##############################################################################
##############################################################################
###
### 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       38.415  0.692  39.108
corr_plot     38.216  0.415  38.638
FSmethod      37.915  0.548  38.475
pred_ensembel 18.420  0.517  16.636
getFASTA       0.721  0.024   9.702
enrichfindP    0.407  0.057  15.516
* 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 95.106056 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.863277 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.858079 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.672524 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.899952 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.272685 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.107353 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  305
initial  value 124.748809 
iter  10 value 93.353684
iter  20 value 93.301806
final  value 93.301233 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.913504 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.801093 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.518421 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.991632 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.015821 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.950097 
iter  10 value 93.582423
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.914877 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.635982 
iter  10 value 87.781512
iter  20 value 83.204306
iter  30 value 82.953612
iter  40 value 82.271983
iter  50 value 82.192194
iter  60 value 82.170883
iter  70 value 82.148930
iter  70 value 82.148930
iter  70 value 82.148930
final  value 82.148930 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.000246 
iter  10 value 94.017945
iter  20 value 87.631563
iter  30 value 85.720360
iter  40 value 83.607638
iter  50 value 81.529292
iter  60 value 81.180997
iter  70 value 80.622386
iter  80 value 80.458249
iter  90 value 80.373732
iter 100 value 80.326536
final  value 80.326536 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.177917 
iter  10 value 94.055127
iter  20 value 94.054596
iter  30 value 93.581638
iter  40 value 86.095994
iter  50 value 82.173300
iter  60 value 82.064797
iter  70 value 81.587932
iter  80 value 80.376222
iter  90 value 80.226587
iter 100 value 80.213654
final  value 80.213654 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.386557 
iter  10 value 91.076340
iter  20 value 85.599114
iter  30 value 83.100849
iter  40 value 82.012857
iter  50 value 81.951349
iter  60 value 81.907919
final  value 81.907881 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.042181 
iter  10 value 92.951826
iter  20 value 83.960745
iter  30 value 82.853294
iter  40 value 81.994843
iter  50 value 81.957444
iter  60 value 81.913306
iter  70 value 81.909034
final  value 81.907881 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.008242 
iter  10 value 94.051236
iter  20 value 83.725844
iter  30 value 82.923623
iter  40 value 82.135409
iter  50 value 81.139078
iter  60 value 80.143197
iter  70 value 79.517460
iter  80 value 79.121815
iter  90 value 79.011210
iter 100 value 79.003988
final  value 79.003988 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.756585 
iter  10 value 94.055172
iter  20 value 93.714639
iter  30 value 84.190895
iter  40 value 83.886904
iter  50 value 83.136652
iter  60 value 82.108828
iter  70 value 81.969178
iter  80 value 81.684490
iter  90 value 80.930848
iter 100 value 79.763116
final  value 79.763116 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.461459 
iter  10 value 94.008368
iter  20 value 93.470656
iter  30 value 93.284597
iter  40 value 88.916556
iter  50 value 83.778046
iter  60 value 81.394303
iter  70 value 81.073677
iter  80 value 80.507337
iter  90 value 79.551167
iter 100 value 79.039968
final  value 79.039968 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.655450 
iter  10 value 93.971822
iter  20 value 93.539279
iter  30 value 93.498273
iter  40 value 93.075038
iter  50 value 85.681366
iter  60 value 82.945921
iter  70 value 82.203868
iter  80 value 80.918053
iter  90 value 80.409614
iter 100 value 79.847359
final  value 79.847359 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.090512 
iter  10 value 93.543256
iter  20 value 91.956001
iter  30 value 84.846924
iter  40 value 81.767837
iter  50 value 80.239363
iter  60 value 78.674230
iter  70 value 78.362853
iter  80 value 78.259142
iter  90 value 78.230268
iter 100 value 78.214196
final  value 78.214196 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 137.166889 
iter  10 value 95.625874
iter  20 value 93.558083
iter  30 value 93.044353
iter  40 value 85.861150
iter  50 value 82.124663
iter  60 value 81.421761
iter  70 value 80.576088
iter  80 value 80.016840
iter  90 value 79.688713
iter 100 value 79.421041
final  value 79.421041 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.238034 
iter  10 value 89.649857
iter  20 value 84.475455
iter  30 value 79.932730
iter  40 value 79.068586
iter  50 value 78.636269
iter  60 value 78.375928
iter  70 value 78.348987
iter  80 value 78.239639
iter  90 value 78.221719
iter 100 value 78.166131
final  value 78.166131 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.879229 
iter  10 value 94.610781
iter  20 value 87.276398
iter  30 value 86.786766
iter  40 value 83.271088
iter  50 value 82.902107
iter  60 value 82.844255
iter  70 value 80.709736
iter  80 value 80.360640
iter  90 value 79.407312
iter 100 value 79.322318
final  value 79.322318 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.358105 
iter  10 value 95.195825
iter  20 value 91.139999
iter  30 value 86.042196
iter  40 value 82.925420
iter  50 value 82.201501
iter  60 value 81.847776
iter  70 value 81.078677
iter  80 value 80.027641
iter  90 value 79.787197
iter 100 value 79.624571
final  value 79.624571 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.954480 
iter  10 value 92.968885
