94.455135
iter  20 value 94.443314
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.295906 
final  value 94.474276 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.526628 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.976816 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.405867 
final  value 94.409418 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.671670 
iter  10 value 90.547910
iter  20 value 89.062240
iter  30 value 88.783426
iter  40 value 87.075724
iter  50 value 87.068450
final  value 87.068439 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.027386 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.349074 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.524136 
iter  10 value 94.446966
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.125169 
final  value 94.291771 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.262766 
iter  10 value 94.059637
final  value 94.059033 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.152697 
iter  10 value 94.489807
iter  20 value 94.226048
iter  30 value 89.048229
iter  40 value 88.158889
iter  50 value 88.105164
iter  60 value 88.009187
iter  70 value 85.616370
iter  80 value 85.261389
iter  90 value 85.224906
final  value 85.223789 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.448701 
iter  10 value 94.469705
iter  20 value 86.776278
iter  30 value 85.977496
iter  40 value 85.525056
iter  50 value 85.481094
iter  60 value 85.395399
iter  70 value 85.380187
iter  80 value 85.337412
iter  90 value 85.235363
iter 100 value 85.223793
final  value 85.223793 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.506824 
iter  10 value 94.266505
iter  20 value 87.961457
iter  30 value 86.556655
iter  40 value 86.413035
iter  50 value 85.738728
iter  60 value 85.434696
iter  70 value 85.275453
iter  80 value 85.224142
final  value 85.223789 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.208638 
iter  10 value 94.478975
iter  20 value 90.182482
iter  30 value 86.714925
iter  40 value 85.601338
iter  50 value 85.382907
iter  60 value 85.352279
iter  70 value 85.281473
iter  80 value 85.226258
final  value 85.223789 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.589982 
iter  10 value 94.488557
iter  20 value 94.414232
iter  30 value 92.512182
iter  40 value 90.292219
iter  50 value 85.676715
iter  60 value 85.199084
iter  70 value 85.102705
iter  80 value 84.563156
iter  90 value 84.343279
iter 100 value 84.151799
final  value 84.151799 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.374388 
iter  10 value 94.565806
iter  20 value 94.468727
iter  30 value 92.915727
iter  40 value 90.756142
iter  50 value 87.061531
iter  60 value 86.243794
iter  70 value 85.386741
iter  80 value 85.248355
iter  90 value 85.188485
iter 100 value 85.108692
final  value 85.108692 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.875687 
iter  10 value 94.562169
iter  20 value 92.438416
iter  30 value 89.952295
iter  40 value 86.868413
iter  50 value 85.793381
iter  60 value 84.414755
iter  70 value 83.320952
iter  80 value 82.779163
iter  90 value 82.701816
iter 100 value 82.559446
final  value 82.559446 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.338378 
iter  10 value 88.479221
iter  20 value 87.497662
iter  30 value 87.093096
iter  40 value 85.178757
iter  50 value 83.978379
iter  60 value 82.956358
iter  70 value 82.208720
iter  80 value 82.016920
iter  90 value 81.959313
iter 100 value 81.913700
final  value 81.913700 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.233697 
iter  10 value 94.466344
iter  20 value 93.649751
iter  30 value 90.709017
iter  40 value 85.739249
iter  50 value 84.079384
iter  60 value 83.488428
iter  70 value 83.304142
iter  80 value 83.013404
iter  90 value 82.859759
iter 100 value 82.721521
final  value 82.721521 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.720131 
iter  10 value 94.484557
iter  20 value 93.476224
iter  30 value 89.186140
iter  40 value 87.380121
iter  50 value 87.185305
iter  60 value 87.148460
iter  70 value 85.732518
iter  80 value 84.551100
iter  90 value 84.184763
iter 100 value 83.673221
final  value 83.673221 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.218095 
iter  10 value 97.038494
iter  20 value 93.270699
iter  30 value 92.775008
iter  40 value 92.351299
iter  50 value 92.176907
iter  60 value 91.348475
iter  70 value 88.959965
iter  80 value 87.754516
iter  90 value 84.601194
iter 100 value 83.130093
final  value 83.130093 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.381664 
iter  10 value 94.485262
iter  20 value 87.598905
iter  30 value 86.868604
iter  40 value 85.000019
iter  50 value 84.854425
iter  60 value 84.757633
iter  70 value 84.239732
iter  80 value 84.132223
