##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/library --timings HPiP_1.5.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2023-01-14 r83615)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
    gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
    GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
* running under: Ubuntu 22.04.1 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.5.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       39.797  0.411  40.224
corr_plot     37.944  0.388  38.587
FSmethod      36.485  0.335  36.836
pred_ensembel 18.094  0.394  17.266
getFASTA       0.874  0.008   7.670
enrichfindP    0.465  0.069  38.652
* 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 ...
  ‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK
 NONE
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.17-bioc/R/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (64-bit)

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

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

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

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
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 102.580067 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.455069 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.040780 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.147308 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.302037 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.886615 
iter  10 value 94.467391
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.512460 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.675893 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.584751 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.129159 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.033114 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.975760 
iter  10 value 94.313415
iter  20 value 93.731227
iter  30 value 93.660996
iter  40 value 93.660681
final  value 93.660676 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.546611 
final  value 94.467392 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.101882 
iter  10 value 93.287557
iter  20 value 91.593199
final  value 91.593023 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.723103 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.078580 
iter  10 value 94.452743
iter  20 value 93.419572
iter  30 value 90.983681
iter  40 value 89.918193
iter  50 value 88.082171
iter  60 value 86.475484
iter  70 value 86.214770
iter  80 value 85.446262
iter  90 value 84.953816
iter 100 value 84.869313
final  value 84.869313 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.854862 
iter  10 value 92.054439
iter  20 value 86.722721
iter  30 value 85.770267
iter  40 value 85.317514
iter  50 value 84.095205
iter  60 value 82.780322
iter  70 value 82.356253
iter  80 value 82.332043
final  value 82.332033 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.101898 
iter  10 value 94.363952
iter  20 value 92.195697
iter  30 value 92.025036
iter  40 value 91.958428
iter  50 value 91.927624
iter  60 value 91.380187
iter  70 value 91.329447
final  value 91.329417 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.218972 
iter  10 value 94.181416
iter  20 value 88.508827
iter  30 value 88.242373
iter  40 value 87.769104
iter  50 value 86.548831
iter  60 value 85.964323
iter  70 value 85.925130
final  value 85.924343 
converged
Fitting Repeat 5 

# weights:  103
initial  value 115.899032 
iter  10 value 94.518955
iter  20 value 94.486985
iter  30 value 94.409043
iter  40 value 88.803109
iter  50 value 85.256059
iter  60 value 84.637275
iter  70 value 83.043736
iter  80 value 81.965836
iter  90 value 81.883091
final  value 81.883085 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.382195 
iter  10 value 94.656474
iter  20 value 94.127808
iter  30 value 86.276957
iter  40 value 85.173200
iter  50 value 84.637128
iter  60 value 84.388172
iter  70 value 83.453174
iter  80 value 82.399535
iter  90 value 81.854998
iter 100 value 81.445990
final  value 81.445990 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.445783 
iter  10 value 94.093800
iter  20 value 88.955650
iter  30 value 88.121173
iter  40 value 87.496419
iter  50 value 87.360238
iter  60 value 86.608839
iter  70 value 84.688935
iter  80 value 84.438756
iter  90 value 81.156666
iter 100 value 80.784375
final  value 80.784375 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.463097 
iter  10 value 94.533951
iter  20 value 88.759529
iter  30 value 86.933495
iter  40 value 84.065050
iter  50 value 81.241812
iter  60 value 80.629918
iter  70 value 80.335059
iter  80 value 80.264144
iter  90 value 80.166509
iter 100 value 80.137248
final  value 80.137248 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.412840 
iter  10 value 94.630795
iter  20 value 91.933624
iter  30 value 87.382475
iter  40 value 83.938416
iter  50 value 82.698056
iter  60 value 80.864609
iter  70 value 80.792986
iter  80 value 80.615921
iter  90 value 80.464118
iter 100 value 80.040923
final  value 80.040923 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.156385 
iter  10 value 97.667473
iter  20 value 90.234273
iter  30 value 84.237530
iter  40 value 83.046589
iter  50 value 82.330952
iter  60 value 81.450769
iter  70 value 81.235821
iter  80 value 80.933042
iter  90 value 80.703865
iter 100 value 80.024524
final  value 80.024524 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.771267 
iter  10 value 94.600567
iter  20 value 93.083270
iter  30 value 87.993028
iter  40 value 84.636007
iter  50 value 83.704731
iter  60 value 83.113754
iter  70 value 81.562673
iter  80 value 80.651312
iter  90 value 80.471094
iter 100 value 80.372580
final  value 80.372580 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.582134 
iter  10 value 94.248541
iter  20 value 90.944795
iter  30 value 86.471026
iter  40 value 84.072441
iter  50 value 82.669115
iter  60 value 82.065961
iter  70 value 80.696873
iter  80 value 80.051029
iter  90 value 79.842913
iter 100 value 79.726734
final  value 79.726734 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.351566 
iter  10 value 99.101325
iter  20 value 87.575047
iter  30 value 85.645644
iter  40 value 84.163711
iter  50 value 82.660134