iter  20 value 84.946855
iter  30 value 82.006327
iter  40 value 81.766107
iter  50 value 81.106437
iter  60 value 80.785153
iter  70 value 80.529347
iter  80 value 80.296989
iter  90 value 79.967678
iter 100 value 79.251914
final  value 79.251914 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.600815 
iter  10 value 94.054535
iter  20 value 93.380657
iter  30 value 86.821543
iter  40 value 86.377044
final  value 86.367518 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.603904 
final  value 94.054639 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.506550 
final  value 94.054548 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.996553 
iter  10 value 94.054492
final  value 94.052964 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.463900 
final  value 94.055456 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.181220 
iter  10 value 90.343761
iter  20 value 90.342145
iter  30 value 90.340702
iter  40 value 90.340203
iter  50 value 90.339348
iter  60 value 90.113227
iter  70 value 90.049296
iter  80 value 90.048668
iter  90 value 90.048496
iter 100 value 90.047946
final  value 90.047946 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.182491 
iter  10 value 87.700637
iter  20 value 83.808185
iter  30 value 82.714214
iter  40 value 82.698851
iter  50 value 82.697633
iter  60 value 80.666972
iter  70 value 80.404975
iter  80 value 79.844556
iter  90 value 79.806334
iter 100 value 79.730010
final  value 79.730010 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.857253 
iter  10 value 94.058068
iter  20 value 94.053155
iter  30 value 93.630280
iter  40 value 82.879370
iter  50 value 82.072388
iter  60 value 82.071747
iter  70 value 82.071110
final  value 82.070854 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.073441 
iter  10 value 93.308990
iter  20 value 93.300411
iter  30 value 91.132469
iter  40 value 90.438881
iter  50 value 90.438344
iter  60 value 88.409211
iter  70 value 86.075354
iter  80 value 82.207138
iter  90 value 82.149501
iter 100 value 82.147640
final  value 82.147640 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 127.558383 
iter  10 value 93.588586
iter  20 value 93.584464
iter  30 value 87.702110
iter  40 value 84.235869
iter  50 value 84.191786
iter  60 value 84.190840
final  value 84.190408 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.585976 
iter  10 value 93.385876
iter  20 value 93.330978
iter  30 value 93.302025
final  value 93.301964 
converged
Fitting Repeat 2 

# weights:  507
initial  value 129.125650 
iter  10 value 94.060253
iter  20 value 92.705824
iter  30 value 83.173478
iter  40 value 80.337591
iter  50 value 79.434721
iter  60 value 79.395122
final  value 79.394098 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.590091 
iter  10 value 94.061494
iter  20 value 94.052952
iter  30 value 85.753290
iter  40 value 85.412131
iter  50 value 84.823946
iter  60 value 83.855385
iter  70 value 83.853132
iter  80 value 83.013975
iter  90 value 82.037287
iter 100 value 81.640351
final  value 81.640351 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.330901 
iter  10 value 90.514794
iter  20 value 90.000525
iter  30 value 86.121286
iter  40 value 85.617702
iter  50 value 85.187935
iter  60 value 85.110103
iter  70 value 85.108479
iter  80 value 85.095824
iter  90 value 81.814326
iter 100 value 80.987801
final  value 80.987801 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.591164 
iter  10 value 93.463584
iter  20 value 93.430468
iter  30 value 93.342807
iter  40 value 82.307277
iter  50 value 81.652122
iter  60 value 81.247993
iter  70 value 81.236771
iter  80 value 80.985415
final  value 80.985404 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.309572 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.470848 
iter  10 value 93.728134
final  value 93.714286 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.127233 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.521245 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.787212 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.167920 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.727776 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 91.096934 
iter  10 value 84.838644
iter  20 value 81.086030
iter  30 value 79.151199
iter  40 value 79.082810
final  value 79.080232 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.725371 
final  value 93.944596 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.866453 
iter  10 value 93.722226
final  value 93.722224 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.605160 
final  value 93.671509 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.079632 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.694654 
iter  10 value 89.574308
iter  20 value 83.781393
iter  30 value 82.075941
iter  40 value 81.984381
final  value 81.984066 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.047144 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.931431 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.231658 
iter  10 value 93.869139
iter  20 value 88.922317
iter  30 value 84.194474
iter  40 value 83.859084
iter  50 value 79.973688
iter  60 value 79.661345
iter  70 value 79.628760
iter  80 value 79.394149
iter  90 value 79.206324
final  value 79.205831 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.293138 
iter  10 value 94.060126
iter  20 value 94.053538
iter  30 value 93.459769
iter  40 value 85.470496
iter  50 value 83.253745
iter  60 value 81.774082
iter  70 value 80.638071
iter  80 value 80.390620
iter  90 value 80.363007
final  value 80.362840 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.390187 
iter  10 value 94.059615
iter  20 value 87.444957
iter  30 value 85.108093
iter  40 value 83.706199
iter  50 value 83.222143
iter  60 value 83.050185
iter  70 value 82.650420
final  value 82.649796 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.733326 
iter  10 value 94.053414
iter  20 value 83.070643
iter  30 value 82.158889
iter  40 value 82.100939
iter  50 value 82.085793