iter  90 value 83.851162
iter 100 value 83.734724
final  value 83.734724 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.321843 
iter  10 value 94.488363
iter  20 value 88.127430
iter  30 value 87.031461
iter  40 value 84.376527
iter  50 value 83.512965
iter  60 value 82.944468
iter  70 value 82.745342
iter  80 value 82.587052
iter  90 value 82.561068
iter 100 value 82.545398
final  value 82.545398 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.833173 
iter  10 value 94.466389
iter  20 value 91.243195
iter  30 value 90.268494
iter  40 value 88.392230
iter  50 value 86.700527
iter  60 value 84.895124
iter  70 value 83.547717
iter  80 value 83.128266
iter  90 value 83.052399
iter 100 value 82.670118
final  value 82.670118 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.588886 
iter  10 value 94.596350
iter  20 value 90.236319
iter  30 value 88.427102
iter  40 value 86.920840
iter  50 value 86.227357
iter  60 value 84.943244
iter  70 value 83.236334
iter  80 value 82.449555
iter  90 value 82.209152
iter 100 value 82.051825
final  value 82.051825 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.952486 
final  value 94.485835 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.488676 
final  value 94.485542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.365135 
iter  10 value 94.485991
iter  20 value 94.437285
iter  30 value 94.409289
iter  40 value 94.403395
final  value 94.403386 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.741482 
final  value 94.486115 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.668167 
final  value 94.485916 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.775532 
iter  10 value 94.489541
iter  20 value 94.405177
iter  30 value 93.476593
iter  40 value 84.572705
iter  50 value 83.427264
iter  60 value 83.036165
iter  70 value 82.847717
iter  80 value 82.667967
iter  90 value 82.398618
iter 100 value 82.264288
final  value 82.264288 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.864989 
iter  10 value 94.448346
iter  20 value 94.443518
iter  30 value 94.359851
iter  40 value 91.513554
iter  50 value 90.978947
iter  60 value 88.855111
iter  70 value 83.264932
iter  80 value 82.718918
iter  90 value 82.617077
iter 100 value 82.534620
final  value 82.534620 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.066500 
iter  10 value 94.143723
iter  20 value 89.574517
iter  30 value 89.522859
iter  40 value 89.296534
iter  50 value 89.283061
iter  60 value 89.272217
iter  70 value 89.267872
iter  80 value 84.804590
iter  90 value 83.859968
iter 100 value 83.803095
final  value 83.803095 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.492495 
iter  10 value 94.447822
iter  20 value 94.404676
final  value 94.403963 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.147818 
iter  10 value 94.489162
iter  20 value 94.446839
iter  30 value 90.546739
iter  40 value 88.931941
iter  50 value 88.466276
iter  60 value 84.980671
iter  70 value 83.832794
final  value 83.832776 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.526604 
iter  10 value 94.451332
iter  20 value 94.425329
iter  30 value 94.097464
iter  40 value 92.209867
final  value 92.009250 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.140371 
iter  10 value 94.490540
iter  20 value 94.449219
final  value 94.443500 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.980139 
iter  10 value 94.451683
iter  20 value 94.169012
iter  30 value 88.820116
iter  40 value 87.451801
iter  50 value 84.615887
iter  60 value 82.341153
iter  70 value 81.629004
iter  80 value 81.184272
final  value 81.184094 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.241894 
iter  10 value 94.492100
iter  20 value 93.011754
iter  30 value 88.572396
iter  40 value 85.928900
iter  50 value 83.441854
iter  60 value 82.949239
iter  70 value 82.917764
iter  80 value 82.459658
iter  90 value 82.001877
iter 100 value 81.932223
final  value 81.932223 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.738679 
iter  10 value 94.451673
iter  20 value 94.443770
iter  30 value 94.357535
iter  40 value 93.492586
iter  50 value 93.353025
iter  60 value 93.352698
iter  60 value 93.352697
final  value 93.352697 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.593196 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.436918 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.611137 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.372539 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.619870 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.451866 
final  value 93.714286 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.988387 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.494455 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.345866 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.027618 
