##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    gcc (GCC) 12.2.1 20220819 (openEuler 12.2.1-14)
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       40.521  0.795  41.396
FSmethod      38.083  0.615  38.773
corr_plot     38.181  0.356  38.599
pred_ensembel 19.589  0.339  17.583
enrichfindP    0.537  0.044  23.625
getFASTA       0.089  0.008   6.121
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.4.1/site-library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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

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

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

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

# weights:  103
initial  value 101.362421 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.098850 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.902071 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.071227 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.103562 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.600753 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.010034 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.929232 
final  value 93.775294 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.745515 
final  value 94.133333 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.734728 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.571372 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.382164 
iter  10 value 94.486861
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.523986 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 135.249261 
iter  10 value 94.453343
final  value 94.453333 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.775560 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.988319 
iter  10 value 94.494552
iter  20 value 93.989748
iter  30 value 87.485050
iter  40 value 86.193001
iter  50 value 85.822813
iter  60 value 85.240119
iter  70 value 84.755485
iter  80 value 84.562865
final  value 84.561634 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.289731 
iter  10 value 94.368587
iter  20 value 90.639914
iter  30 value 85.855373
iter  40 value 85.245700
iter  50 value 84.819049
iter  60 value 84.530387
iter  70 value 84.397000
iter  80 value 84.019245
iter  90 value 83.678037
iter 100 value 83.667024
final  value 83.667024 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.068358 
iter  10 value 94.488795
iter  20 value 94.306773
iter  30 value 89.580074
iter  40 value 87.130931
iter  50 value 84.283544
iter  60 value 83.527115
iter  70 value 83.354632
iter  80 value 83.150185
iter  90 value 83.020148
iter 100 value 82.945759
final  value 82.945759 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.106601 
iter  10 value 94.496208
iter  20 value 94.470877
iter  30 value 85.056396
iter  40 value 84.051585
iter  50 value 83.770924
iter  60 value 83.699362
iter  70 value 83.563626
iter  80 value 83.023878
iter  90 value 82.937444
iter 100 value 82.862571
final  value 82.862571 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.010236 
iter  10 value 94.400636
iter  20 value 88.205963
iter  30 value 86.701545
iter  40 value 82.907483
iter  50 value 82.579026
iter  60 value 81.852337
iter  70 value 81.533749
iter  80 value 81.400891
iter  90 value 81.250965
iter 100 value 81.112756
final  value 81.112756 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.788152 
iter  10 value 94.524412
iter  20 value 88.172451
iter  30 value 86.514443
iter  40 value 85.431283
iter  50 value 84.893940
iter  60 value 84.690417
iter  70 value 84.329558
iter  80 value 83.501352
iter  90 value 80.628089
iter 100 value 80.049669
final  value 80.049669 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.938122 
iter  10 value 95.000903
iter  20 value 94.491868
iter  30 value 94.331913
iter  40 value 86.027857
iter  50 value 84.603801
iter  60 value 84.209199
iter  70 value 84.030465
iter  80 value 83.972196
iter  90 value 83.609647
iter 100 value 83.553266
final  value 83.553266 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.459417 
iter  10 value 94.672462
iter  20 value 94.506968
iter  30 value 94.491632
iter  40 value 92.763102
iter  50 value 89.983209
iter  60 value 86.306351
iter  70 value 84.478389
iter  80 value 82.208693
iter  90 value 81.784284
iter 100 value 81.340349
final  value 81.340349 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.547272 
iter  10 value 94.511233
iter  20 value 94.367730
iter  30 value 87.686407
iter  40 value 84.416496
iter  50 value 84.026431
iter  60 value 83.257179
iter  70 value 82.861033
iter  80 value 81.507343
iter  90 value 80.826659
iter 100 value 80.446742
final  value 80.446742 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.181774 
iter  10 value 90.772828
iter  20 value 89.112277
iter  30 value 83.839380
iter  40 value 82.654173
iter  50 value 82.149550
iter  60 value 81.508474
iter  70 value 80.927120
iter  80 value 80.789612
iter  90 value 80.594184
iter 100 value 80.125266
final  value 80.125266 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.072672 
iter  10 value 94.906654
iter  20 value 94.303567
iter  30 value 91.695318
iter  40 value 90.174403
iter  50 value 88.599950
iter  60 value 85.345976
iter  70 value 81.818696
iter  80 value 80.878030
iter  90 value 80.671949
iter 100 value 80.521052
final  value 80.521052 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.134906 
iter  10 value 94.234311
iter  20 value 87.645836
iter  30 value 86.642286
iter  40 value 82.818517
iter  50 value 81.682221
iter  60 value 80.691718
iter  70 value 80.189516
iter  80 value 79.967006
iter  90 value 79.801072
iter 100 value 79.782131
final  value 79.782131 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.259577 
iter  10 value 94.069169
iter  20 value 88.089966
iter  30 value 84.789211
iter  40 value 82.443477
iter  50 value 82.307800
iter  60 value 82.212924
iter  70 value 81.293011
iter  80 value 80.296841
iter  90 value 79.812279
iter 100 value 79.715253
final  value 79.715253 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.018852 