iter  60 value 82.145937
iter  70 value 82.098220
iter  80 value 81.728610
iter  90 value 81.404317
iter 100 value 80.527191
final  value 80.527191 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.487095 
iter  10 value 94.816583
iter  20 value 93.999340
iter  30 value 90.291045
iter  40 value 86.733958
iter  50 value 85.992023
iter  60 value 84.009508
iter  70 value 82.247714
iter  80 value 80.922070
iter  90 value 80.077892
iter 100 value 79.826599
final  value 79.826599 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.412751 
iter  10 value 93.332315
iter  20 value 88.362143
iter  30 value 87.296936
iter  40 value 82.373250
iter  50 value 80.680161
iter  60 value 80.098853
iter  70 value 79.769782
iter  80 value 79.596388
iter  90 value 79.449323
iter 100 value 79.396205
final  value 79.396205 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.738728 
final  value 94.485988 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.885277 
final  value 94.462637 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.593318 
final  value 94.485868 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.204786 
final  value 94.485987 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.911949 
final  value 94.485591 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.619954 
iter  10 value 94.489229
iter  20 value 94.484142
iter  30 value 94.467435
final  value 94.467417 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.094620 
iter  10 value 94.302016
iter  20 value 93.427752
iter  30 value 91.473717
iter  40 value 91.115592
iter  50 value 90.909829
iter  60 value 90.909224
iter  70 value 90.897489
iter  80 value 90.897341
iter  90 value 90.896935
final  value 90.896930 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.135443 
iter  10 value 94.488579
iter  20 value 94.422838
iter  30 value 87.572447
iter  40 value 86.908543
iter  50 value 84.262722
iter  60 value 84.060339
iter  70 value 84.059955
iter  80 value 82.910737
iter  90 value 82.497394
iter 100 value 82.476842
final  value 82.476842 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.364164 
iter  10 value 94.472519
iter  20 value 93.612077
iter  30 value 85.650995
iter  40 value 83.408541
iter  50 value 83.265682
iter  60 value 83.264835
iter  70 value 83.249075
iter  80 value 82.858876
final  value 82.811967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.651549 
iter  10 value 88.383382
iter  20 value 87.490858
iter  30 value 87.484283
iter  40 value 86.443017
iter  50 value 86.162598
iter  60 value 86.151507
iter  70 value 86.147742
iter  80 value 86.147017
iter  90 value 85.943953
iter 100 value 85.804171
final  value 85.804171 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.798447 
iter  10 value 94.492340
iter  20 value 94.481737
iter  30 value 94.467732
iter  40 value 94.374375
iter  50 value 94.134233
iter  60 value 86.716887
iter  70 value 86.314138
iter  80 value 85.630375
iter  90 value 83.628509
iter 100 value 82.154846
final  value 82.154846 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.091110 
iter  10 value 94.492087
iter  20 value 94.474386
iter  30 value 89.890742
iter  40 value 86.081990
iter  50 value 84.273938
iter  60 value 84.260431
final  value 84.260232 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.147486 
iter  10 value 94.474984
iter  20 value 94.345490
iter  30 value 92.742315
iter  40 value 92.279674
final  value 92.277287 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.814650 
iter  10 value 94.492317
iter  20 value 94.461235
iter  30 value 88.314521
iter  40 value 85.390144
iter  50 value 84.354353
iter  60 value 84.200259
iter  70 value 84.200076
iter  80 value 84.087259
iter  90 value 82.883517
iter 100 value 82.833612
final  value 82.833612 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.227014 
iter  10 value 94.492419
iter  20 value 94.484919
iter  30 value 94.389497
iter  40 value 94.304329
iter  50 value 94.068761
iter  60 value 93.865501
iter  70 value 85.055000
iter  80 value 84.288821
iter  90 value 84.050577
iter 100 value 84.046866
final  value 84.046866 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.018851 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.698085 
iter  10 value 93.772976
final  value 93.772973 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.208577 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.680277 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.267920 
final  value 94.052434 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.623311 
iter  10 value 93.772989
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.003686 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.890000 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.985074 
iter  10 value 93.772979
final  value 93.772973 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.753768 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.731101 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.721479 
final  value 93.772973 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.015752 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.397120 
iter  10 value 93.772976
final  value 93.772973 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.108023 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.648677 
iter  10 value 94.213500
iter  20 value 85.580748
iter  30 value 82.954373
iter  40 value 82.736389
iter  50 value 82.638876
iter  60 value 82.588022
final  value 82.586568 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.243673 
iter  10 value 94.489373
iter  20 value 94.066072
iter  30 value 91.701401
iter  40 value 91.416411
iter  50 value 87.272560
iter  60 value 86.763092
iter  70 value 83.127812
iter  80 value 81.649229
iter  90 value 81.598357
iter 100 value 81.524278
final  value 81.524278 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.996653 
iter  10 value 94.836485
iter  20 value 94.488154
iter  30 value 94.029795
iter  40 value 93.982605
iter  50 value 93.436554
iter  60 value 90.003757
iter  70 value 86.663345
iter  80 value 83.424971
iter  90 value 83.043474
iter 100 value 83.037461
final  value 83.037461 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.026017 
iter  10 value 94.007130
iter  20 value 86.233276
iter  30 value 85.797536
iter  40 value 85.140016
iter  50 value 83.011624