final  value 82.085008 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.353484 
iter  10 value 94.054862
iter  20 value 88.903564
iter  30 value 85.559826
iter  40 value 85.185299
iter  50 value 84.935175
iter  60 value 84.695477
iter  70 value 83.881905
iter  80 value 83.363218
iter  90 value 82.701643
iter 100 value 82.663004
final  value 82.663004 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.770045 
iter  10 value 94.076295
iter  20 value 92.002141
iter  30 value 86.256977
iter  40 value 85.435680
iter  50 value 82.820971
iter  60 value 81.046506
iter  70 value 79.561144
iter  80 value 78.599703
iter  90 value 78.357857
iter 100 value 78.291962
final  value 78.291962 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.012546 
iter  10 value 94.573581
iter  20 value 94.037750
iter  30 value 93.929023
iter  40 value 85.308180
iter  50 value 83.477709
iter  60 value 81.724560
iter  70 value 79.722410
iter  80 value 79.516269
iter  90 value 79.389711
iter 100 value 79.311886
final  value 79.311886 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.135857 
iter  10 value 93.018593
iter  20 value 83.438768
iter  30 value 82.400388
iter  40 value 82.172836
iter  50 value 81.374341
iter  60 value 79.739131
iter  70 value 79.379719
iter  80 value 78.986842
iter  90 value 78.502543
iter 100 value 78.119693
final  value 78.119693 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.160393 
iter  10 value 94.520006
iter  20 value 93.791902
iter  30 value 90.938980
iter  40 value 89.247039
iter  50 value 88.661921
iter  60 value 88.015268
iter  70 value 85.236544
iter  80 value 84.562420
iter  90 value 82.649766
iter 100 value 78.993242
final  value 78.993242 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.994363 
iter  10 value 94.287456
iter  20 value 93.982295
iter  30 value 86.286636
iter  40 value 85.007039
iter  50 value 82.439552
iter  60 value 81.745791
iter  70 value 80.874793
iter  80 value 80.709262
iter  90 value 80.467141
iter 100 value 80.316801
final  value 80.316801 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.833804 
iter  10 value 93.931877
iter  20 value 88.469033
iter  30 value 87.073373
iter  40 value 86.736370
iter  50 value 82.442341
iter  60 value 81.046085
iter  70 value 80.499029
iter  80 value 80.451014
iter  90 value 80.349226
iter 100 value 80.265112
final  value 80.265112 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.143497 
iter  10 value 93.743684
iter  20 value 84.421221
iter  30 value 83.818792
iter  40 value 82.796212
iter  50 value 81.270413
iter  60 value 80.777887
iter  70 value 80.717837
iter  80 value 79.701930
iter  90 value 79.363481
iter 100 value 78.767647
final  value 78.767647 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.965963 
iter  10 value 94.783189
iter  20 value 84.630072
iter  30 value 83.705539
iter  40 value 81.274848
iter  50 value 78.327299
iter  60 value 77.883693
iter  70 value 77.684327
iter  80 value 77.523345
iter  90 value 77.320266
iter 100 value 77.237236
final  value 77.237236 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.426368 
iter  10 value 92.545755
iter  20 value 83.109643
iter  30 value 81.835651
iter  40 value 81.337135
iter  50 value 80.386961
iter  60 value 79.870983
iter  70 value 79.635942
iter  80 value 79.087420
iter  90 value 78.374001
iter 100 value 78.191350
final  value 78.191350 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.197547 
iter  10 value 90.747681
iter  20 value 84.062349
iter  30 value 80.133168
iter  40 value 79.473496
iter  50 value 78.660679
iter  60 value 78.480668
iter  70 value 78.351183
iter  80 value 78.173900
iter  90 value 78.021961
iter 100 value 77.942831
final  value 77.942831 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.617893 
final  value 94.054509 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.726318 
final  value 94.054661 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.265206 
iter  10 value 93.962973
iter  20 value 90.609017
iter  30 value 85.865905
iter  40 value 85.853343
iter  50 value 85.502711
iter  60 value 85.372009
iter  70 value 85.371802
iter  70 value 85.371801
iter  70 value 85.371801
final  value 85.371801 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.223866 
final  value 94.054484 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.300578 
iter  10 value 94.055459
iter  20 value 94.052914
iter  30 value 87.626368
iter  40 value 87.457822
iter  50 value 82.596966
iter  60 value 81.641075
iter  70 value 81.322773
iter  80 value 81.314405
iter  90 value 81.310144
final  value 81.309964 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.904570 
final  value 94.057660 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.965877 
iter  10 value 93.826761
iter  20 value 93.823182
iter  30 value 93.479871
iter  40 value 93.476890
iter  50 value 93.419127
iter  60 value 93.418181
iter  70 value 93.385174
iter  80 value 93.383301
iter  90 value 93.325821
iter 100 value 86.653390
final  value 86.653390 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.636038 
iter  10 value 87.556299
iter  20 value 83.241501
iter  30 value 81.989921
iter  40 value 80.093830
iter  50 value 79.405243
iter  60 value 79.363345
iter  70 value 79.361431
iter  80 value 79.358404
iter  90 value 79.356281
iter 100 value 79.299252
final  value 79.299252 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.030808 
iter  10 value 94.057206
iter  20 value 93.979484
iter  30 value 92.982978
iter  40 value 92.962399
iter  50 value 92.566783
iter  60 value 92.562981
final  value 92.562943 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.461041 
iter  10 value 94.013556
iter  20 value 94.010394
iter  30 value 93.792099
iter  40 value 87.167806
iter  50 value 85.815631
iter  60 value 85.646190
final  value 85.609962 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.565043 
iter  10 value 93.673077
iter  20 value 93.650450
iter  30 value 93.567691
iter  40 value 92.393324
iter  50 value 81.263065
iter  60 value 79.044762
iter  70 value 78.843522
iter  80 value 78.582691
iter  90 value 78.242173