iter  10 value 94.504193
iter  20 value 92.524565
iter  30 value 84.859296
iter  40 value 82.638525
iter  50 value 82.363102
iter  60 value 82.317616
iter  70 value 82.302919
iter  80 value 82.280592
iter  90 value 82.156760
iter 100 value 81.731176
final  value 81.731176 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.912862 
iter  10 value 98.467563
iter  20 value 84.549142
iter  30 value 82.848869
iter  40 value 81.698241
iter  50 value 81.123320
iter  60 value 80.986458
iter  70 value 80.867692
iter  80 value 80.548424
iter  90 value 80.460324
iter 100 value 80.348025
final  value 80.348025 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.643303 
final  value 94.485902 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.607686 
final  value 94.485786 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.866600 
iter  10 value 94.485961
iter  20 value 94.447825
iter  30 value 84.517192
iter  40 value 84.076067
iter  50 value 84.030657
iter  60 value 84.030524
iter  60 value 84.030523
iter  60 value 84.030523
final  value 84.030523 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.499315 
final  value 94.485836 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.565791 
final  value 94.485730 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.311803 
iter  10 value 94.488506
iter  20 value 94.464048
iter  30 value 91.966679
final  value 91.943365 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.890016 
iter  10 value 94.471703
iter  20 value 84.188032
iter  30 value 84.162408
iter  40 value 83.938984
iter  50 value 83.612509
iter  60 value 83.555781
final  value 83.555150 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.864617 
iter  10 value 94.490355
iter  20 value 94.460982
iter  30 value 94.220791
iter  40 value 92.421070
iter  50 value 82.963816
iter  60 value 82.571943
iter  70 value 82.433862
final  value 82.433444 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.232299 
iter  10 value 89.971227
iter  20 value 86.448812
iter  30 value 85.619116
iter  40 value 84.418948
iter  50 value 84.208719
iter  60 value 84.207349
iter  70 value 84.195277
final  value 84.194034 
converged
Fitting Repeat 5 

# weights:  305
initial  value 93.530347 
iter  10 value 89.419255
iter  20 value 88.758352
iter  30 value 88.757073
iter  40 value 87.879776
iter  50 value 86.345816
iter  60 value 86.339704
iter  70 value 86.315633
iter  80 value 84.258012
iter  90 value 83.625835
final  value 83.625351 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.297068 
iter  10 value 94.429050
iter  20 value 94.427068
iter  30 value 94.277171
iter  40 value 94.266436
iter  50 value 93.983138
iter  60 value 93.508676
iter  70 value 86.620964
iter  80 value 81.432406
iter  90 value 80.288947
iter 100 value 80.083811
final  value 80.083811 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.455643 
iter  10 value 94.491443
iter  20 value 94.475642
iter  30 value 84.717065
iter  40 value 84.043380
iter  50 value 83.997444
iter  60 value 83.991167
final  value 83.991140 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.586872 
iter  10 value 94.492561
iter  20 value 94.452341
iter  30 value 87.476919
iter  40 value 84.547993
iter  50 value 82.934162
iter  60 value 82.842074
iter  70 value 82.841287
iter  80 value 82.840929
iter  90 value 82.840648
final  value 82.840378 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.126125 
iter  10 value 94.474697
iter  20 value 94.466158
iter  30 value 86.769224
iter  40 value 85.674403
iter  50 value 85.345288
iter  60 value 82.012089
iter  70 value 81.908066
final  value 81.880025 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.659747 
iter  10 value 94.491866
iter  20 value 94.470061
iter  30 value 90.808417
iter  40 value 85.864412
iter  50 value 84.819924
iter  60 value 83.783182
iter  70 value 82.889078
iter  80 value 82.499368
iter  90 value 82.491094
final  value 82.488599 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.339017 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.212461 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.186556 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.273519 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.383440 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.823627 
iter  10 value 93.915748
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.728962 
final  value 93.868965 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.297407 
iter  10 value 93.685238
iter  10 value 93.685238
iter  10 value 93.685238
final  value 93.685238 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.929783 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.794472 
final  value 94.003143 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.784687 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.516561 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.947322 
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.828934 
iter  10 value 87.572034
iter  20 value 86.077988
final  value 86.077985 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.491774 
iter  10 value 93.628480
final  value 93.628453 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.736739 
iter  10 value 89.068679
iter  20 value 85.146488
iter  30 value 83.669772
iter  40 value 82.813983
iter  50 value 82.180259
iter  60 value 82.142054
iter  70 value 82.135033
final  value 82.134912 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.343559 
iter  10 value 94.645632
iter  20 value 94.079338
iter  30 value 93.960280
iter  40 value 89.235970
iter  50 value 87.068137
iter  60 value 86.346744
iter  70 value 85.226094
iter  80 value 85.196338
iter  90 value 84.430825
iter 100 value 83.668475
final  value 83.668475 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.873162 
iter  10 value 94.071976
iter  20 value 89.778717
iter  30 value 88.798329
iter  40 value 86.385348
iter  50 value 82.618951
iter  60 value 82.291777
iter  70 value 82.288461
iter  80 value 82.117309
iter  90 value 82.011217
iter 100 value 81.969671
final  value 81.969671 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.652440 