iter  60 value 82.997131
iter  70 value 82.996809
iter  80 value 82.996612
final  value 82.996606 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.133446 
iter  10 value 94.001214
iter  20 value 93.968296
iter  30 value 87.887752
iter  40 value 83.995743
iter  50 value 83.063818
iter  60 value 82.998829
iter  70 value 82.977623
final  value 82.977622 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.945474 
iter  10 value 94.546334
iter  20 value 94.432603
iter  30 value 88.670859
iter  40 value 82.828541
iter  50 value 82.651893
iter  60 value 81.755858
iter  70 value 81.451028
iter  80 value 81.390086
iter  90 value 81.219796
iter 100 value 80.623237
final  value 80.623237 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.941457 
iter  10 value 93.394562
iter  20 value 83.013899
iter  30 value 82.841857
iter  40 value 82.420134
iter  50 value 81.635811
iter  60 value 81.500740
iter  70 value 81.350830
iter  80 value 81.181704
iter  90 value 80.814665
iter 100 value 80.655881
final  value 80.655881 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.283447 
iter  10 value 94.164959
iter  20 value 92.195260
iter  30 value 85.238774
iter  40 value 83.061907
iter  50 value 82.945333
iter  60 value 82.689397
iter  70 value 82.476626
iter  80 value 82.469179
iter  90 value 82.467717
iter 100 value 81.420035
final  value 81.420035 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.295891 
iter  10 value 94.419104
iter  20 value 93.621698
iter  30 value 86.641584
iter  40 value 84.467120
iter  50 value 82.654603
iter  60 value 82.452560
iter  70 value 82.295356
iter  80 value 81.935320
iter  90 value 80.888930
iter 100 value 80.144979
final  value 80.144979 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.760589 
iter  10 value 94.474666
iter  20 value 89.104283
iter  30 value 83.972361
iter  40 value 82.430146
iter  50 value 80.939728
iter  60 value 80.397489
iter  70 value 80.210325
iter  80 value 80.061793
iter  90 value 79.766578
iter 100 value 79.588286
final  value 79.588286 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 133.977359 
iter  10 value 95.362971
iter  20 value 94.262979
iter  30 value 89.902291
iter  40 value 88.455923
iter  50 value 87.023402
iter  60 value 83.063961
iter  70 value 81.104074
iter  80 value 80.406235
iter  90 value 79.974809
iter 100 value 79.813533
final  value 79.813533 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.537629 
iter  10 value 93.674556
iter  20 value 90.296005
iter  30 value 89.450592
iter  40 value 86.439248
iter  50 value 83.166382
iter  60 value 82.399703
iter  70 value 82.335969
iter  80 value 82.054601
iter  90 value 81.354965
iter 100 value 80.997333
final  value 80.997333 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.427917 
iter  10 value 93.513065
iter  20 value 91.558350
iter  30 value 86.037993
iter  40 value 84.111264
iter  50 value 82.924733
iter  60 value 81.283298
iter  70 value 80.252100
iter  80 value 79.676412
iter  90 value 79.431075
iter 100 value 79.341601
final  value 79.341601 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.033898 
iter  10 value 94.540289
iter  20 value 91.174587
iter  30 value 90.266555
iter  40 value 84.484571
iter  50 value 83.605739
iter  60 value 83.195944
iter  70 value 81.761830
iter  80 value 81.369714
iter  90 value 80.966354
iter 100 value 80.857026
final  value 80.857026 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.641683 
iter  10 value 94.405515
iter  20 value 91.260353
iter  30 value 84.280100
iter  40 value 83.508314
iter  50 value 82.155362
iter  60 value 81.689621
iter  70 value 81.466647
iter  80 value 81.426013
iter  90 value 81.397290
iter 100 value 81.342848
final  value 81.342848 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.977069 
final  value 94.485825 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.232068 
final  value 94.486194 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.505756 
final  value 94.485838 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.281808 
iter  10 value 94.486011
iter  20 value 94.200135
iter  30 value 86.959474
iter  40 value 86.956594
iter  50 value 86.956449
iter  60 value 85.593398
iter  70 value 84.861790
iter  80 value 82.397215
final  value 81.904198 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.056149 
iter  10 value 93.774978
iter  20 value 93.773975
iter  30 value 93.763629
iter  40 value 90.945818
iter  50 value 90.843330
iter  60 value 90.842976
final  value 90.842941 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.684971 
iter  10 value 94.488556
iter  20 value 93.894340
iter  30 value 93.352162
iter  40 value 93.351924
final  value 93.351849 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.716463 
iter  10 value 88.993683
iter  20 value 87.926583
iter  30 value 84.506593
iter  40 value 84.486612
iter  50 value 84.093415
iter  60 value 84.087611
iter  70 value 84.085442
final  value 84.085283 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.968057 
iter  10 value 93.784016
iter  20 value 93.780623
iter  30 value 93.729624
iter  40 value 93.725239
iter  50 value 93.093010
iter  60 value 89.212466
iter  70 value 87.485373
iter  80 value 87.216302
iter  90 value 87.195520
iter 100 value 81.013185
final  value 81.013185 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.920780 
iter  10 value 93.457071
iter  20 value 93.374551
iter  30 value 93.370513
iter  40 value 93.361209
iter  50 value 93.357535
iter  60 value 93.157674
final  value 93.157631 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.595220 
iter  10 value 94.488802
iter  20 value 94.452546
iter  30 value 89.950403
iter  40 value 84.676579
iter  50 value 83.809126
final  value 83.807636 
converged
Fitting Repeat 1 

# weights:  507
initial  value 131.278618 
iter  10 value 93.426234
iter  20 value 93.395363
iter  30 value 93.295049
iter  40 value 93.292318
final  value 93.291868 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.276277 
iter  10 value 84.308244
iter  20 value 84.083400
iter  30 value 84.075777
iter  40 value 84.072612
iter  50 value 84.071964
iter  60 value 84.070967
iter  70 value 83.815084
iter  80 value 83.565416
iter  90 value 83.520311
iter 100 value 83.443909
final  value 83.443909 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.291600 