iter 100 value 78.184788
final  value 78.184788 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.713951 
iter  10 value 94.016856
iter  20 value 93.894144
iter  30 value 93.671876
iter  30 value 93.671876
iter  30 value 93.671876
final  value 93.671876 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.556079 
iter  10 value 93.722255
iter  20 value 90.280023
iter  30 value 81.311958
final  value 81.311718 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.906343 
iter  10 value 94.014283
iter  20 value 93.962686
iter  30 value 93.949989
iter  40 value 93.945394
iter  50 value 93.943809
iter  60 value 86.914165
iter  70 value 85.352508
iter  80 value 79.890923
iter  90 value 79.833100
iter 100 value 79.827456
final  value 79.827456 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.198102 
iter  10 value 94.016541
iter  20 value 94.009634
iter  30 value 93.541246
iter  40 value 91.963353
iter  50 value 91.953282
iter  60 value 91.953060
final  value 91.953054 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.784157 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.238478 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.847799 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.616131 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.767718 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.864918 
iter  10 value 87.705521
final  value 87.590732 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.914412 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.921275 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.002804 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.395062 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.520860 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.611595 
iter  10 value 94.466590
final  value 94.466580 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.215855 
iter  10 value 94.467370
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.192654 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.924051 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.996152 
iter  10 value 90.044354
iter  20 value 85.808866
iter  30 value 85.615795
iter  40 value 85.559965
iter  50 value 85.463044
iter  60 value 85.460386
final  value 85.460369 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.114053 
iter  10 value 94.488947
iter  20 value 93.954117
iter  30 value 93.870625
iter  40 value 93.835527
iter  50 value 92.225338
iter  60 value 84.892461
iter  70 value 83.922290
iter  80 value 83.809353
iter  90 value 83.531879
iter 100 value 83.403862
final  value 83.403862 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.846681 
iter  10 value 94.459141
iter  20 value 88.808197
iter  30 value 87.102651
iter  40 value 86.782274
iter  50 value 85.824365
iter  60 value 85.494777
iter  70 value 85.451025
iter  80 value 85.278151
iter  90 value 85.195102
final  value 85.192346 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.150828 
iter  10 value 94.076193
iter  20 value 91.146059
iter  30 value 87.246313
iter  40 value 86.880655
iter  50 value 86.550760
iter  60 value 85.742733
iter  70 value 85.537890
iter  80 value 85.486215
iter  90 value 85.405878
iter 100 value 85.340098
final  value 85.340098 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.196220 
iter  10 value 94.527697
iter  20 value 93.920175
iter  30 value 86.848463
iter  40 value 85.716400
iter  50 value 85.566668
iter  60 value 84.472846
iter  70 value 83.565636
iter  80 value 83.251329
final  value 83.231462 
converged
Fitting Repeat 1 

# weights:  305
initial  value 137.928402 
iter  10 value 95.392340
iter  20 value 92.911936
iter  30 value 88.846131
iter  40 value 87.109284
iter  50 value 86.735800
iter  60 value 85.337912
iter  70 value 84.714701
iter  80 value 83.835087
iter  90 value 83.644221
iter 100 value 83.381188
final  value 83.381188 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.040278 
iter  10 value 94.556462
iter  20 value 94.410964
iter  30 value 91.851859
iter  40 value 88.401661
iter  50 value 86.665411
iter  60 value 85.846225
iter  70 value 85.744453
iter  80 value 84.928303
iter  90 value 84.145593
iter 100 value 83.056826
final  value 83.056826 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.946567 
iter  10 value 94.484904
iter  20 value 88.644542
iter  30 value 87.831463
iter  40 value 87.277364
iter  50 value 86.109886
iter  60 value 85.757402
iter  70 value 85.485636
iter  80 value 84.757156
iter  90 value 83.559838
iter 100 value 83.223195
final  value 83.223195 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.386817 
iter  10 value 94.475421
iter  20 value 92.640758
iter  30 value 92.425172
iter  40 value 89.822505
iter  50 value 86.062756
iter  60 value 85.628190
iter  70 value 85.416638
iter  80 value 85.077894
iter  90 value 84.342944
iter 100 value 83.449847
final  value 83.449847 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.067590 
iter  10 value 94.465383
iter  20 value 93.404594
iter  30 value 93.263085
iter  40 value 86.511971
iter  50 value 86.207733
iter  60 value 85.992766
iter  70 value 85.128367
iter  80 value 84.372763
iter  90 value 83.898872
iter 100 value 83.686642
final  value 83.686642 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.843040 
iter  10 value 92.492482
iter  20 value 86.792671
iter  30 value 85.968564
iter  40 value 84.849899
iter  50 value 83.343054
iter  60 value 83.205971
iter  70 value 83.155123
iter  80 value 82.655258
iter  90 value 82.256397
iter 100 value 82.041413
final  value 82.041413 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.790205 
iter  10 value 94.395931
iter  20 value 89.736891
iter  30 value 85.468598
iter  40 value 84.721022
iter  50 value 84.041142
iter  60 value 83.121892
iter  70 value 82.738200
iter  80 value 82.672677
iter  90 value 82.487800
iter 100 value 82.287864
final  value 82.287864 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.880765 
iter  10 value 94.766434
iter  20 value 94.254988
iter  30 value 92.152267
iter  40 value 90.772834
iter  50 value 88.083319