iter  10 value 94.186099
iter  20 value 93.575497
iter  30 value 87.058432
iter  40 value 83.837556
iter  50 value 82.776408
iter  60 value 82.219206
iter  70 value 82.162022
iter  80 value 82.148434
iter  90 value 82.134914
final  value 82.134912 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.441855 
iter  10 value 94.055151
iter  20 value 94.054874
iter  30 value 93.965904
iter  40 value 90.830722
iter  50 value 90.450808
iter  60 value 85.488243
iter  70 value 83.806527
iter  80 value 83.543546
iter  90 value 83.020388
iter 100 value 82.033253
final  value 82.033253 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 98.895052 
iter  10 value 93.344491
iter  20 value 85.252372
iter  30 value 83.065945
iter  40 value 82.585564
iter  50 value 82.257130
iter  60 value 81.677898
iter  70 value 80.955820
iter  80 value 80.873254
iter  90 value 80.860668
iter 100 value 80.812212
final  value 80.812212 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.205912 
iter  10 value 94.023540
iter  20 value 89.598849
iter  30 value 88.584247
iter  40 value 86.738766
iter  50 value 86.247791
iter  60 value 85.695230
iter  70 value 82.337716
iter  80 value 81.986818
iter  90 value 81.681085
iter 100 value 81.660381
final  value 81.660381 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.587444 
iter  10 value 94.064701
iter  20 value 92.917054
iter  30 value 88.215866
iter  40 value 86.721313
iter  50 value 86.029151
iter  60 value 85.407534
iter  70 value 84.914468
iter  80 value 84.727250
iter  90 value 82.883828
iter 100 value 80.400590
final  value 80.400590 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.172590 
iter  10 value 94.142197
iter  20 value 88.671436
iter  30 value 86.200482
iter  40 value 86.018357
iter  50 value 83.261334
iter  60 value 82.750623
iter  70 value 82.440566
iter  80 value 80.833472
iter  90 value 80.716373
iter 100 value 80.658093
final  value 80.658093 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.563281 
iter  10 value 93.871687
iter  20 value 83.780561
iter  30 value 83.414322
iter  40 value 82.757033
iter  50 value 82.426238
iter  60 value 82.315522
iter  70 value 81.632934
iter  80 value 81.403186
iter  90 value 81.198877
iter 100 value 80.989646
final  value 80.989646 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.961008 
iter  10 value 88.120062
iter  20 value 86.197230
iter  30 value 85.782656
iter  40 value 84.827924
iter  50 value 83.174836
iter  60 value 81.417415
iter  70 value 80.317595
iter  80 value 79.765487
iter  90 value 79.285779
iter 100 value 79.255764
final  value 79.255764 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.091926 
iter  10 value 94.414720
iter  20 value 94.077796
iter  30 value 93.552232
iter  40 value 85.047802
iter  50 value 83.030536
iter  60 value 82.431034
iter  70 value 80.643064
iter  80 value 79.988705
iter  90 value 79.718313
iter 100 value 79.525814
final  value 79.525814 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.526503 
iter  10 value 92.867791
iter  20 value 86.451070
iter  30 value 83.813151
iter  40 value 81.738069
iter  50 value 80.524636
iter  60 value 79.988226
iter  70 value 79.760406
iter  80 value 79.509907
iter  90 value 79.463943
iter 100 value 79.322151
final  value 79.322151 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 136.522180 
iter  10 value 94.108202
iter  20 value 92.705685
iter  30 value 91.915002
iter  40 value 84.319589
iter  50 value 83.556159
iter  60 value 83.274380
iter  70 value 82.341415
iter  80 value 81.099830
iter  90 value 80.619537
iter 100 value 80.120437
final  value 80.120437 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.269669 
iter  10 value 94.597184
iter  20 value 93.283312
iter  30 value 91.432399
iter  40 value 83.306680
iter  50 value 81.987097
iter  60 value 81.834761
iter  70 value 80.976604
iter  80 value 80.851518
iter  90 value 80.668049
iter 100 value 80.157072
final  value 80.157072 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.502338 
final  value 93.917554 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.027452 
iter  10 value 93.698957
iter  20 value 93.698663
iter  30 value 93.695825
final  value 93.695805 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.679791 
iter  10 value 94.054490
iter  20 value 94.052094
iter  20 value 94.052094
iter  30 value 93.916056
iter  40 value 84.197065
iter  50 value 82.147222
iter  60 value 82.126487
iter  70 value 82.118621
iter  80 value 82.056493
iter  90 value 82.053498
iter 100 value 82.043032
final  value 82.043032 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.879515 
final  value 94.054543 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.576303 
final  value 94.054305 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.561519 
iter  10 value 93.993994
iter  20 value 93.920672
iter  30 value 93.920325
iter  40 value 93.913861
iter  50 value 93.697010
iter  60 value 93.695964
final  value 93.695906 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.435682 
iter  10 value 94.058124
iter  20 value 84.239396
iter  30 value 83.648307
iter  40 value 83.647715
iter  50 value 83.647569
iter  60 value 82.347934
iter  70 value 82.266450
iter  80 value 82.202290
iter  90 value 81.839538
iter 100 value 80.072532
final  value 80.072532 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.597843 
iter  10 value 93.999853
iter  20 value 93.992889
iter  30 value 93.827839
iter  40 value 88.311751
iter  50 value 81.137757
iter  60 value 78.404739
iter  70 value 78.059319
iter  80 value 77.970638
iter  90 value 77.969705
final  value 77.969233 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.008586 
iter  10 value 94.057636
iter  20 value 93.896228
iter  30 value 83.674667
iter  40 value 83.671925
iter  50 value 82.947769
final  value 82.643880 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.792947 
iter  10 value 94.057606
iter  20 value 87.458049
final  value 87.056695 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.676755 
iter  10 value 91.771701
iter  20 value 91.169253