iter  10 value 93.915746
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.814283 
iter  10 value 93.296542
iter  20 value 93.295042
final  value 93.295007 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.155873 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.620258 
final  value 93.869755 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.342456 
iter  10 value 93.668351
iter  10 value 93.668351
iter  10 value 93.668351
final  value 93.668351 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.840350 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.276239 
iter  10 value 94.055065
iter  20 value 93.520032
iter  30 value 93.453722
iter  40 value 92.397401
iter  50 value 86.459996
iter  60 value 86.290295
iter  70 value 85.929189
iter  80 value 85.452479
iter  90 value 85.211585
iter 100 value 85.148127
final  value 85.148127 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.419835 
iter  10 value 92.606110
iter  20 value 88.400843
iter  30 value 84.448569
iter  40 value 84.086902
iter  50 value 83.377051
iter  60 value 82.932548
iter  70 value 82.315087
iter  80 value 82.239578
iter  80 value 82.239577
iter  80 value 82.239577
final  value 82.239577 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.563827 
iter  10 value 94.169619
iter  20 value 88.498624
iter  30 value 86.474309
iter  40 value 86.261402
iter  50 value 86.168079
iter  60 value 85.770528
iter  70 value 85.489140
iter  80 value 85.224703
iter  90 value 85.141168
iter 100 value 85.129660
final  value 85.129660 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.606217 
iter  10 value 93.646156
iter  20 value 86.795394
iter  30 value 86.253423
iter  40 value 85.972084
iter  50 value 85.553906
iter  60 value 85.400224
iter  70 value 85.305996
final  value 85.303475 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.840242 
iter  10 value 94.058422
iter  20 value 94.033899
iter  30 value 93.480912
iter  40 value 93.121351
iter  50 value 91.358547
iter  60 value 90.679093
iter  70 value 89.069132
iter  80 value 85.085321
iter  90 value 84.586203
iter 100 value 84.253396
final  value 84.253396 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 120.205958 
iter  10 value 94.059244
iter  20 value 93.848596
iter  30 value 93.465924
iter  40 value 93.390717
iter  50 value 93.349667
iter  60 value 91.390599
iter  70 value 85.718586
iter  80 value 84.391448
iter  90 value 83.399055
iter 100 value 83.115238
final  value 83.115238 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.074493 
iter  10 value 92.798290
iter  20 value 89.448924
iter  30 value 88.847800
iter  40 value 85.180108
iter  50 value 83.206765
iter  60 value 82.049538
iter  70 value 81.504298
iter  80 value 81.326409
iter  90 value 81.007720
iter 100 value 80.918573
final  value 80.918573 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.440552 
iter  10 value 94.190340
iter  20 value 92.520071
iter  30 value 91.457252
iter  40 value 91.278573
iter  50 value 90.159760
iter  60 value 89.805467
iter  70 value 85.755738
iter  80 value 84.888630
iter  90 value 84.223633
iter 100 value 83.025524
final  value 83.025524 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.232017 
iter  10 value 94.084749
iter  20 value 93.515505
iter  30 value 93.454242
iter  40 value 85.214253
iter  50 value 84.294230
iter  60 value 82.980188
iter  70 value 82.920939
iter  80 value 81.927836
iter  90 value 81.536626
iter 100 value 81.478028
final  value 81.478028 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.680814 
iter  10 value 88.319587
iter  20 value 85.600604
iter  30 value 84.745464
iter  40 value 84.603419
iter  50 value 84.364018
iter  60 value 83.562250
iter  70 value 82.767407
iter  80 value 82.335453
iter  90 value 81.728927
iter 100 value 81.566298
final  value 81.566298 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.459562 
iter  10 value 95.987040
iter  20 value 91.202494
iter  30 value 88.557832
iter  40 value 84.546354
iter  50 value 82.493555
iter  60 value 81.790536
iter  70 value 81.573003
iter  80 value 81.232771
iter  90 value 80.990381
iter 100 value 80.948944
final  value 80.948944 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.543332 
iter  10 value 94.057521
iter  20 value 86.462894
iter  30 value 85.824745
iter  40 value 84.241192
iter  50 value 83.256236
iter  60 value 83.016420
iter  70 value 82.861218
iter  80 value 82.622264
iter  90 value 82.073047
iter 100 value 81.771227
final  value 81.771227 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.056633 
iter  10 value 88.260953
iter  20 value 86.402340
iter  30 value 84.989582
iter  40 value 83.891430
iter  50 value 83.312864
iter  60 value 82.586757