iter  10 value 92.401923
iter  20 value 92.160891
iter  30 value 92.007825
iter  40 value 87.455287
iter  50 value 84.103818
iter  60 value 83.965455
iter  70 value 83.957012
iter  80 value 83.910412
iter  90 value 83.904476
iter 100 value 81.875923
final  value 81.875923 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.162214 
iter  10 value 94.491739
iter  20 value 94.196832
iter  30 value 93.339692
iter  40 value 92.427465
iter  50 value 92.408374
iter  60 value 92.122865
final  value 92.122766 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.843476 
iter  10 value 94.060175
iter  20 value 93.750419
iter  30 value 85.985490
iter  40 value 82.917898
iter  50 value 82.896159
iter  60 value 82.763997
iter  70 value 82.761924
iter  80 value 82.759871
iter  90 value 81.296833
iter 100 value 79.889031
final  value 79.889031 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.853786 
iter  10 value 85.694112
iter  20 value 84.641278
iter  30 value 84.039107
iter  40 value 84.017630
final  value 84.017612 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.119671 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.179892 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.160122 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.880675 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.206232 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.139124 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.710089 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.765247 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.989910 
iter  10 value 89.275774
iter  20 value 87.446213
iter  30 value 87.378876
iter  40 value 86.354600
iter  50 value 86.298867
iter  60 value 86.298322
final  value 86.298282 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.638152 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.255263 
iter  10 value 94.467447
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.003430 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 123.634308 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.920088 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.256037 
iter  10 value 94.573759
iter  20 value 92.352523
iter  30 value 85.645523
iter  40 value 85.291012
iter  50 value 84.752388
iter  60 value 84.204390
final  value 84.127255 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.675158 
iter  10 value 94.395587
iter  20 value 90.355735
iter  30 value 89.625255
iter  40 value 89.473980
iter  50 value 87.415265
iter  60 value 85.429143
iter  70 value 85.343272
iter  80 value 85.225832
iter  90 value 84.874806
iter 100 value 84.834701
final  value 84.834701 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 109.164382 
iter  10 value 94.454071
iter  20 value 90.406294
iter  30 value 88.259038
iter  40 value 87.670214
iter  50 value 85.604440
iter  60 value 83.707472
iter  70 value 82.967740
iter  80 value 82.855231
final  value 82.855122 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.811415 
iter  10 value 94.489445
iter  20 value 87.693914
iter  30 value 85.470402
iter  40 value 84.810353
iter  50 value 84.609912
iter  60 value 84.508608
iter  70 value 84.398292
iter  80 value 84.105518
final  value 84.104459 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.400828 
iter  10 value 91.012979
iter  20 value 87.845110
iter  30 value 83.976298
iter  40 value 83.799893
iter  50 value 83.681816
iter  60 value 83.566170
iter  70 value 83.346848
iter  80 value 83.032866
iter  90 value 82.680686
iter 100 value 82.653143
final  value 82.653143 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.351833 
iter  10 value 94.470420
iter  20 value 86.926837
iter  30 value 85.420528
iter  40 value 84.915495
iter  50 value 83.143268
iter  60 value 82.295494
iter  70 value 82.042159
iter  80 value 81.890993
iter  90 value 81.768299
iter 100 value 81.683674
final  value 81.683674 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.931538 
iter  10 value 94.614042
iter  20 value 89.096515
iter  30 value 87.568536
iter  40 value 87.191006
iter  50 value 85.932623
iter  60 value 85.220863
iter  70 value 85.115646
iter  80 value 85.097842
iter  90 value 85.047084
iter 100 value 84.870314
final  value 84.870314 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.109006 
iter  10 value 94.774157
iter  20 value 94.473419
iter  30 value 88.733485
iter  40 value 87.286892
iter  50 value 84.075677
iter  60 value 82.928079
iter  70 value 82.572231
iter  80 value 82.037330
iter  90 value 81.759516
iter 100 value 81.621957
final  value 81.621957 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.204263 
iter  10 value 94.494575
iter  20 value 90.125117
iter  30 value 87.311114
iter  40 value 85.560687
iter  50 value 84.983745
iter  60 value 84.714937
iter  70 value 82.931642
iter  80 value 82.282474
iter  90 value 82.067832
iter 100 value 81.970521
final  value 81.970521 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.981140 
iter  10 value 90.905863
iter  20 value 89.815446
iter  30 value 89.306025
iter  40 value 88.004786
iter  50 value 86.784441
iter  60 value 85.494154
iter  70 value 85.038868
iter  80 value 84.981598
iter  90 value 84.769152
iter 100 value 83.363286
final  value 83.363286 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.326220 
iter  10 value 94.468409
iter  20 value 86.855815
iter  30 value 85.501025
iter  40 value 84.724489
iter  50 value 83.806901
iter  60 value 83.044296
iter  70 value 82.604295
iter  80 value 82.224882
iter  90 value 81.850105
iter 100 value 81.784517
final  value 81.784517 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.179708 
iter  10 value 94.502424
iter  20 value 89.009305
iter  30 value 86.448513
iter  40 value 86.082000
iter  50 value 85.455370
iter  60 value 84.361139
iter  70 value 83.871238
iter  80 value 82.868502
iter  90 value 82.449796
iter 100 value 82.317854
final  value 82.317854 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.633859 
iter  10 value 94.139234
iter  20 value 86.111110
iter  30 value 85.477103
iter  40 value 85.284762
iter  50 value 83.654283
iter  60 value 82.455270
iter  70 value 82.114920
iter  80 value 81.973312
iter  90 value 81.552731
iter 100 value 81.244317
final  value 81.244317 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.807361 