final  value 91.169021 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.932208 
iter  10 value 84.115650
iter  20 value 81.620539
iter  30 value 80.951646
iter  40 value 80.786681
iter  50 value 80.760358
iter  60 value 80.759548
iter  70 value 80.755539
iter  80 value 80.513953
iter  90 value 80.405662
iter 100 value 80.405356
final  value 80.405356 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.234437 
iter  10 value 93.925211
iter  20 value 93.899335
iter  30 value 85.607405
iter  40 value 81.918569
iter  50 value 81.834714
iter  60 value 81.682431
iter  70 value 80.409002
iter  80 value 80.354560
iter  90 value 80.324724
iter 100 value 80.324598
final  value 80.324598 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.445404 
iter  10 value 94.060892
iter  20 value 94.052984
iter  30 value 93.692696
iter  40 value 87.259126
iter  50 value 81.392045
iter  60 value 78.734371
iter  70 value 78.233129
iter  80 value 78.226375
iter  90 value 78.225698
iter 100 value 78.225007
final  value 78.225007 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.470095 
iter  10 value 94.060921
iter  20 value 94.053788
iter  30 value 85.253426
iter  40 value 83.675463
iter  50 value 83.671528
iter  60 value 83.012641
iter  70 value 82.555702
iter  80 value 81.545923
iter  90 value 80.145559
iter 100 value 80.052015
final  value 80.052015 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.404965 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.846260 
iter  10 value 93.836067
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.200457 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.156193 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.431554 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.816000 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.596554 
final  value 92.954172 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.394902 
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.797405 
iter  10 value 93.177921
iter  20 value 93.171479
final  value 93.171476 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.993163 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.469959 
iter  10 value 90.667750
iter  20 value 90.343025
final  value 90.343023 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.025637 
final  value 93.482759 
converged
Fitting Repeat 3 

# weights:  507
initial  value 130.070827 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.871391 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.670046 
iter  10 value 93.836083
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.103365 
iter  10 value 94.055214
iter  20 value 93.927509
iter  30 value 93.075938
iter  40 value 93.054270
iter  50 value 93.049244
iter  50 value 93.049244
final  value 93.049244 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.797156 
iter  10 value 93.588050
iter  20 value 93.164152
iter  30 value 93.065072
iter  40 value 89.827425
iter  50 value 86.334897
iter  60 value 85.864930
iter  70 value 84.878626
iter  80 value 83.069011
iter  90 value 82.007096
iter 100 value 81.623782
final  value 81.623782 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.738689 
iter  10 value 92.667881
iter  20 value 87.487178
iter  30 value 85.703991
iter  40 value 85.538000
iter  50 value 84.342071
iter  60 value 82.685423
iter  70 value 82.059078
iter  80 value 81.896969
final  value 81.849440 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.288430 
iter  10 value 93.997426
iter  20 value 92.659866
iter  30 value 89.546526
iter  40 value 86.711816
iter  50 value 82.631041
iter  60 value 81.986302
iter  70 value 81.850166
final  value 81.849440 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.735437 
iter  10 value 94.065942
iter  20 value 94.054872
iter  30 value 93.267021
iter  40 value 93.066912
iter  50 value 92.888944
iter  60 value 85.510643
iter  70 value 82.708756
iter  80 value 82.516813
iter  90 value 82.431466
iter 100 value 81.860895
final  value 81.860895 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.014843 
iter  10 value 93.832590
iter  20 value 90.095540
iter  30 value 84.183751
iter  40 value 83.342631
iter  50 value 83.045719
iter  60 value 81.865006
iter  70 value 80.968174
iter  80 value 80.797935
iter  90 value 80.604187
iter 100 value 80.379041
final  value 80.379041 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.498377 
iter  10 value 93.334562
iter  20 value 87.378542
iter  30 value 83.541860
iter  40 value 82.356870
iter  50 value 82.076718
iter  60 value 81.912146
iter  70 value 81.869293
iter  80 value 81.833584
iter  90 value 81.766435
iter 100 value 81.476359
final  value 81.476359 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.057983 
iter  10 value 93.631472
iter  20 value 93.081640
iter  30 value 93.009615
iter  40 value 91.971310
iter  50 value 89.076532
iter  60 value 85.768608
iter  70 value 83.924582
iter  80 value 83.424287
iter  90 value 83.246759
iter 100 value 82.658406
final  value 82.658406 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.439308 
iter  10 value 94.761013
iter  20 value 87.598733
iter  30 value 83.571747
iter  40 value 83.389924
iter  50 value 83.065678
iter  60 value 82.659986
iter  70 value 82.269661
iter  80 value 81.773467
iter  90 value 81.389417
iter 100 value 81.300442
final  value 81.300442 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.538730 
iter  10 value 94.146469
iter  20 value 92.151226
iter  30 value 88.532187
iter  40 value 85.102280
iter  50 value 84.776801
iter  60 value 84.706219
iter  70 value 84.333941
iter  80 value 83.900927
iter  90 value 83.234574
iter 100 value 82.900970
final  value 82.900970 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.467906 
iter  10 value 94.108718
iter  20 value 89.524828
iter  30 value 84.821153
iter  40 value 84.535595
iter  50 value 84.447791
iter  60 value 84.363662
iter  70 value 82.848545
iter  80 value 82.320611
iter  90 value 81.981294
iter 100 value 81.317556
final  value 81.317556 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.670231 
iter  10 value 94.737765
iter  20 value 92.028071