iter  70 value 81.564927
iter  80 value 81.482777
iter  90 value 81.390632
iter 100 value 81.169672
final  value 81.169672 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.745579 
iter  10 value 94.182195
iter  20 value 91.401976
iter  30 value 89.800655
iter  40 value 86.082754
iter  50 value 84.160383
iter  60 value 82.135122
iter  70 value 81.584884
iter  80 value 81.351414
iter  90 value 81.170764
iter 100 value 80.940716
final  value 80.940716 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.909881 
iter  10 value 94.250737
iter  20 value 89.256847
iter  30 value 88.297352
iter  40 value 86.280199
iter  50 value 84.536677
iter  60 value 82.899370
iter  70 value 82.606527
iter  80 value 82.268629
iter  90 value 82.082503
iter 100 value 82.033336
final  value 82.033336 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.587168 
final  value 93.917454 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.149033 
final  value 94.054543 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.197019 
final  value 94.054627 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.397943 
final  value 94.054652 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.979096 
final  value 94.054345 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.059226 
iter  10 value 87.669915
iter  20 value 84.239409
iter  30 value 83.889046
final  value 83.718982 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.994382 
iter  10 value 93.700014
iter  20 value 93.693859
iter  30 value 93.693111
iter  40 value 86.236991
iter  50 value 85.708510
iter  60 value 84.856691
iter  70 value 83.445984
iter  80 value 83.445387
iter  90 value 83.445136
final  value 83.445128 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.137142 
iter  10 value 93.718419
iter  20 value 93.681686
iter  30 value 86.384885
iter  40 value 85.513849
iter  50 value 85.495329
iter  60 value 83.809642
iter  70 value 83.621347
iter  80 value 83.242298
iter  90 value 83.240893
iter 100 value 83.161612
final  value 83.161612 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.799978 
iter  10 value 94.057723
iter  20 value 94.053248
iter  30 value 93.410615
final  value 93.410436 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.185561 
iter  10 value 93.920609
iter  20 value 93.915866
iter  30 value 93.431136
final  value 93.410383 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.638971 
iter  10 value 93.923911
iter  20 value 93.916800
iter  30 value 93.887143
iter  40 value 92.079561
iter  50 value 89.910412
iter  60 value 89.418942
iter  70 value 88.297290
iter  80 value 88.218265
iter  90 value 88.217694
iter 100 value 86.222726
final  value 86.222726 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.649979 
iter  10 value 94.057511
iter  20 value 90.728329
iter  30 value 90.348087
iter  40 value 90.090173
final  value 90.033654 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.743548 
iter  10 value 94.061115
iter  20 value 93.644367
iter  30 value 93.362852
iter  40 value 90.455777
iter  50 value 83.683817
iter  60 value 83.297823
iter  70 value 83.290312
iter  80 value 83.132935
iter  90 value 82.948445
iter 100 value 82.933231
final  value 82.933231 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.172068 
iter  10 value 88.229563
iter  20 value 88.219242
iter  30 value 87.627557
iter  40 value 87.618849
iter  50 value 87.617108
iter  60 value 87.613028
final  value 87.613013 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.760120 
iter  10 value 94.007926
iter  20 value 93.923072
iter  30 value 92.462262
iter  40 value 91.609530
iter  50 value 91.588586
iter  60 value 91.588327
final  value 91.588268 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.127934 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.476868 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.129991 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.551347 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.755518 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.385287 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.709390 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.353930 
final  value 94.052434 
converged
Fitting Repeat 4 

# weights:  305
initial  value 120.844214 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.084615 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.017283 
iter  10 value 91.493659
iter  20 value 91.097475
iter  30 value 91.078985
final  value 91.078774 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.670133 
final  value 94.275363 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.311867 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.794217 
iter  10 value 85.820371
iter  20 value 85.168203
iter  30 value 85.165681
iter  40 value 84.803178