iter  10 value 92.410115
iter  20 value 87.626690
iter  30 value 86.396355
iter  40 value 86.131639
iter  50 value 85.464540
iter  60 value 85.236713
iter  70 value 84.658076
iter  80 value 84.303110
iter  90 value 83.033151
iter 100 value 82.291008
final  value 82.291008 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.282507 
iter  10 value 94.752001
iter  20 value 87.114660
iter  30 value 85.581788
iter  40 value 85.000274
iter  50 value 83.654380
iter  60 value 82.679534
iter  70 value 82.477495
iter  80 value 82.191204
iter  90 value 81.533550
iter 100 value 81.448475
final  value 81.448475 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.720721 
final  value 94.485735 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.450969 
iter  10 value 94.486056
iter  20 value 94.484228
iter  30 value 92.707169
iter  40 value 88.963325
iter  50 value 88.923982
final  value 88.923867 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.075354 
final  value 94.468478 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.299556 
iter  10 value 94.486016
iter  20 value 94.375540
iter  30 value 92.247896
iter  40 value 92.238634
iter  50 value 92.238271
iter  50 value 92.238270
iter  50 value 92.238270
final  value 92.238270 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.670782 
final  value 94.468240 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.481617 
iter  10 value 93.161448
iter  20 value 88.867697
iter  30 value 88.864601
iter  40 value 88.861960
iter  50 value 88.596536
iter  60 value 88.561318
iter  70 value 86.333394
iter  80 value 85.758041
iter  90 value 85.753299
iter 100 value 85.752624
final  value 85.752624 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.502635 
iter  10 value 94.472023
iter  20 value 94.467341
final  value 94.467152 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.615005 
iter  10 value 94.611287
iter  20 value 94.603005
iter  30 value 94.415697
iter  40 value 92.014571
iter  50 value 91.926206
iter  60 value 85.289895
iter  70 value 84.765138
iter  80 value 84.479295
iter  90 value 84.278690
iter 100 value 84.239069
final  value 84.239069 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.359647 
iter  10 value 94.489152
iter  20 value 94.483773
iter  30 value 94.151756
iter  40 value 88.566340
iter  50 value 88.526672
iter  60 value 87.047101
iter  70 value 86.742035
final  value 86.709926 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.310478 
iter  10 value 94.488605
iter  20 value 94.037435
iter  30 value 92.221704
iter  40 value 91.962138
iter  50 value 91.909669
iter  60 value 84.194229
iter  70 value 84.010957
iter  80 value 83.896987
iter  90 value 83.881339
iter 100 value 82.539153
final  value 82.539153 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.167413 
iter  10 value 89.883403
iter  20 value 88.788534
iter  30 value 85.837995
iter  40 value 85.280924
iter  50 value 84.273608
iter  60 value 83.777851
iter  70 value 83.553835
iter  80 value 83.456698
final  value 83.455607 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.511115 
iter  10 value 94.475345
iter  20 value 94.470617
iter  30 value 94.469121
iter  40 value 94.466912
iter  50 value 94.281448
iter  60 value 89.277050
iter  70 value 84.700133
iter  80 value 84.115160
iter  90 value 82.753170
iter 100 value 81.515605
final  value 81.515605 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.309814 
iter  10 value 94.492430
iter  20 value 94.475107
iter  30 value 94.405445
iter  40 value 86.214137
iter  50 value 84.449407
iter  60 value 83.360855
iter  70 value 83.100122
iter  80 value 83.073764
iter  90 value 83.065076
iter 100 value 83.055940
final  value 83.055940 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.778224 
iter  10 value 90.887369
iter  20 value 90.689790
iter  30 value 89.919194
iter  40 value 89.055478
iter  50 value 88.906695
iter  60 value 88.887344
final  value 88.886927 
converged
Fitting Repeat 5 

# weights:  507
initial  value 130.066304 
iter  10 value 94.492686
iter  20 value 94.452948
iter  30 value 94.208581
iter  40 value 89.421063
iter  50 value 88.515054
iter  60 value 82.421892
iter  70 value 81.927751
iter  80 value 81.907505
iter  90 value 81.821755
iter 100 value 81.757032
final  value 81.757032 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.775832 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.024553 
iter  10 value 86.807207
iter  20 value 86.648320
iter  30 value 86.648245
final  value 86.648239 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.390135 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.503528 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.071117 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.204977 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.335704 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.306720 
iter  10 value 93.865571
final  value 93.798554 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.564442 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.912146 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.813421 
iter  10 value 92.043772
iter  20 value 86.046089
final  value 86.014293 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.288832 
iter  10 value 84.393713
iter  20 value 81.247073
iter  30 value 80.954829
iter  40 value 80.841964
final  value 80.841956 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.243812 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.978916 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.407502 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.629511 
iter  10 value 94.018759
iter  20 value 85.973603
iter  30 value 84.520339
iter  40 value 84.188129
iter  50 value 82.892089
iter  60 value 82.362861
iter  70 value 82.244081
iter  80 value 81.680676
iter  90 value 79.999802
iter 100 value 79.987103
final  value 79.987103 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.795975 
iter  10 value 94.057804
iter  20 value 92.963192
iter  30 value 85.097224
iter  40 value 82.673692
iter  50 value 81.916891
iter  60 value 81.127361
iter  70 value 80.969613
iter  80 value 80.588387
iter  90 value 80.357984
iter 100 value 80.050010
final  value 80.050010 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.351267 
iter  10 value 94.055873
iter  20 value 93.960336