iter  30 value 84.297562
iter  40 value 82.534953
iter  50 value 82.141077
iter  60 value 81.931183
iter  70 value 81.766894
iter  80 value 81.638766
iter  90 value 81.414405
iter 100 value 80.866171
final  value 80.866171 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.352923 
iter  10 value 90.434103
iter  20 value 85.702707
iter  30 value 85.203204
iter  40 value 84.472515
iter  50 value 82.716372
iter  60 value 82.453080
iter  70 value 82.201409
iter  80 value 81.927129
iter  90 value 81.274742
iter 100 value 80.705198
final  value 80.705198 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.210321 
iter  10 value 94.231904
iter  20 value 93.392418
iter  30 value 88.273472
iter  40 value 84.866869
iter  50 value 83.134301
iter  60 value 82.745114
iter  70 value 82.394026
iter  80 value 81.397895
iter  90 value 81.253467
iter 100 value 81.132281
final  value 81.132281 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.201882 
iter  10 value 93.999826
iter  20 value 90.619577
iter  30 value 84.908302
iter  40 value 83.291709
iter  50 value 82.965549
iter  60 value 82.653866
iter  70 value 82.487686
iter  80 value 82.404094
iter  90 value 82.307038
iter 100 value 82.217090
final  value 82.217090 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.893138 
iter  10 value 93.837880
iter  10 value 93.837879
iter  10 value 93.837879
final  value 93.837879 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.754738 
final  value 94.054387 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.577964 
iter  10 value 94.054550
iter  20 value 94.052274
iter  30 value 93.838210
final  value 93.836296 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.181933 
final  value 94.054486 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.085495 
final  value 94.054623 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.660588 
iter  10 value 94.060908
iter  20 value 94.054410
iter  30 value 92.961832
iter  40 value 86.894361
iter  50 value 86.843568
iter  60 value 86.280608
iter  70 value 86.272113
iter  80 value 86.271970
iter  90 value 86.266012
iter 100 value 83.766767
final  value 83.766767 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.109075 
iter  10 value 92.458529
iter  20 value 92.457607
final  value 92.456049 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.211774 
iter  10 value 94.057160
iter  20 value 94.053073
iter  30 value 86.736120
iter  40 value 84.289624
iter  50 value 84.175285
iter  60 value 84.164553
iter  70 value 84.162138
iter  80 value 83.819672
iter  90 value 83.755843
iter 100 value 83.753704
final  value 83.753704 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.006772 
iter  10 value 94.058121
iter  20 value 93.964980
iter  30 value 83.997464
iter  40 value 83.971680
iter  50 value 83.965401
iter  60 value 83.912396
iter  70 value 83.896513
iter  80 value 83.306102
iter  90 value 80.964421
iter 100 value 80.471655
final  value 80.471655 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.443989 
iter  10 value 92.959541
iter  20 value 92.955502
iter  30 value 92.926694
iter  40 value 91.069102
iter  50 value 88.986906
iter  60 value 88.807737
iter  70 value 88.701852
iter  80 value 88.701534
iter  90 value 88.701374
final  value 88.701312 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.752449 
iter  10 value 94.059009
iter  20 value 93.747257
iter  30 value 92.955580
iter  40 value 84.896274
iter  50 value 84.328402
iter  60 value 84.298166
iter  70 value 84.294975
iter  70 value 84.294974
iter  70 value 84.294974
final  value 84.294974 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.161803 
iter  10 value 93.844149
iter  20 value 93.838894
iter  30 value 88.751299
iter  40 value 86.258331
iter  50 value 86.255137
iter  60 value 86.085716
iter  70 value 84.240398
iter  80 value 83.582807
iter  90 value 83.509530
iter 100 value 83.144378
final  value 83.144378 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.524321 
iter  10 value 93.844339
iter  20 value 93.837064
iter  30 value 92.960037
iter  40 value 92.937326
iter  50 value 91.029074
iter  60 value 87.997507
iter  70 value 81.459614
iter  80 value 80.904367
iter  90 value 80.900117
final  value 80.899919 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.371734 
iter  10 value 93.297032
iter  20 value 92.432758
iter  30 value 84.550838
iter  40 value 83.974549
final  value 83.973964 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.678218 
iter  10 value 93.843473
iter  20 value 84.922702
iter  30 value 82.423606
iter  40 value 81.291577
iter  50 value 81.276868
iter  60 value 80.993022
iter  70 value 80.806949
iter  80 value 80.715306
iter  90 value 80.713408
final  value 80.708491 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.858585 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.922580 
final  value 94.484209 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.412494 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.478908 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.715415 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.718737 
final  value 94.325945 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.302708 
final  value 94.473118 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.110064 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.729589 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.364850 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.862486 
final  value 94.473118 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.390053 
final  value 94.473118 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.804401 
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.377550 
iter  10 value 93.778458
iter  20 value 92.991421
iter  30 value 92.962533
iter  40 value 92.962305
iter  40 value 92.962305
iter  40 value 92.962305
final  value 92.962305 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.847362 
iter  10 value 94.386120
final  value 94.373383 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.017096 
iter  10 value 94.500322
iter  20 value 92.219296
iter  30 value 89.750347