final  value 84.790663 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.458197 
iter  10 value 93.923203
iter  20 value 93.921139
iter  30 value 93.902919
final  value 93.883027 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.055734 
iter  10 value 94.464802
iter  20 value 94.337566
iter  30 value 94.214814
iter  40 value 84.813112
iter  50 value 84.026787
iter  60 value 80.744159
iter  70 value 79.829810
iter  80 value 79.648595
iter  90 value 78.703899
iter 100 value 78.520396
final  value 78.520396 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.476495 
iter  10 value 94.530913
iter  20 value 94.437712
iter  30 value 94.184751
iter  40 value 93.966097
iter  50 value 93.894637
iter  60 value 91.624778
iter  70 value 86.530528
iter  80 value 85.775649
iter  90 value 82.883319
iter 100 value 81.328909
final  value 81.328909 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.531319 
iter  10 value 94.482841
iter  20 value 94.098704
iter  30 value 93.993358
iter  40 value 84.864996
iter  50 value 81.703888
iter  60 value 81.016763
iter  70 value 80.314100
iter  80 value 80.176725
iter  90 value 80.103728
iter 100 value 80.052372
final  value 80.052372 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.781492 
iter  10 value 94.490642
iter  20 value 94.468823
iter  30 value 94.398476
iter  40 value 83.583238
iter  50 value 81.152109
iter  60 value 81.100984
iter  70 value 80.172890
iter  80 value 79.586727
iter  90 value 79.524198
iter 100 value 79.514783
final  value 79.514783 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.014863 
iter  10 value 94.310431
iter  20 value 86.448584
iter  30 value 83.188926
iter  40 value 81.782806
iter  50 value 81.379606
iter  60 value 81.309133
iter  70 value 78.747170
iter  80 value 78.661239
iter  90 value 78.490102
iter 100 value 78.435321
final  value 78.435321 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.977001 
iter  10 value 94.084385
iter  20 value 86.937209
iter  30 value 81.991084
iter  40 value 80.246401
iter  50 value 79.809494
iter  60 value 78.668654
iter  70 value 78.535126
iter  80 value 78.358069
iter  90 value 77.965069
iter 100 value 77.301160
final  value 77.301160 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.917645 
iter  10 value 94.503209
iter  20 value 93.775445
iter  30 value 88.894579
iter  40 value 79.964561
iter  50 value 79.217654
iter  60 value 78.582428
iter  70 value 77.811331
iter  80 value 76.843684
iter  90 value 76.634533
iter 100 value 76.550663
final  value 76.550663 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.132311 
iter  10 value 94.571570
iter  20 value 94.482022
iter  30 value 93.598293
iter  40 value 86.834474
iter  50 value 86.071240
iter  60 value 85.373617
iter  70 value 84.884858
iter  80 value 84.299769
iter  90 value 81.641974
iter 100 value 80.682472
final  value 80.682472 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.127731 
iter  10 value 94.581083
iter  20 value 94.032531
iter  30 value 91.821785
iter  40 value 86.609022
iter  50 value 86.137929
iter  60 value 85.366196
iter  70 value 85.097721
iter  80 value 84.976489
iter  90 value 84.882803
iter 100 value 84.712962
final  value 84.712962 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.671057 
iter  10 value 95.976034
iter  20 value 83.298835
iter  30 value 82.052838
iter  40 value 81.408419
iter  50 value 79.300235
iter  60 value 78.453623
iter  70 value 77.443508
iter  80 value 77.062477
iter  90 value 77.040185
iter 100 value 76.941590
final  value 76.941590 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.578670 
iter  10 value 96.066827
iter  20 value 90.393785
iter  30 value 89.186038
iter  40 value 88.693576
iter  50 value 80.471892
iter  60 value 79.783751
iter  70 value 79.626514
iter  80 value 79.174789
iter  90 value 78.130760
iter 100 value 77.537553
final  value 77.537553 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.262669 
iter  10 value 95.122829
iter  20 value 94.411341
iter  30 value 83.927773
iter  40 value 81.802105
iter  50 value 81.604463
iter  60 value 81.252345
iter  70 value 80.752766
iter  80 value 79.136606
iter  90 value 77.914649
iter 100 value 77.470757
final  value 77.470757 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.974986 
iter  10 value 94.541290
iter  20 value 93.397937
iter  30 value 83.240493
iter  40 value 80.065546
iter  50 value 79.288560
iter  60 value 78.980636
iter  70 value 78.900749
iter  80 value 78.890126
iter  90 value 78.131437
iter 100 value 77.544293
final  value 77.544293 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.803868 
iter  10 value 94.417068
iter  20 value 87.634042
iter  30 value 81.986661
iter  40 value 81.543559
iter  50 value 80.604692
iter  60 value 79.474330