iter  30 value 91.936096
iter  40 value 90.520909
iter  50 value 86.271925
iter  60 value 84.965137
iter  70 value 84.290017
iter  80 value 83.910160
iter  90 value 83.603586
iter 100 value 83.048738
final  value 83.048738 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.264198 
iter  10 value 94.060353
iter  20 value 94.055984
iter  30 value 93.606699
iter  40 value 91.447254
iter  50 value 87.347604
iter  60 value 86.444100
iter  70 value 85.911055
iter  80 value 85.881092
iter  90 value 85.863422
iter 100 value 85.665621
final  value 85.665621 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.750900 
iter  10 value 94.011163
iter  20 value 93.028933
iter  30 value 86.218534
iter  40 value 84.042975
iter  50 value 83.610196
iter  60 value 83.008387
iter  70 value 82.897052
iter  80 value 82.887816
iter  80 value 82.887815
iter  80 value 82.887815
final  value 82.887815 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.447086 
iter  10 value 94.376705
iter  20 value 91.684939
iter  30 value 89.843565
iter  40 value 88.037475
iter  50 value 84.806822
iter  60 value 83.499523
iter  70 value 81.266869
iter  80 value 80.491585
iter  90 value 80.086958
iter 100 value 80.032816
final  value 80.032816 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.231509 
iter  10 value 94.059549
iter  20 value 93.871635
iter  30 value 93.821448
iter  40 value 87.322331
iter  50 value 85.082247
iter  60 value 84.093772
iter  70 value 80.327241
iter  80 value 79.634868
iter  90 value 79.346809
iter 100 value 79.276236
final  value 79.276236 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.001871 
iter  10 value 93.928294
iter  20 value 90.472226
iter  30 value 85.333784
iter  40 value 82.472444
iter  50 value 81.168836
iter  60 value 80.224848
iter  70 value 79.214874
iter  80 value 78.981282
iter  90 value 78.933910
iter 100 value 78.742338
final  value 78.742338 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.653358 
iter  10 value 92.786553
iter  20 value 91.050049
iter  30 value 90.871468
iter  40 value 90.615271
iter  50 value 84.068948
iter  60 value 82.283744
iter  70 value 82.144711
iter  80 value 81.947378
iter  90 value 81.861562
iter 100 value 81.632337
final  value 81.632337 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 125.243154 
iter  10 value 94.022914
iter  20 value 87.030405
iter  30 value 84.629998
iter  40 value 83.943968
iter  50 value 83.641106
iter  60 value 83.104189
iter  70 value 82.960267
iter  80 value 80.626260
iter  90 value 78.849668
iter 100 value 78.694936
final  value 78.694936 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.391763 
iter  10 value 94.780036
iter  20 value 94.074789
iter  30 value 92.034113
iter  40 value 91.232481
iter  50 value 86.697444
iter  60 value 82.058670
iter  70 value 79.819029
iter  80 value 79.003083
iter  90 value 78.770226
iter 100 value 78.539708
final  value 78.539708 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 146.193067 
iter  10 value 93.851197
iter  20 value 84.930742
iter  30 value 84.517438
iter  40 value 80.678037
iter  50 value 79.883319
iter  60 value 79.727477
iter  70 value 79.567788
iter  80 value 79.483995
iter  90 value 79.282488
iter 100 value 78.832851
final  value 78.832851 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.920712 
iter  10 value 95.094056
iter  20 value 90.532370
iter  30 value 82.546740
iter  40 value 79.951860
iter  50 value 79.228292
iter  60 value 78.925869
iter  70 value 78.414576
iter  80 value 78.277667
iter  90 value 78.100192
iter 100 value 77.996971
final  value 77.996971 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.912583 
iter  10 value 94.209085
iter  20 value 93.966796
iter  30 value 92.348727
iter  40 value 85.593134
iter  50 value 85.277780
iter  60 value 83.179750
iter  70 value 80.794858
iter  80 value 79.300687
iter  90 value 78.493649
iter 100 value 78.226858
final  value 78.226858 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.757319 
iter  10 value 94.671648
iter  20 value 92.436132
iter  30 value 86.501369
iter  40 value 84.854316
iter  50 value 82.210347
iter  60 value 80.966333
iter  70 value 80.383889
iter  80 value 80.158622
iter  90 value 79.837170
iter 100 value 79.596863
final  value 79.596863 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.952388 
iter  10 value 94.073027
iter  20 value 94.053371
final  value 94.052914 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.413131 
final  value 94.054632 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.333255 
iter  10 value 94.054645
iter  20 value 94.052912
iter  20 value 94.052912
final  value 94.052912 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.022369 
final  value 94.054634 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.981297 
final  value 94.054495 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.005054 
iter  10 value 94.057626
iter  20 value 94.052280
iter  30 value 86.275313
iter  40 value 86.173891
iter  50 value 86.167366
iter  60 value 83.039092
iter  70 value 83.038495
iter  80 value 82.940608
iter  90 value 82.910338
final  value 82.905177 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.273942 
iter  10 value 94.057240
iter  20 value 91.721153
iter  30 value 83.102453
iter  40 value 83.006658
iter  50 value 82.838504
iter  60 value 82.834497
final  value 82.834421 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.648133 
iter  10 value 94.057484
iter  20 value 93.653931
iter  30 value 86.249551
iter  40 value 84.866087
iter  50 value 84.568992
final  value 84.568574 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.234531 
iter  10 value 94.037817
iter  20 value 94.033284
final  value 94.033036 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.475237 
iter  10 value 94.057724
iter  20 value 94.053093
iter  30 value 88.942245
iter  40 value 85.251145
iter  50 value 85.247255
iter  60 value 84.944241
iter  70 value 84.680263
iter  80 value 84.678985
final  value 84.676838 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.162540 
iter  10 value 94.061147
iter  20 value 94.048464
iter  30 value 91.619765
iter  40 value 91.616655
iter  50 value 91.611997
iter  60 value 91.089223
final  value 91.086541 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.929143 
iter  10 value 94.040816
iter  20 value 94.033808