iter  40 value 86.245330
iter  50 value 85.593210
iter  60 value 85.559509
iter  70 value 85.558712
final  value 85.558578 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.065435 
iter  10 value 94.499123
iter  20 value 94.153278
iter  30 value 92.747529
iter  40 value 92.653320
iter  50 value 90.003614
iter  60 value 87.818574
iter  70 value 87.714916
iter  80 value 87.339484
iter  90 value 87.057956
iter 100 value 84.968395
final  value 84.968395 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.866344 
iter  10 value 94.488597
iter  20 value 94.385954
iter  30 value 94.366105
iter  40 value 93.899892
iter  50 value 88.103199
iter  60 value 86.009457
iter  70 value 85.009183
iter  80 value 84.611274
iter  90 value 84.588411
final  value 84.588237 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.892015 
iter  10 value 94.366980
iter  20 value 88.395352
iter  30 value 87.980342
iter  40 value 87.762089
iter  50 value 87.232239
iter  60 value 86.325475
iter  70 value 86.203718
iter  80 value 85.450073
iter  90 value 85.105270
iter 100 value 85.029969
final  value 85.029969 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.011696 
iter  10 value 94.488244
iter  20 value 94.371106
iter  30 value 94.343826
iter  40 value 94.173864
iter  50 value 87.217315
iter  60 value 86.535506
iter  70 value 86.391689
iter  80 value 85.850087
iter  90 value 85.306854
iter 100 value 85.126035
final  value 85.126035 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.329305 
iter  10 value 94.537594
iter  20 value 88.395016
iter  30 value 88.019435
iter  40 value 87.737419
iter  50 value 86.960756
iter  60 value 84.795146
iter  70 value 83.703309
iter  80 value 82.832039
iter  90 value 82.172023
iter 100 value 81.841409
final  value 81.841409 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 122.018917 
iter  10 value 94.412785
iter  20 value 92.448015
iter  30 value 88.671203
iter  40 value 86.725621
iter  50 value 85.140266
iter  60 value 84.747808
iter  70 value 84.580743
iter  80 value 84.539365
iter  90 value 84.331572
iter 100 value 83.838267
final  value 83.838267 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.770056 
iter  10 value 94.819726
iter  20 value 93.658103
iter  30 value 90.215888
iter  40 value 87.782094
iter  50 value 87.548662
iter  60 value 86.121682
iter  70 value 85.772586
iter  80 value 84.173414
iter  90 value 81.862573
iter 100 value 81.112991
final  value 81.112991 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.131755 
iter  10 value 96.062150
iter  20 value 94.516940
iter  30 value 94.260253
iter  40 value 87.087341
iter  50 value 85.289355
iter  60 value 83.313928
iter  70 value 82.717069
iter  80 value 82.081816
iter  90 value 81.561502
iter 100 value 81.511044
final  value 81.511044 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.045944 
iter  10 value 94.699107
iter  20 value 94.459456
iter  30 value 89.472728
iter  40 value 87.813462
iter  50 value 86.357105
iter  60 value 82.843899
iter  70 value 82.360797
iter  80 value 82.061613
iter  90 value 81.943479
iter 100 value 81.799100
final  value 81.799100 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.099706 
iter  10 value 95.126926
iter  20 value 91.232292
iter  30 value 88.392568
iter  40 value 87.293827
iter  50 value 85.538658
iter  60 value 85.444200
iter  70 value 84.854095
iter  80 value 84.715229
iter  90 value 84.543957
iter 100 value 84.044093
final  value 84.044093 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.615468 
iter  10 value 94.403815
iter  20 value 90.130709
iter  30 value 89.573070
iter  40 value 84.216373
iter  50 value 82.747115
iter  60 value 82.074842
iter  70 value 81.650320
iter  80 value 81.251086
iter  90 value 80.968059
iter 100 value 80.817444
final  value 80.817444 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.234296 
iter  10 value 94.806263
iter  20 value 94.382940
iter  30 value 94.320554
iter  40 value 93.561385
iter  50 value 88.138411
iter  60 value 85.647815
iter  70 value 85.248232
iter  80 value 85.112309
iter  90 value 84.063147
iter 100 value 83.592427
final  value 83.592427 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.470323 
iter  10 value 98.406871
iter  20 value 94.640870
iter  30 value 92.931682
iter  40 value 87.670754
iter  50 value 86.762072
iter  60 value 86.095206
iter  70 value 84.102593
iter  80 value 83.261629
iter  90 value 82.893889
iter 100 value 82.560226
final  value 82.560226 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.409543 
iter  10 value 94.856691
iter  20 value 90.707451
iter  30 value 85.725337
iter  40 value 85.053396
iter  50 value 83.228828
iter  60 value 82.773711
iter  70 value 82.495947
iter  80 value 82.155554
iter  90 value 81.847721
iter 100 value 81.757934
final  value 81.757934 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.269793 
final  value 94.485669 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.969496 
final  value 94.485826 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.337630 
final  value 94.485921 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.692547 
final  value 94.485738 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.887983 
final  value 94.485657 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.739712 
iter  10 value 94.390464
iter  20 value 94.312387
iter  30 value 94.302219
iter  40 value 92.839715
iter  50 value 89.011496
iter  60 value 88.934378
iter  70 value 88.931167
iter  80 value 83.695422
iter  90 value 82.880148
iter 100 value 82.447671
final  value 82.447671 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.505197 
iter  10 value 94.489168
iter  20 value 94.421278
iter  30 value 89.191138
iter  40 value 87.856220
iter  50 value 86.937184
iter  60 value 85.209580
iter  70 value 85.171380
iter  80 value 85.103553
iter  90 value 85.088097
final  value 85.087885 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.585282 
iter  10 value 94.486422
iter  20 value 94.466240
iter  30 value 94.312054
iter  40 value 93.263227
iter  50 value 93.078016
iter  60 value 92.850720