iter  70 value 79.102569
iter  80 value 78.816693
iter  90 value 78.623864
iter 100 value 78.438285
final  value 78.438285 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.573467 
iter  10 value 94.694308
iter  20 value 86.671049
iter  30 value 83.812434
iter  40 value 81.138247
iter  50 value 79.833186
iter  60 value 78.455813
iter  70 value 77.938999
iter  80 value 77.390668
iter  90 value 76.701619
iter 100 value 76.348899
final  value 76.348899 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.502735 
iter  10 value 94.277145
iter  20 value 93.949059
final  value 93.883244 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.867806 
final  value 94.277188 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.783652 
final  value 94.486074 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.032029 
final  value 94.485788 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.935335 
iter  10 value 94.485857
iter  20 value 94.368164
iter  30 value 85.174801
iter  40 value 85.171714
iter  50 value 84.924867
iter  60 value 84.296852
iter  70 value 84.295821
iter  80 value 84.294225
iter  90 value 84.293908
final  value 84.293792 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.007162 
iter  10 value 94.489321
iter  20 value 94.484341
iter  30 value 85.258616
iter  40 value 82.386694
iter  50 value 80.002338
iter  60 value 79.999498
final  value 79.997449 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.391124 
iter  10 value 94.354584
iter  20 value 94.280203
iter  30 value 94.277233
iter  40 value 93.964551
iter  50 value 81.053481
iter  60 value 81.046720
iter  70 value 80.543980
iter  80 value 79.021618
iter  90 value 76.088391
iter 100 value 75.587018
final  value 75.587018 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.388363 
iter  10 value 94.489364
iter  20 value 94.484344
iter  30 value 94.323340
iter  40 value 93.890832
iter  50 value 90.515825
iter  60 value 81.218872
final  value 81.218871 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.112756 
iter  10 value 93.555448
iter  20 value 89.505914
iter  30 value 89.197722
iter  40 value 88.596411
iter  50 value 88.127768
iter  60 value 88.126165
iter  70 value 88.124651
final  value 88.124527 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.582530 
iter  10 value 94.169876
iter  20 value 94.157924
iter  30 value 94.127398
iter  30 value 94.127397
iter  30 value 94.127397
final  value 94.127397 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.853011 
iter  10 value 94.283329
iter  20 value 94.211217
iter  30 value 89.299750
iter  40 value 80.767118
iter  50 value 79.376181
iter  60 value 78.960670
iter  70 value 78.630545
iter  80 value 78.624158
iter  90 value 78.618454
iter 100 value 77.262446
final  value 77.262446 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.004379 
iter  10 value 94.491046
iter  20 value 94.480600
iter  30 value 85.937052
iter  40 value 85.169037
iter  50 value 84.980495
iter  60 value 84.297810
final  value 84.293392 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.186597 
iter  10 value 94.317800
iter  20 value 92.172396
iter  30 value 88.358710
iter  40 value 88.326405
iter  50 value 87.529593
iter  60 value 83.926348
iter  70 value 83.539284
iter  80 value 83.433090
iter  90 value 83.104662
iter 100 value 82.796338
final  value 82.796338 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.913970 
iter  10 value 94.283441
iter  20 value 94.283105
iter  30 value 93.674123
iter  40 value 89.761664
iter  50 value 88.605857
iter  60 value 79.207768
iter  70 value 78.015100
iter  80 value 77.996437
iter  90 value 77.995609
final  value 77.995602 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.707309 
iter  10 value 85.274991
iter  20 value 85.115240
iter  30 value 85.084490
iter  40 value 85.040736
iter  50 value 85.037255
iter  60 value 85.037075
final  value 85.036987 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.955528 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.648225 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.490259 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.782469 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.395875 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.479950 
iter  10 value 93.567526
iter  10 value 93.567525
iter  10 value 93.567525
final  value 93.567525 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.940095 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.135497 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.716613 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.263807 
iter  10 value 92.914468
iter  20 value 90.303746
iter  30 value 87.690345
iter  40 value 87.601852
iter  50 value 87.601464
final  value 87.601457 
converged
Fitting Repeat 1 