iter  60 value 85.467725
iter  70 value 84.311587
iter  80 value 82.912245
iter  90 value 82.375253
iter 100 value 82.070113
final  value 82.070113 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.290265 
iter  10 value 94.167621
iter  20 value 90.112091
iter  30 value 87.222852
iter  40 value 86.491898
iter  50 value 85.955782
iter  60 value 84.614689
iter  70 value 84.019006
iter  80 value 83.591159
iter  90 value 83.381127
iter 100 value 83.230522
final  value 83.230522 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.931126 
iter  10 value 94.360839
iter  20 value 92.572985
iter  30 value 92.513901
iter  40 value 92.175227
iter  50 value 88.338155
iter  60 value 86.305854
iter  70 value 85.876951
iter  80 value 85.013081
iter  90 value 84.404255
iter 100 value 83.745039
final  value 83.745039 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.233360 
iter  10 value 94.485632
iter  20 value 94.471334
iter  30 value 88.827115
iter  40 value 88.466840
iter  50 value 88.316662
final  value 88.316502 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.073649 
final  value 94.485793 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.213087 
final  value 94.486106 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.467268 
final  value 94.468420 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.121822 
final  value 94.485912 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.000578 
iter  10 value 94.486662
iter  20 value 94.078790
iter  30 value 87.768945
iter  40 value 87.417425
iter  50 value 87.301895
iter  60 value 87.269594
iter  70 value 87.269531
final  value 87.269529 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.131853 
iter  10 value 94.488912
iter  20 value 94.449492
iter  30 value 87.892674
iter  40 value 87.353220
iter  50 value 87.339469
iter  60 value 87.337096
iter  70 value 87.331680
iter  80 value 86.750796
iter  90 value 86.644490
iter 100 value 86.642586
final  value 86.642586 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.837076 
iter  10 value 94.489067
iter  20 value 94.479661
iter  30 value 92.722994
iter  40 value 89.407373
iter  50 value 89.406307
iter  60 value 89.301156
iter  70 value 89.288655
iter  80 value 89.288543
final  value 89.288528 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.647744 
iter  10 value 94.489019
iter  20 value 94.428923
iter  30 value 87.578157
iter  40 value 87.532178
iter  50 value 87.000956
iter  60 value 86.386859
iter  70 value 85.699571
iter  80 value 85.698923
iter  90 value 85.696199
final  value 85.695896 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.773765 
iter  10 value 94.431472
iter  20 value 94.428319
iter  30 value 94.424272
iter  40 value 94.031984
iter  50 value 93.698227
iter  60 value 88.339201
iter  70 value 87.292127
iter  80 value 84.197929
iter  90 value 82.780949
iter 100 value 82.514928
final  value 82.514928 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.852855 
iter  10 value 94.544271
iter  20 value 94.462207
iter  30 value 91.610098
iter  40 value 87.691427
iter  50 value 87.538104
iter  60 value 87.513576
iter  70 value 87.499970
iter  80 value 85.408336
iter  90 value 85.068774
iter 100 value 85.059137
final  value 85.059137 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.345991 
iter  10 value 94.474631
iter  20 value 94.335011
iter  30 value 89.804546
iter  40 value 84.854270
iter  50 value 84.539262
iter  60 value 84.525972
iter  70 value 84.510378
final  value 84.510310 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.306389 
iter  10 value 94.484532
iter  20 value 94.213949
iter  30 value 86.711738
iter  40 value 86.556667
iter  50 value 86.549412
iter  60 value 86.549006
final  value 86.547776 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.895566 
iter  10 value 94.492386
iter  20 value 94.476248
iter  30 value 93.702951
final  value 93.702940 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.928448 
iter  10 value 94.473146
iter  20 value 92.095316
final  value 91.907812 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.568229 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.403834 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.261373 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.098333 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.574727 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.865691 
iter  10 value 93.956631
iter  20 value 93.918057
final  value 93.918040 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.300910 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.576720 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.387439 
iter  10 value 92.316148
iter  20 value 88.133414
iter  30 value 87.799779
iter  40 value 87.589861
iter  50 value 87.588902
final  value 87.588893 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.966021 
final  value 94.461539 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.515846 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.121374 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.884301 
final  value 94.482932 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.367778 
final  value 94.449438 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.540087 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.787916 
iter  10 value 94.491347
iter  20 value 92.955590
iter  30 value 87.531684
iter  40 value 87.375333
iter  50 value 87.257281
iter  60 value 87.195964
iter  70 value 86.543549
iter  80 value 85.926817
iter  90 value 85.831913
iter 100 value 85.342875
final  value 85.342875 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 109.693461 
iter  10 value 94.345737
iter  20 value 91.395663
iter  30 value 91.011213
iter  40 value 87.101238
iter  50 value 87.022212
iter  60 value 86.915006
iter  70 value 86.716416
iter  80 value 86.088742
iter  90 value 85.462714
iter 100 value 84.463768
final  value 84.463768 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.772803 
iter  10 value 94.287180
iter  20 value 90.451248
iter  30 value 88.611372
iter  40 value 87.792260