iter  30 value 93.456167
iter  40 value 92.262893
final  value 92.262771 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.436922 
iter  10 value 93.636951
iter  20 value 93.636253
iter  30 value 93.634241
iter  40 value 86.227900
iter  50 value 86.157331
iter  60 value 83.045888
iter  70 value 82.870814
iter  80 value 82.870595
iter  90 value 82.448298
iter 100 value 81.022527
final  value 81.022527 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.202017 
iter  10 value 91.017532
iter  20 value 91.006513
iter  30 value 90.885368
iter  40 value 90.703453
iter  50 value 90.701703
iter  60 value 90.691637
iter  70 value 90.685969
iter  80 value 90.366405
iter  90 value 89.932403
iter 100 value 89.549579
final  value 89.549579 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.002225 
iter  10 value 89.372952
iter  20 value 82.622477
iter  30 value 81.766480
iter  40 value 81.322304
final  value 81.321808 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.130305 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.426347 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.407950 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.886393 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.372690 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.952481 
iter  10 value 87.218311
iter  20 value 85.070764
iter  30 value 84.979559
iter  40 value 84.972292
final  value 84.972265 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.962460 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 127.247869 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.540229 
iter  10 value 93.401960
iter  20 value 93.352243
iter  30 value 93.343375
final  value 93.343341 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.244768 
iter  10 value 88.855300
iter  20 value 87.698470
iter  30 value 87.602294
iter  40 value 87.565479
iter  50 value 87.563021
final  value 87.562999 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.720395 
final  value 93.671508 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.002159 
final  value 93.900000 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.681026 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.808593 
iter  10 value 93.361941
iter  20 value 93.109854
iter  30 value 92.985556
iter  40 value 92.985080
iter  40 value 92.985080
final  value 92.985080 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.970618 
iter  10 value 92.170929
iter  20 value 89.758758
iter  30 value 89.391315
iter  40 value 89.263987
iter  40 value 89.263986
iter  40 value 89.263986
final  value 89.263986 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.178423 
iter  10 value 94.032558
iter  20 value 92.647483
iter  30 value 92.364462
iter  40 value 88.309076
iter  50 value 87.379825
iter  60 value 86.902763
iter  70 value 86.848204
iter  80 value 83.191986
iter  90 value 82.990033
iter 100 value 82.760746
final  value 82.760746 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 111.208707 
iter  10 value 93.112905
iter  20 value 85.994363
iter  30 value 84.708245
iter  40 value 84.239453
iter  50 value 83.899271
iter  60 value 83.455355
iter  70 value 83.399355
iter  80 value 82.702284
iter  90 value 81.671060
iter 100 value 81.660818
final  value 81.660818 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.304081 
iter  10 value 94.059522
iter  20 value 93.838539
iter  30 value 93.443247
iter  40 value 93.094973
iter  50 value 87.251102
iter  60 value 86.883498
iter  70 value 85.479678
iter  80 value 85.017435
iter  90 value 84.148198
iter 100 value 82.417549
final  value 82.417549 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.096385 
iter  10 value 94.063566
iter  20 value 85.842001
iter  30 value 85.104304
iter  40 value 84.055348
iter  50 value 83.885710
iter  60 value 83.856124
final  value 83.855693 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.590449 
iter  10 value 94.028961
iter  20 value 92.254652
iter  30 value 87.796635
iter  40 value 86.048041
iter  50 value 85.090760
iter  60 value 83.907856
iter  70 value 82.994199
iter  80 value 82.114601
iter  90 value 82.052728
iter 100 value 81.753649
final  value 81.753649 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.145530 
iter  10 value 94.077697
iter  20 value 94.011506
iter  30 value 87.209955
iter  40 value 84.290945
iter  50 value 83.602781
iter  60 value 81.954807
iter  70 value 80.891948
iter  80 value 80.624082
iter  90 value 80.435168
iter 100 value 80.241280
final  value 80.241280 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.528046 
iter  10 value 85.602452
iter  20 value 83.598649
iter  30 value 81.986706
iter  40 value 81.454919
iter  50 value 80.894694
iter  60 value 80.779002
iter  70 value 80.690688
iter  80 value 80.666366
iter  90 value 80.643166
iter 100 value 80.589974
final  value 80.589974 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.570082 
iter  10 value 94.056306
iter  20 value 91.857367
iter  30 value 85.072112
iter  40 value 84.512244
iter  50 value 84.009725
iter  60 value 82.637308
iter  70 value 81.178917
iter  80 value 80.891789
iter  90 value 80.366848
iter 100 value 80.099392
final  value 80.099392 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.135123 
iter  10 value 94.190263
iter  20 value 93.508693
iter  30 value 92.244867
iter  40 value 89.175379
iter  50 value 84.675885
iter  60 value 82.032941
iter  70 value 81.159433
iter  80 value 80.819226
iter  90 value 80.449820
iter 100 value 80.276420
final  value 80.276420 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.876441 
iter  10 value 93.984558
iter  20 value 89.843302
iter  30 value 86.062478
iter  40 value 85.041445
iter  50 value 83.458733
iter  60 value 82.767506
iter  70 value 82.117761
iter  80 value 80.971011
iter  90 value 80.702532
iter 100 value 80.571526
final  value 80.571526 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.098674 
iter  10 value 93.759737
iter  20 value 90.398301
iter  30 value 86.609253
iter  40 value 83.174241
iter  50 value 82.213519
iter  60 value 81.535678
iter  70 value 80.980243
iter  80 value 80.700736
iter  90 value 80.546646
iter 100 value 80.471589
final  value 80.471589 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.097432 
iter  10 value 92.701314
iter  20 value 85.612964