# weights:  507
initial  value 125.610924 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.503032 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.305978 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.105331 
final  value 93.608369 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.429408 
final  value 94.400000 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.180321 
iter  10 value 94.363166
iter  20 value 88.098292
iter  30 value 86.371288
iter  40 value 85.938468
iter  50 value 84.551252
iter  60 value 84.411316
iter  70 value 84.389699
iter  80 value 84.374038
final  value 84.374037 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.199955 
iter  10 value 94.482277
iter  20 value 93.877783
iter  30 value 92.796292
iter  40 value 92.191464
iter  50 value 90.937599
iter  60 value 90.897888
iter  70 value 90.897071
iter  80 value 90.893987
final  value 90.893840 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.786057 
iter  10 value 94.488485
iter  20 value 94.373068
iter  30 value 91.922198
iter  40 value 89.100320
iter  50 value 85.632563
iter  60 value 84.355512
iter  70 value 83.073758
iter  80 value 81.208097
iter  90 value 81.046279
final  value 81.038310 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.358116 
iter  10 value 94.484174
iter  20 value 92.463310
iter  30 value 90.981943
iter  40 value 87.811653
iter  50 value 87.207289
iter  60 value 86.674640
iter  70 value 84.973570
iter  80 value 83.964832
iter  90 value 83.936524
final  value 83.936384 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.263671 
iter  10 value 94.487042
iter  20 value 94.475479
iter  30 value 83.984158
iter  40 value 82.943609
iter  50 value 82.206398
iter  60 value 80.753259
iter  70 value 80.205007
iter  80 value 80.137322
iter  90 value 80.096358
final  value 80.065827 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.150338 
iter  10 value 94.429881
iter  20 value 91.558470
iter  30 value 84.748128
iter  40 value 82.349735
iter  50 value 81.310803
iter  60 value 81.167757
iter  70 value 80.653971
iter  80 value 79.149016
iter  90 value 78.678421
iter 100 value 78.453724
final  value 78.453724 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.882418 
iter  10 value 94.861593
iter  20 value 92.898179
iter  30 value 90.317613
iter  40 value 85.029940
iter  50 value 84.173087
iter  60 value 83.558909
iter  70 value 83.495266
iter  80 value 83.355308
iter  90 value 82.239011
iter 100 value 81.930930
final  value 81.930930 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.754946 
iter  10 value 95.005581
iter  20 value 86.396894
iter  30 value 84.940181
iter  40 value 84.677878
iter  50 value 84.312262
iter  60 value 84.101864
iter  70 value 84.039813
iter  80 value 83.947287
iter  90 value 83.507222
iter 100 value 80.289163
final  value 80.289163 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.380541 
iter  10 value 94.736660
iter  20 value 86.742423
iter  30 value 85.699719
iter  40 value 85.175192
iter  50 value 84.868465
iter  60 value 84.050661
iter  70 value 83.873351
iter  80 value 83.492246
iter  90 value 81.476434
iter 100 value 79.504763
final  value 79.504763 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.124256 
iter  10 value 94.846259
iter  20 value 94.181760
iter  30 value 92.512836
iter  40 value 82.682669
iter  50 value 80.326213
iter  60 value 79.465346
iter  70 value 79.196282
iter  80 value 78.880459
iter  90 value 78.761851
iter 100 value 78.677338
final  value 78.677338 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.362792 
iter  10 value 94.146725
iter  20 value 92.453206
iter  30 value 84.393503
iter  40 value 82.959786
iter  50 value 80.304078
iter  60 value 79.908517
iter  70 value 79.791183
iter  80 value 79.279678
iter  90 value 78.893712
iter 100 value 78.582807
final  value 78.582807 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.355164 
iter  10 value 89.300082
iter  20 value 86.557564
iter  30 value 85.883489
iter  40 value 85.148662
iter  50 value 82.179444
iter  60 value 80.278263
iter  70 value 79.852171
iter  80 value 79.323142
iter  90 value 79.140283
iter 100 value 79.035546
final  value 79.035546 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.185073 
iter  10 value 94.564188
iter  20 value 88.372558
iter  30 value 86.072263
iter  40 value 84.467240
iter  50 value 84.148439
iter  60 value 82.700091
iter  70 value 81.029319
iter  80 value 80.082494
iter  90 value 79.073914
iter 100 value 78.892738
final  value 78.892738 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.540557 
iter  10 value 94.509988
iter  20 value 92.516711
iter  30 value 89.436243
iter  40 value 86.535977
iter  50 value 85.505695
iter  60 value 83.434753
iter  70 value 81.833929
iter  80 value 81.184292