iter  70 value 92.479563
iter  80 value 84.145048
iter  90 value 84.125615
iter 100 value 84.101782
final  value 84.101782 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.475990 
iter  10 value 94.489212
iter  20 value 94.469052
iter  30 value 91.127762
iter  40 value 87.232172
iter  50 value 87.070490
final  value 87.070425 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.942125 
iter  10 value 94.477535
iter  20 value 94.461818
iter  30 value 94.251965
iter  40 value 92.837918
final  value 92.837916 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.078119 
iter  10 value 94.425421
iter  20 value 94.300218
iter  30 value 94.295898
iter  40 value 94.292311
final  value 94.292284 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.887586 
iter  10 value 94.394267
iter  20 value 94.391478
iter  30 value 94.388473
iter  40 value 94.386040
iter  50 value 89.113370
iter  60 value 89.077145
iter  70 value 88.933044
iter  80 value 87.821534
iter  90 value 87.751009
iter 100 value 87.749234
final  value 87.749234 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.536053 
iter  10 value 87.945858
iter  20 value 87.739265
iter  30 value 87.736512
iter  40 value 86.269971
iter  50 value 86.231482
iter  60 value 85.939381
iter  70 value 85.740874
iter  80 value 85.729296
iter  90 value 85.703753
iter 100 value 85.601666
final  value 85.601666 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.787164 
iter  10 value 94.492080
iter  20 value 94.478340
iter  30 value 87.763928
iter  40 value 87.242080
iter  50 value 87.240314
iter  60 value 87.234993
iter  70 value 87.232990
iter  80 value 87.232775
iter  90 value 87.211135
iter 100 value 87.012760
final  value 87.012760 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.391596 
iter  10 value 94.312756
iter  20 value 94.060606
iter  30 value 89.438577
iter  40 value 89.278281
iter  50 value 89.277630
iter  60 value 89.254405
iter  70 value 84.360513
iter  80 value 83.231117
iter  90 value 82.987732
iter 100 value 82.450080
final  value 82.450080 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.816360 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.470869 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.393670 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.392981 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.972956 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.490526 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.266482 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.391725 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.692373 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.058681 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.341440 
iter  10 value 93.157468
iter  10 value 93.157468
iter  10 value 93.157468
final  value 93.157468 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.642761 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.671580 
iter  10 value 94.339179
iter  20 value 88.756995
iter  30 value 87.378096
iter  40 value 87.030933
final  value 87.030791 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.186481 
iter  10 value 92.941167
iter  20 value 92.542429
iter  30 value 92.541496
iter  30 value 92.541496
iter  30 value 92.541496
final  value 92.541496 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.792805 
iter  10 value 93.299991
iter  20 value 84.676066
iter  30 value 83.198495
final  value 83.196405 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.611007 
iter  10 value 94.322781
iter  20 value 94.133978
iter  30 value 94.126473
iter  40 value 92.607701
iter  50 value 85.854520
iter  60 value 84.914219
iter  70 value 83.164748
iter  80 value 82.502060
iter  90 value 82.329710
final  value 82.322789 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.574670 
iter  10 value 94.486491
iter  20 value 92.232280
iter  30 value 85.695102
iter  40 value 84.991086
iter  50 value 83.763015
iter  60 value 81.855296
iter  70 value 81.201075
iter  80 value 81.100000
final  value 81.099836 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.381106 
iter  10 value 94.500360
iter  20 value 84.606551
iter  30 value 83.314889
iter  40 value 82.959117
iter  50 value 82.583220
iter  60 value 82.028687
iter  70 value 81.930261
iter  80 value 79.932047
iter  90 value 79.875761
iter 100 value 79.856429
final  value 79.856429 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 94.801604 
iter  10 value 89.585605
iter  20 value 83.163112
iter  30 value 82.275552
iter  40 value 82.068272
iter  50 value 81.356356
iter  60 value 81.314868
final  value 81.314865 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.695532 
iter  10 value 94.394098
iter  20 value 94.106297
iter  30 value 84.115781
iter  40 value 83.068244
iter  50 value 82.195494
iter  60 value 81.322888
iter  70 value 81.237478
iter  80 value 81.133579
iter  90 value 81.099842
final  value 81.099836 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.703414 
iter  10 value 94.143223
iter  20 value 84.650016
iter  30 value 81.985756
iter  40 value 79.705822
iter  50 value 79.019510
iter  60 value 78.761386
iter  70 value 78.541506
iter  80 value 78.529634
iter  90 value 78.494755
iter 100 value 78.457331
final  value 78.457331 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 126.154577 
iter  10 value 88.619294
iter  20 value 83.563449
iter  30 value 80.358946
iter  40 value 79.280552
iter  50 value 79.099072
iter  60 value 79.019466
iter  70 value 78.854309
iter  80 value 78.672543
iter  90 value 78.365886
iter 100 value 78.198708
final  value 78.198708 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.049223 
iter  10 value 94.497803
iter  20 value 94.033385
iter  30 value 83.410571
iter  40 value 82.327958
iter  50 value 81.761693
iter  60 value 81.201365
iter  70 value 81.002689
iter  80 value 80.560700
iter  90 value 79.227305
iter 100 value 78.779237
final  value 78.779237 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.082672 
iter  10 value 94.052979
iter  20 value 93.819772
iter  30 value 91.010502
iter  40 value 87.712105
iter  50 value 83.731834
