##############################################################################
##############################################################################
###
### 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_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (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 ‘1.13.0’
* 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 ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       39.998  0.870  40.936
FSmethod      38.136  0.208  38.407
corr_plot     37.515  0.388  37.964
pred_ensembel 18.483  0.575  17.864
enrichfindP    0.509  0.032  21.349
getFASTA       0.125  0.008   7.672
* 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: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.21-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-devel_2025-02-19/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.13.0’
** 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) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 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 100.460937 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.859001 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.932297 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.571647 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.836243 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.790707 
iter  10 value 94.452716
final  value 94.449438 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.784676 
final  value 94.088890 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.210787 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.060335 
iter  10 value 94.357526
iter  20 value 86.691998
iter  30 value 86.666539
final  value 86.665542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.937823 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.430243 
iter  10 value 94.083951
iter  10 value 94.083951
iter  10 value 94.083951
final  value 94.083951 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.550304 
final  value 94.400000 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.908280 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 151.195123 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.609819 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.916233 
iter  10 value 90.525693
iter  20 value 86.116631
iter  30 value 85.389476
iter  40 value 84.582881
iter  50 value 84.370753
iter  60 value 84.310571
final  value 84.310554 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.183377 
iter  10 value 94.421485
iter  20 value 92.273784
iter  30 value 91.847986
iter  40 value 91.816662
iter  50 value 91.759753
iter  60 value 91.677975
iter  70 value 85.387069
iter  80 value 84.049427
iter  90 value 83.423537
iter 100 value 83.145135
final  value 83.145135 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 110.445947 
iter  10 value 94.461858
iter  20 value 92.967586
iter  30 value 91.730611
iter  40 value 85.876519
iter  50 value 84.166138
iter  60 value 83.698836
iter  70 value 83.344413
iter  80 value 82.870738
iter  90 value 82.709399
iter 100 value 82.610473
final  value 82.610473 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.994466 
iter  10 value 94.222124
iter  20 value 86.811301
iter  30 value 85.672104
iter  40 value 85.620304
iter  50 value 84.970748
iter  60 value 84.501090
iter  70 value 84.378528
iter  80 value 84.310934
final  value 84.310548 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.914167 
iter  10 value 94.486551
iter  20 value 94.424052
iter  30 value 92.746567
iter  40 value 92.538492
iter  50 value 87.325939
iter  60 value 85.844861
iter  70 value 85.095159
iter  80 value 84.853798
iter  90 value 84.714067
final  value 84.713594 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.607338 
iter  10 value 94.542208
iter  20 value 94.358096
iter  30 value 94.326298
iter  40 value 94.281888
iter  50 value 92.901583
iter  60 value 88.430436
iter  70 value 85.452801
iter  80 value 84.500010
iter  90 value 82.904805
iter 100 value 81.932296
final  value 81.932296 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.278307 
iter  10 value 95.223283
iter  20 value 93.140343
iter  30 value 85.395472
iter  40 value 82.996192
iter  50 value 81.607704
iter  60 value 81.446236
iter  70 value 81.241626
iter  80 value 81.202279
iter  90 value 81.110124
iter 100 value 81.034696
final  value 81.034696 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.626258 
iter  10 value 94.544833
iter  20 value 94.374661
iter  30 value 92.852207
iter  40 value 87.207602
iter  50 value 83.144014
iter  60 value 81.952554
iter  70 value 81.519143
iter  80 value 81.253807
iter  90 value 81.029393
iter 100 value 80.785908
final  value 80.785908 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.566022 
iter  10 value 92.898276
iter  20 value 87.928695
iter  30 value 87.484453
iter  40 value 87.220927
iter  50 value 85.097876
iter  60 value 83.352810
iter  70 value 82.678388
iter  80 value 81.661407
iter  90 value 81.299329
iter 100 value 81.216283
final  value 81.216283 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.364762 
iter  10 value 94.109205
iter  20 value 87.555127
iter  30 value 85.282874
iter  40 value 85.169663
iter  50 value 84.769463
iter  60 value 82.254365
iter  70 value 81.538876