iter  50 value 86.036738
iter  60 value 84.392621
iter  70 value 83.915023
iter  80 value 83.803801
final  value 83.803790 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.335193 
iter  10 value 94.485404
iter  20 value 90.252547
iter  30 value 87.306608
iter  40 value 87.161028
iter  50 value 86.865044
iter  60 value 86.722086
iter  70 value 85.975063
iter  80 value 85.596384
final  value 85.532314 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.459180 
iter  10 value 94.490757
iter  20 value 93.870037
iter  30 value 88.932248
iter  40 value 87.179575
iter  50 value 86.896032
iter  60 value 86.713475
iter  70 value 86.462510
iter  80 value 85.578446
iter  90 value 85.532344
final  value 85.532314 
converged
Fitting Repeat 1 

# weights:  305
initial  value 126.149757 
iter  10 value 94.512562
iter  20 value 92.322605
iter  30 value 91.378239
iter  40 value 89.440002
iter  50 value 87.389089
iter  60 value 86.313366
iter  70 value 85.468789
iter  80 value 84.601815
iter  90 value 83.732675
iter 100 value 83.515597
final  value 83.515597 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.524570 
iter  10 value 94.532047
iter  20 value 93.453616
iter  30 value 86.145504
iter  40 value 84.852583
iter  50 value 83.462853
iter  60 value 83.295049
iter  70 value 83.202083
iter  80 value 82.970083
iter  90 value 82.824937
iter 100 value 82.713987
final  value 82.713987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.112434 
iter  10 value 94.496908
iter  20 value 94.434338
iter  30 value 91.311874
iter  40 value 87.656395
iter  50 value 84.956733
iter  60 value 84.237181
iter  70 value 83.698048
iter  80 value 82.984118
iter  90 value 82.586665
iter 100 value 82.407632
final  value 82.407632 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.338014 
iter  10 value 93.591206
iter  20 value 87.910928
iter  30 value 87.761989
iter  40 value 87.386727
iter  50 value 86.649808
iter  60 value 86.034331
iter  70 value 84.416512
iter  80 value 83.767230
iter  90 value 83.659712
iter 100 value 83.641352
final  value 83.641352 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.208085 
iter  10 value 95.989350
iter  20 value 95.325070
iter  30 value 91.613493
iter  40 value 88.164470
iter  50 value 86.417690
iter  60 value 85.518029
iter  70 value 84.882714
iter  80 value 83.726722
iter  90 value 83.100038
iter 100 value 82.871740
final  value 82.871740 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.357077 
iter  10 value 93.875781
iter  20 value 88.747080
iter  30 value 87.755667
iter  40 value 86.130236
iter  50 value 84.827317
iter  60 value 84.165000
iter  70 value 83.403732
iter  80 value 82.996859
iter  90 value 82.321738
iter 100 value 82.175372
final  value 82.175372 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.862579 
iter  10 value 94.225651
iter  20 value 89.129616
iter  30 value 85.313857
iter  40 value 84.199761
iter  50 value 83.756916
iter  60 value 83.592967
iter  70 value 83.322999
iter  80 value 83.011424
iter  90 value 82.874920
iter 100 value 82.570354
final  value 82.570354 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.037940 
iter  10 value 95.629789
iter  20 value 90.245967
iter  30 value 87.170625
iter  40 value 85.158391
iter  50 value 83.329278
iter  60 value 83.076362
iter  70 value 82.798489
iter  80 value 82.598695
iter  90 value 82.458184
iter 100 value 82.428861
final  value 82.428861 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.051048 
iter  10 value 94.609071
iter  20 value 90.320223
iter  30 value 87.776510
iter  40 value 85.116646
iter  50 value 84.195300
iter  60 value 83.390477
iter  70 value 83.182660
iter  80 value 82.883664
iter  90 value 82.643551
iter 100 value 82.540161
final  value 82.540161 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.899520 
iter  10 value 94.561509
iter  20 value 91.597973
iter  30 value 87.862560
iter  40 value 87.491542
iter  50 value 87.208956
iter  60 value 85.954934
iter  70 value 83.475563
iter  80 value 82.880047
iter  90 value 82.791751
iter 100 value 82.598857
final  value 82.598857 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.336805 
final  value 94.485562 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.143469 
iter  10 value 94.485953
iter  20 value 94.484277
iter  30 value 93.838116
iter  40 value 86.273765
iter  50 value 86.207579
iter  60 value 85.893802
iter  70 value 85.164854
iter  80 value 85.155621
final  value 85.155500 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.032091 
iter  10 value 94.486062
iter  20 value 94.481409
iter  30 value 93.911465
iter  40 value 86.019947
iter  50 value 85.275848
iter  60 value 85.275206
iter  70 value 85.147423
final  value 85.147369 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.418718 
final  value 94.485687 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.556126 
final  value 94.485654 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.047142 
iter  10 value 90.998432
iter  20 value 89.605636
iter  30 value 89.063278
iter  40 value 89.061744
final  value 89.060261 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.063012 
iter  10 value 94.488881
iter  20 value 94.477823
iter  30 value 89.319361
iter  40 value 88.710907
iter  50 value 88.709332
iter  60 value 85.332570
iter  70 value 85.160636
iter  80 value 85.148513
iter  80 value 85.148512
iter  80 value 85.148512
final  value 85.148512 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.778532 
iter  10 value 94.471660
iter  20 value 94.463361
iter  30 value 94.429733
final  value 94.429449 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.613563 
iter  10 value 94.489514
iter  20 value 94.465009
iter  30 value 88.614573
iter  40 value 86.508195
final  value 86.504498 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.785910 
iter  10 value 94.489245
iter  20 value 94.484234
iter  30 value 93.995815
iter  40 value 87.342492
iter  50 value 86.454807
iter  60 value 86.366590
iter  70 value 86.357460
final  value 86.353940 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.625961 