iter  60 value 79.757290
iter  70 value 79.037492
iter  80 value 78.781125
iter  90 value 78.443143
iter 100 value 78.244255
final  value 78.244255 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.436193 
iter  10 value 94.510190
iter  20 value 94.318347
iter  30 value 93.255827
iter  40 value 91.716688
iter  50 value 83.534641
iter  60 value 80.417149
iter  70 value 79.628207
iter  80 value 78.969789
iter  90 value 78.827333
iter 100 value 78.747934
final  value 78.747934 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.780850 
iter  10 value 94.632055
iter  20 value 93.209054
iter  30 value 90.752346
iter  40 value 85.581054
iter  50 value 80.449524
iter  60 value 79.678734
iter  70 value 78.750860
iter  80 value 78.572586
iter  90 value 78.471659
iter 100 value 78.450582
final  value 78.450582 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.774596 
iter  10 value 96.243768
iter  20 value 89.962295
iter  30 value 85.351219
iter  40 value 84.070152
iter  50 value 82.922796
iter  60 value 82.019388
iter  70 value 81.294243
iter  80 value 79.617105
iter  90 value 79.132740
iter 100 value 78.779378
final  value 78.779378 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.159271 
iter  10 value 95.799229
iter  20 value 93.129745
iter  30 value 83.605138
iter  40 value 81.140172
iter  50 value 79.459618
iter  60 value 78.718542
iter  70 value 78.531871
iter  80 value 78.528172
iter  90 value 78.451811
iter 100 value 78.241544
final  value 78.241544 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.200110 
iter  10 value 94.374804
iter  20 value 83.866827
iter  30 value 82.741638
iter  40 value 81.921188
iter  50 value 81.376800
iter  60 value 80.040728
iter  70 value 79.437269
iter  80 value 79.192509
iter  90 value 78.658206
iter 100 value 78.497852
final  value 78.497852 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.812464 
iter  10 value 93.974639
iter  20 value 87.184665
iter  30 value 84.563331
iter  40 value 83.923750
iter  50 value 82.121663
iter  60 value 80.250286
iter  70 value 79.443300
iter  80 value 78.910894
iter  90 value 78.595391
iter 100 value 78.481933
final  value 78.481933 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.657315 
final  value 94.486278 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.735649 
iter  10 value 94.485775
final  value 94.484275 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.164977 
iter  10 value 94.485804
final  value 94.484215 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.702375 
iter  10 value 94.485881
final  value 94.484319 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.690173 
iter  10 value 94.028252
final  value 94.028248 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.990861 
iter  10 value 94.488768
iter  20 value 94.481028
iter  30 value 92.636458
final  value 92.636396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.324011 
iter  10 value 92.562322
iter  20 value 91.722782
final  value 91.722546 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.812617 
iter  10 value 94.481459
iter  20 value 94.322796
final  value 94.027652 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.269142 
iter  10 value 94.477230
final  value 94.027309 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.932147 
iter  10 value 94.488628
iter  20 value 94.054066
iter  30 value 90.693897
iter  40 value 90.659899
iter  50 value 90.658874
iter  60 value 90.656277
iter  70 value 90.618934
iter  80 value 90.617359
iter  90 value 90.616314
iter 100 value 90.616239
final  value 90.616239 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.950874 
iter  10 value 94.123536
iter  20 value 94.050487
iter  30 value 91.505960
iter  40 value 91.003064
iter  50 value 89.815514
iter  60 value 89.796329
iter  70 value 89.773131
iter  80 value 89.771074
iter  90 value 82.271740
iter 100 value 80.313042
final  value 80.313042 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.687023 
iter  10 value 94.492211
iter  20 value 92.776414
final  value 92.637324 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.554057 
iter  10 value 92.391778
iter  20 value 87.493289
iter  30 value 83.096192
iter  40 value 82.299299
iter  50 value 81.920394
iter  60 value 80.747517
iter  70 value 80.746818
iter  80 value 80.442647
iter  90 value 79.996451
iter 100 value 78.789712
final  value 78.789712 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.598560 
iter  10 value 93.374029
iter  20 value 92.964330
iter  30 value 86.015087
iter  40 value 85.623642
iter  50 value 85.582688
final  value 85.582351 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.129372 
iter  10 value 94.492838
iter  20 value 94.484638
iter  30 value 92.636835
final  value 92.636715 
converged
Fitting Repeat 1 

# weights:  507
initial  value 125.374340 
iter  10 value 117.766696
iter  20 value 115.714927
iter  30 value 105.102116
iter  40 value 104.909369
iter  50 value 104.906396
iter  60 value 102.024882
iter  70 value 100.085337
iter  80 value 99.537370
iter  90 value 99.521088
iter 100 value 99.518062
final  value 99.518062 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.617443 
iter  10 value 117.624607
iter  20 value 117.600665
iter  30 value 117.506634
iter  40 value 117.499275
iter  50 value 115.666645
iter  60 value 107.447687
iter  70 value 106.956058
iter  80 value 106.796444
final  value 106.770748 
converged
Fitting Repeat 3 

# weights:  507
initial  value 134.109278 
iter  10 value 117.767217
iter  20 value 117.759667
final  value 117.758997 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.386829 
iter  10 value 117.766984
iter  20 value 117.763119
iter  30 value 117.760610
iter  40 value 115.124234
final  value 114.657842 
converged
Fitting Repeat 5 

# weights:  507
initial  value 125.244561 
iter  10 value 117.746514
iter  20 value 117.689506
iter  30 value 117.605671
iter  40 value 117.526812
iter  50 value 117.509969
final  value 117.509860 
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 -- Sat Jul  6 05:49:07 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 54.844   1.335  73.953