iter  80 value 81.273713
iter  90 value 81.066116
iter 100 value 81.038007
final  value 81.038007 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.322607 
iter  10 value 95.733290
iter  20 value 87.946492
iter  30 value 85.150739
iter  40 value 84.421988
iter  50 value 83.913382
iter  60 value 83.454621
iter  70 value 83.112975
iter  80 value 82.903560
iter  90 value 82.725531
iter 100 value 82.352147
final  value 82.352147 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.653881 
iter  10 value 94.566565
iter  20 value 86.326857
iter  30 value 84.530981
iter  40 value 83.383859
iter  50 value 82.931484
iter  60 value 82.040674
iter  70 value 81.828377
iter  80 value 81.631530
iter  90 value 81.212072
iter 100 value 80.840076
final  value 80.840076 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.207753 
iter  10 value 93.583953
iter  20 value 86.524716
iter  30 value 86.269311
iter  40 value 85.732064
iter  50 value 83.925181
iter  60 value 83.262272
iter  70 value 81.486060
iter  80 value 80.991481
iter  90 value 80.950083
iter 100 value 80.934297
final  value 80.934297 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.525273 
iter  10 value 94.492768
iter  20 value 87.421001
iter  30 value 86.660245
iter  40 value 84.432057
iter  50 value 82.827666
iter  60 value 82.715492
iter  70 value 82.339042
iter  80 value 82.154568
iter  90 value 82.036721
iter 100 value 81.571553
final  value 81.571553 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.432054 
iter  10 value 94.852330
iter  20 value 88.607990
iter  30 value 85.647786
iter  40 value 84.554141
iter  50 value 83.329341
iter  60 value 81.720479
iter  70 value 80.888535
iter  80 value 80.654541
iter  90 value 80.571249
iter 100 value 80.506173
final  value 80.506173 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.942202 
iter  10 value 94.277063
iter  20 value 94.275925
iter  30 value 94.212424
iter  40 value 89.838584
iter  50 value 89.537254
iter  60 value 87.926197
final  value 87.922897 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.037147 
final  value 94.486322 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.208306 
final  value 94.485710 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.035022 
iter  10 value 88.952050
iter  20 value 87.080588
iter  30 value 86.146700
final  value 86.146351 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.994443 
final  value 94.485760 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.749614 
iter  10 value 91.954672
iter  20 value 91.671100
iter  30 value 91.669861
iter  40 value 91.667969
iter  40 value 91.667969
final  value 91.667969 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.747702 
iter  10 value 94.489005
iter  20 value 93.959215
iter  30 value 91.932184
iter  40 value 91.931709
iter  50 value 91.705389
iter  60 value 91.514338
iter  70 value 91.502268
iter  80 value 91.448177
final  value 91.445674 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.703266 
iter  10 value 94.144693
iter  20 value 86.393013
iter  30 value 86.371873
iter  40 value 86.276023
iter  50 value 86.273954
iter  60 value 86.270885
final  value 86.269377 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.867323 
iter  10 value 94.489584
iter  20 value 94.474317
iter  30 value 87.599554
iter  40 value 85.965949
iter  50 value 85.654998
iter  60 value 85.106516
iter  70 value 82.419120
iter  80 value 80.506650
iter  90 value 80.369792
final  value 80.369231 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.665316 
iter  10 value 94.280642
iter  20 value 94.275668
iter  30 value 94.272558
iter  40 value 93.573874
iter  50 value 93.348833
iter  60 value 89.768250
iter  70 value 87.609582
iter  80 value 83.598722
iter  90 value 83.444115
iter 100 value 83.306582
final  value 83.306582 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.633431 
iter  10 value 88.169352
iter  20 value 87.476377
iter  30 value 87.033592
iter  40 value 83.489304
iter  50 value 82.829641
iter  60 value 82.567596
iter  70 value 82.514257
iter  80 value 82.511028
iter  90 value 82.510854
final  value 82.510849 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.654551 
iter  10 value 94.422717
iter  20 value 94.283856
iter  30 value 94.281183
iter  40 value 94.098415
iter  50 value 88.262291
iter  60 value 87.720896
iter  70 value 87.719152
iter  80 value 87.694026
final  value 87.693999 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.170944 
iter  10 value 94.492165
iter  20 value 89.770505
iter  30 value 83.688946
iter  40 value 83.354100
iter  50 value 82.116546
iter  60 value 80.274981
iter  70 value 79.919561
iter  80 value 79.906052
iter  90 value 79.902397
final  value 79.902065 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.757062 
iter  10 value 94.054947
iter  20 value 89.780838
iter  30 value 85.940505
iter  40 value 85.628736
iter  50 value 85.621398
iter  60 value 84.927507
iter  70 value 84.912410
iter  80 value 84.639553
iter  90 value 84.143984
iter 100 value 84.137072
final  value 84.137072 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.983133 
iter  10 value 94.284109
iter  20 value 94.276323