iter  10 value 94.458189
iter  20 value 94.388520
iter  30 value 94.385048
iter  40 value 94.383404
iter  50 value 94.380095
iter  60 value 94.379748
final  value 94.379690 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.363248 
iter  10 value 94.492710
iter  20 value 94.410162
iter  30 value 90.541803
iter  40 value 90.448951
iter  50 value 90.399940
iter  60 value 87.525183
iter  70 value 84.559688
iter  80 value 83.772231
iter  90 value 83.548258
iter 100 value 83.468887
final  value 83.468887 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.758405 
iter  10 value 94.492170
iter  20 value 94.484492
iter  30 value 94.426180
iter  40 value 87.333397
iter  50 value 85.340668
iter  60 value 84.750474
final  value 84.750417 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.679008 
iter  10 value 94.474724
iter  20 value 94.463538
iter  30 value 90.189053
iter  40 value 88.916045
iter  50 value 88.895049
iter  60 value 88.567057
iter  70 value 87.867976
iter  80 value 87.827355
iter  90 value 87.822209
iter 100 value 87.812649
final  value 87.812649 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.431996 
iter  10 value 94.457631
iter  20 value 94.450976
final  value 94.450953 
converged
Fitting Repeat 1 

# weights:  103
initial  value 117.412020 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.839881 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.568125 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.907377 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.297597 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.436232 
iter  10 value 94.199750
iter  20 value 90.040289
iter  30 value 89.815382
final  value 89.812156 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.774379 
final  value 94.448052 
converged
Fitting Repeat 3 

# weights:  305
initial  value 93.242969 
iter  10 value 84.243341
iter  20 value 81.987241
iter  30 value 81.968514
iter  40 value 81.966771
final  value 81.966696 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.682095 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.292771 
final  value 94.275363 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.931752 
iter  10 value 89.231554
iter  20 value 86.760882
iter  30 value 86.130312
iter  40 value 86.129365
iter  50 value 85.577621
iter  60 value 85.490857
final  value 85.490753 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.731489 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.240079 
iter  10 value 88.571746
iter  20 value 86.854422
final  value 86.644766 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.220038 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.714241 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.907117 
iter  10 value 94.491157
iter  20 value 93.937625
iter  30 value 93.710466
iter  40 value 93.703720
iter  50 value 88.206139
iter  60 value 85.400205
iter  70 value 84.938816
iter  80 value 84.927486
iter  90 value 84.925184
iter 100 value 84.864431
final  value 84.864431 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.863548 
iter  10 value 94.489508
iter  20 value 94.194437
iter  30 value 90.236062
iter  40 value 89.824350
iter  50 value 89.632952
iter  60 value 82.613194
iter  70 value 81.662879
iter  80 value 81.500477
iter  90 value 80.925102
iter 100 value 80.576514
final  value 80.576514 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.572995 
iter  10 value 94.392417
iter  20 value 89.555187
iter  30 value 86.539828
iter  40 value 85.403572
iter  50 value 85.115067
iter  60 value 84.881282
iter  70 value 84.833666
final  value 84.833656 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.389121 
iter  10 value 94.466682
iter  20 value 88.873005
iter  30 value 85.801663
iter  40 value 85.590137
iter  50 value 85.443533
iter  60 value 85.329251
iter  70 value 84.812033
iter  80 value 81.857658
iter  90 value 81.114108
iter 100 value 80.669073
final  value 80.669073 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.504983 
iter  10 value 94.518898
iter  20 value 94.489737
iter  30 value 94.016322
iter  40 value 86.419146
iter  50 value 83.914982
iter  60 value 82.155323
iter  70 value 81.135867
iter  80 value 80.847205
iter  90 value 80.772875
iter 100 value 80.627244
final  value 80.627244 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.523947 
iter  10 value 94.378777
iter  20 value 86.481624
iter  30 value 85.276058
iter  40 value 84.867781
iter  50 value 84.814997
iter  60 value 84.780685
iter  70 value 84.198565
iter  80 value 83.088931
iter  90 value 81.098845
iter 100 value 80.030265
final  value 80.030265 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.047129 
iter  10 value 94.176689
iter  20 value 92.213559
iter  30 value 86.112533
iter  40 value 84.760081
iter  50 value 84.377479
iter  60 value 83.837739
iter  70 value 83.600358
iter  80 value 81.684820
iter  90 value 81.268761
iter 100 value 80.983328
final  value 80.983328 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.599196 
iter  10 value 93.801364
iter  20 value 82.897766
iter  30 value 82.061633
iter  40 value 81.650335
iter  50 value 81.028440
iter  60 value 80.796030
iter  70 value 80.695739
iter  80 value 80.522080
iter  90 value 80.394975
iter 100 value 80.309731
final  value 80.309731 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.062015 
iter  10 value 94.396601
iter  20 value 93.574407
iter  30 value 92.873785
iter  40 value 87.120188
iter  50 value 84.708951
iter  60 value 82.686607
iter  70 value 82.074959
iter  80 value 81.529757
iter  90 value 81.273222
iter 100 value 80.434359
final  value 80.434359 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.038294 
iter  10 value 94.545383
iter  20 value 87.399659
iter  30 value 85.834114
iter  40 value 84.798590
iter  50 value 84.258879
iter  60 value 82.500089
iter  70 value 80.183940
iter  80 value 79.508865
iter  90 value 79.400344
iter 100 value 79.322934
final  value 79.322934 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.672671 
iter  10 value 94.351110
iter  20 value 89.916955