iter  90 value 80.976956
iter 100 value 80.810587
final  value 80.810587 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.335577 
iter  10 value 94.521972
iter  20 value 90.715344
iter  30 value 84.230276
iter  40 value 83.684563
iter  50 value 83.381313
iter  60 value 82.467053
iter  70 value 80.160829
iter  80 value 79.151422
iter  90 value 78.764350
iter 100 value 78.632260
final  value 78.632260 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.521384 
final  value 94.485712 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.793203 
final  value 94.485822 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.658080 
final  value 94.486168 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.706358 
iter  10 value 94.485756
iter  20 value 94.484241
final  value 94.484216 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.900965 
final  value 94.468581 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.550824 
iter  10 value 94.330589
iter  20 value 93.067610
iter  30 value 88.074640
iter  40 value 87.791007
iter  50 value 87.317590
iter  60 value 83.503107
iter  70 value 83.451898
iter  80 value 83.451503
final  value 83.451485 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.666814 
iter  10 value 94.489138
iter  20 value 94.475411
iter  30 value 85.169593
iter  40 value 85.169436
final  value 85.169350 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.429308 
iter  10 value 93.618773
iter  20 value 93.089082
iter  30 value 84.865136
iter  40 value 82.896107
iter  50 value 80.823613
iter  60 value 80.386511
iter  70 value 80.374304
final  value 80.370423 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.768881 
iter  10 value 94.488837
iter  20 value 85.790056
iter  30 value 83.829145
iter  40 value 83.269971
final  value 83.269360 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.819638 
iter  10 value 94.489333
iter  20 value 94.478842
iter  30 value 85.438074
iter  40 value 85.169167
final  value 85.169166 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.279594 
iter  10 value 91.222742
iter  20 value 82.949229
iter  30 value 82.803320
iter  40 value 82.457517
iter  50 value 82.269521
iter  60 value 82.263146
iter  70 value 82.260617
iter  80 value 82.254670
final  value 82.253983 
converged
Fitting Repeat 2 

# weights:  507
initial  value 133.485244 
iter  10 value 94.494257
iter  20 value 94.485774
iter  30 value 88.396365
iter  40 value 87.780776
iter  50 value 87.780227
iter  60 value 85.556715
iter  70 value 83.453348
iter  80 value 83.440181
iter  90 value 83.421843
iter 100 value 83.419027
final  value 83.419027 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.123286 
iter  10 value 94.474992
iter  20 value 94.468165
final  value 94.467176 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.115519 
iter  10 value 94.334959
iter  20 value 94.330098
iter  30 value 94.328214
iter  40 value 94.065148
iter  50 value 93.150980
iter  60 value 85.121209
iter  70 value 83.112682
iter  80 value 82.688122
iter  90 value 82.621243
final  value 82.613281 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.100320 
iter  10 value 94.501160
iter  20 value 94.490930
iter  30 value 93.960702
iter  40 value 93.696296
iter  50 value 91.938512
iter  60 value 91.935613
iter  70 value 91.934797
iter  80 value 90.661523
iter  90 value 82.004708
iter 100 value 81.382458
final  value 81.382458 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 167.503580 
iter  10 value 117.745148
iter  20 value 117.732801
iter  30 value 117.728525
final  value 117.728513 
converged
Fitting Repeat 2 

# weights:  507
initial  value 137.142669 
iter  10 value 117.106184
iter  20 value 116.973928
iter  30 value 113.535916
iter  40 value 106.710773
iter  50 value 105.279114
iter  60 value 103.124560
final  value 103.124362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.014149 
iter  10 value 117.789116
iter  20 value 117.767892
iter  30 value 117.575245
iter  40 value 116.941172
iter  50 value 116.336976
iter  60 value 114.582288
iter  70 value 114.527916
final  value 114.527655 
converged
Fitting Repeat 4 

# weights:  507
initial  value 134.152224 
iter  10 value 117.560017
iter  20 value 117.536180
iter  30 value 117.520911
iter  40 value 117.514378
iter  50 value 116.602927
iter  60 value 106.897388
iter  70 value 104.289044
iter  80 value 103.676087
iter  90 value 103.674795
iter 100 value 103.470406
final  value 103.470406 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.143068 
iter  10 value 117.766682
iter  20 value 117.733467
iter  30 value 109.872523
final  value 108.527964 
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 -- Thu Jun 27 21:46:52 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 17.928   1.143  25.366