iter  30 value 84.342230
iter  40 value 83.919931
iter  50 value 83.320975
iter  60 value 83.081837
iter  70 value 83.021032
iter  80 value 82.976226
iter  90 value 82.623012
iter 100 value 81.585856
final  value 81.585856 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 144.436818 
iter  10 value 107.143922
iter  20 value 94.718927
iter  30 value 89.937987
iter  40 value 87.595064
iter  50 value 86.751725
iter  60 value 84.735652
iter  70 value 84.133567
iter  80 value 83.482038
iter  90 value 82.215867
iter 100 value 80.910394
final  value 80.910394 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.601815 
iter  10 value 94.294970
iter  20 value 93.781548
iter  30 value 90.987044
iter  40 value 89.304048
iter  50 value 86.029149
iter  60 value 84.631769
iter  70 value 83.043599
iter  80 value 81.300115
iter  90 value 80.513541
iter 100 value 80.282077
final  value 80.282077 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 131.930209 
iter  10 value 94.184661
iter  20 value 92.929943
iter  30 value 88.992843
iter  40 value 86.527116
iter  50 value 85.765961
iter  60 value 85.363124
iter  70 value 85.276577
iter  80 value 83.944954
iter  90 value 83.707869
iter 100 value 82.690513
final  value 82.690513 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.539166 
final  value 94.054553 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.627600 
final  value 94.055494 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.232398 
final  value 94.054406 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.135836 
final  value 94.054625 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.302517 
final  value 94.054758 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.720220 
iter  10 value 94.061835
iter  20 value 94.017322
iter  30 value 93.581108
iter  40 value 93.578467
iter  50 value 93.552701
iter  60 value 92.245580
iter  70 value 85.029752
iter  80 value 83.138382
iter  90 value 83.012308
final  value 83.012098 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.772908 
iter  10 value 94.057796
iter  20 value 94.027495
iter  30 value 93.584179
iter  40 value 93.583651
iter  50 value 93.582954
final  value 93.582852 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.797917 
iter  10 value 93.580191
iter  20 value 93.577595
iter  30 value 90.911295
iter  40 value 84.335401
iter  50 value 84.204283
iter  60 value 83.526961
iter  70 value 83.085009
iter  70 value 83.085008
iter  70 value 83.085008
final  value 83.085008 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.301973 
iter  10 value 93.587642
iter  20 value 93.544367
iter  30 value 92.073315
iter  40 value 85.520370
iter  50 value 85.192956
iter  60 value 84.998037
final  value 84.965497 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.139556 
iter  10 value 94.055772
iter  20 value 94.045689
final  value 93.602928 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.035296 
iter  10 value 93.591388
iter  20 value 93.585707
iter  30 value 93.579513
iter  40 value 93.459556
iter  50 value 93.330764
iter  60 value 93.330408
final  value 93.330388 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.458544 
iter  10 value 94.059910
iter  20 value 93.858574
iter  30 value 89.098861
iter  40 value 88.953889
iter  50 value 88.899434
iter  60 value 88.888344
iter  70 value 86.198232
iter  80 value 86.118747
iter  90 value 86.113681
iter 100 value 84.849727
final  value 84.849727 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.766256 
iter  10 value 94.061388
iter  20 value 94.018031
iter  30 value 91.050572
iter  40 value 84.053781
iter  50 value 82.877452
iter  60 value 82.805163
iter  70 value 82.409626
iter  80 value 82.355969
final  value 82.355911 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.738493 
iter  10 value 94.059346
iter  20 value 91.888297
iter  30 value 89.807243
iter  40 value 85.298742
iter  50 value 85.270558
iter  60 value 84.772162
iter  70 value 84.766265
iter  80 value 84.765094
iter  90 value 84.383057
iter 100 value 84.110253
final  value 84.110253 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.600593 
iter  10 value 94.060658
iter  20 value 94.053244
iter  30 value 94.052913
iter  30 value 94.052912
iter  30 value 94.052912
final  value 94.052912 
converged
Fitting Repeat 1 

# weights:  305
initial  value 135.944876 
iter  10 value 117.895191
iter  20 value 117.862454
iter  30 value 108.949157
iter  40 value 105.523564
iter  50 value 105.369176
iter  60 value 105.136563
iter  70 value 103.615190
iter  80 value 101.727626
iter  90 value 99.684098
iter 100 value 99.268829
final  value 99.268829 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 136.864713 
iter  10 value 117.899782
iter  20 value 117.894949
iter  30 value 116.352541
iter  40 value 108.547093
iter  50 value 108.538786
iter  60 value 105.364169
iter  70 value 105.361360
iter  80 value 105.360729
iter  90 value 105.149582
iter 100 value 104.973580
final  value 104.973580 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.897452 
iter  10 value 111.164897
iter  20 value 108.577011
iter  30 value 108.531127
iter  40 value 107.316192
iter  50 value 107.051448
iter  60 value 107.045013
iter  70 value 106.833811
final  value 106.828636 
converged
Fitting Repeat 4 

# weights:  305
initial  value 123.742794 
iter  10 value 117.895047
iter  20 value 117.826864
iter  30 value 114.735285
iter  40 value 108.538600
iter  50 value 107.197484
iter  60 value 107.191873
iter  70 value 107.167532
final  value 107.166521 
converged
Fitting Repeat 5 

# weights:  305
initial  value 124.742103 
iter  10 value 117.894470
final  value 117.890435 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Feb  7 04:45:50 2023 
*********************************************** 
Number of test functions: 8 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures
Number of test functions: 8 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: The `.data` argument of `add_column()` must have unique names as of tibble
3.0.0.
ℹ Use `.name_repair = "minimal"`.
ℹ The deprecated feature was likely used in the tibble package.
  Please report the issue at <https://github.com/tidyverse/tibble/issues>. 
2: `repeats` has no meaning for this resampling method. 
3: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 53.776   0.735 103.515