iter  30 value 83.866161
iter  40 value 81.719506
iter  50 value 79.617169
iter  60 value 79.438961
iter  70 value 78.976461
iter  80 value 78.890457
iter  90 value 78.828494
iter 100 value 78.802411
final  value 78.802411 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.645981 
iter  10 value 94.275634
iter  20 value 84.042396
iter  30 value 83.192830
iter  40 value 82.532263
iter  50 value 81.895260
iter  60 value 81.110241
iter  70 value 80.787242
iter  80 value 80.626739
iter  90 value 80.464679
iter 100 value 80.034587
final  value 80.034587 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.213478 
iter  10 value 94.467350
iter  20 value 87.315496
iter  30 value 85.685218
iter  40 value 84.488524
iter  50 value 82.141060
iter  60 value 81.424999
iter  70 value 81.134384
iter  80 value 80.179090
iter  90 value 79.952706
iter 100 value 79.839188
final  value 79.839188 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.834995 
iter  10 value 94.189874
iter  20 value 87.764070
iter  30 value 84.974583
iter  40 value 84.429688
iter  50 value 81.967492
iter  60 value 80.865440
iter  70 value 80.098863
iter  80 value 79.932848
iter  90 value 79.835720
iter 100 value 79.504603
final  value 79.504603 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.245956 
iter  10 value 95.157664
iter  20 value 85.799459
iter  30 value 83.763768
iter  40 value 81.992360
iter  50 value 80.883928
iter  60 value 80.141392
iter  70 value 80.016622
iter  80 value 79.874354
iter  90 value 79.734644
iter 100 value 79.580596
final  value 79.580596 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.754329 
final  value 94.485883 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.742584 
final  value 94.486071 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.019756 
final  value 94.485831 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.152443 
final  value 94.486139 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.212699 
final  value 94.485526 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.530762 
iter  10 value 94.488481
iter  20 value 93.838932
iter  30 value 93.588869
iter  40 value 93.579846
iter  50 value 90.937357
iter  60 value 85.491837
final  value 85.491427 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.105768 
iter  10 value 94.488064
iter  20 value 94.401239
final  value 93.637817 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.148659 
iter  10 value 93.644114
iter  20 value 93.641921
iter  30 value 93.576477
iter  40 value 93.065532
iter  40 value 93.065531
iter  50 value 92.838364
iter  60 value 83.812889
iter  70 value 79.920476
iter  80 value 79.376523
iter  90 value 79.173424
iter 100 value 78.728176
final  value 78.728176 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.531005 
iter  10 value 94.489115
iter  20 value 94.483913
iter  30 value 91.738378
final  value 91.580858 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.189838 
iter  10 value 93.988909
iter  20 value 93.985648
iter  30 value 87.767398
iter  40 value 83.920571
iter  50 value 81.050586
iter  60 value 80.913238
iter  70 value 80.912819
iter  80 value 80.912212
final  value 80.912047 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.937398 
iter  10 value 94.456033
iter  20 value 94.449781
final  value 94.449598 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.270475 
iter  10 value 94.492515
iter  20 value 94.484162
iter  30 value 85.046325
iter  40 value 82.763093
iter  50 value 82.130200
iter  60 value 82.098814
iter  70 value 81.667644
iter  80 value 79.596177
iter  90 value 79.374655
iter 100 value 79.368134
final  value 79.368134 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.860945 
iter  10 value 93.781514
iter  20 value 93.764030
iter  30 value 93.579023
iter  40 value 93.476378
iter  50 value 93.476271
iter  60 value 93.475724
iter  70 value 93.475587
final  value 93.475556 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.218106 
iter  10 value 94.283845
iter  20 value 94.277413
iter  30 value 94.015935
iter  40 value 91.444173
iter  50 value 91.272520
iter  60 value 80.847927
iter  70 value 79.811985
final  value 79.811531 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.761344 
iter  10 value 94.283112
iter  20 value 94.173713
iter  30 value 83.352553
iter  40 value 81.954933
iter  50 value 81.781035
iter  60 value 81.585799
iter  70 value 81.391882
iter  80 value 78.954189
iter  90 value 78.336638
iter 100 value 78.315215
final  value 78.315215 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.206597 
iter  10 value 117.895848
iter  20 value 115.550654
iter  30 value 107.050275
iter  40 value 106.715079
iter  50 value 106.645360
final  value 106.645172 
converged
Fitting Repeat 2 

# weights:  507
initial  value 123.355089 
iter  10 value 117.899157
iter  20 value 117.872993
iter  30 value 114.812861
iter  40 value 114.039526
iter  50 value 114.032297
iter  60 value 108.627735
iter  70 value 108.401831
iter  80 value 108.369145
iter  90 value 108.366311
iter 100 value 108.362982
final  value 108.362982 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 158.090359 
iter  10 value 117.203318
iter  20 value 116.959323
iter  30 value 116.956498
iter  40 value 116.871933
final  value 116.869127 
converged
Fitting Repeat 4 

# weights:  507
initial  value 123.727945 
iter  10 value 117.898439
iter  20 value 117.887797
iter  30 value 114.755351
iter  40 value 108.132238
iter  50 value 107.004679
iter  60 value 106.746255
iter  70 value 102.517258
iter  80 value 101.111117
iter  90 value 101.062518
iter 100 value 101.054332
final  value 101.054332 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 131.002655 
iter  10 value 116.630956
iter  20 value 112.021345
iter  30 value 109.838292
iter  40 value 109.659431
iter  50 value 109.270335
iter  60 value 109.162416
iter  70 value 109.160172
iter  80 value 109.151092
final  value 109.150989 
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 -- Fri Feb 24 12:41:12 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 
 53.470   1.805  68.822