final  value 94.276132 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.252050 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.062487 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.597110 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.527148 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.443104 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.286825 
final  value 93.356725 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.973055 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.275875 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.389779 
iter  10 value 93.328441
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.375560 
iter  10 value 93.383430
iter  20 value 93.154725
final  value 93.154174 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.006905 
iter  10 value 93.296135
final  value 93.296118 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.006728 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.967914 
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.732855 
iter  10 value 93.630117
iter  20 value 93.161988
final  value 93.110571 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.226432 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.224770 
iter  10 value 94.028586
iter  20 value 92.545243
iter  30 value 85.484238
iter  40 value 85.173998
iter  50 value 85.042983
iter  60 value 84.489616
iter  70 value 84.210621
iter  80 value 84.192097
final  value 84.192032 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.881515 
iter  10 value 93.381672
iter  20 value 85.688606
iter  30 value 84.928130
iter  40 value 84.831555
iter  50 value 84.140413
iter  60 value 84.082895
final  value 84.082658 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.396620 
iter  10 value 94.072337
iter  20 value 88.099573
iter  30 value 86.959026
iter  40 value 85.951553
iter  50 value 84.962525
iter  60 value 84.569099
final  value 84.567333 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.845440 
iter  10 value 93.788203
iter  20 value 91.974041
iter  30 value 89.112231
iter  40 value 89.062736
iter  50 value 88.435237
iter  60 value 83.693515
iter  70 value 82.621337
iter  80 value 81.988497
iter  90 value 81.366342
iter 100 value 81.114048
final  value 81.114048 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.755459 
iter  10 value 94.688824
iter  20 value 94.045437
iter  30 value 93.459402
iter  40 value 90.203620
iter  50 value 85.695814
iter  60 value 85.187129
iter  70 value 83.506897
iter  80 value 81.851088
iter  90 value 81.152905
iter 100 value 80.981958
final  value 80.981958 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 116.764422 
iter  10 value 97.131769
iter  20 value 90.477114
iter  30 value 82.811671
iter  40 value 81.862197
iter  50 value 81.271619
iter  60 value 80.846602
iter  70 value 80.805832
iter  80 value 80.669421
iter  90 value 80.175012
iter 100 value 79.913945
final  value 79.913945 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.785832 
iter  10 value 94.596670
iter  20 value 89.521535
iter  30 value 83.502562
iter  40 value 81.258169
iter  50 value 79.622836
iter  60 value 79.494154
iter  70 value 79.290282
iter  80 value 79.236126
iter  90 value 79.205515
iter 100 value 79.185419
final  value 79.185419 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.619828 
iter  10 value 94.058726
iter  20 value 88.617047
iter  30 value 84.609747
iter  40 value 84.385286
iter  50 value 83.910212
iter  60 value 83.480725
iter  70 value 81.773285
iter  80 value 81.248743
iter  90 value 80.336166
iter 100 value 80.055454
final  value 80.055454 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.472758 
iter  10 value 94.073255
iter  20 value 93.290324
iter  30 value 91.130551
iter  40 value 88.326314
iter  50 value 85.752128
iter  60 value 84.248328
iter  70 value 83.205847
iter  80 value 83.093845
iter  90 value 82.826557
iter 100 value 82.612087
final  value 82.612087 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.370712 
iter  10 value 93.915165
iter  20 value 86.465478
iter  30 value 85.257593
iter  40 value 84.518852
iter  50 value 84.062553
iter  60 value 83.198748
iter  70 value 81.521301
iter  80 value 81.013093
iter  90 value 80.243169
iter 100 value 80.182139
final  value 80.182139 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.781149 
iter  10 value 94.251838
iter  20 value 86.771123
iter  30 value 85.659370
iter  40 value 83.919568
iter  50 value 83.217530
iter  60 value 82.991826
iter  70 value 81.396646
iter  80 value 80.549508
iter  90 value 80.219444
iter 100 value 79.701695
final  value 79.701695 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.012527 
iter  10 value 97.048265
iter  20 value 95.107663
iter  30 value 94.471395
iter  40 value 94.020285
iter  50 value 87.617920
iter  60 value 86.822260
iter  70 value 85.359971
iter  80 value 83.666371
iter  90 value 81.851847
iter 100 value 80.546846
final  value 80.546846 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.568036 
iter  10 value 96.012790
iter  20 value 91.921696
iter  30 value 87.883710
iter  40 value 82.838842
iter  50 value 81.123056
iter  60 value 79.932761
iter  70 value 79.460422
iter  80 value 79.330372
iter  90 value 79.259363
iter 100 value 79.224940
final  value 79.224940 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.707914 
iter  10 value 94.915522
iter  20 value 90.395016
iter  30 value 85.193084
iter  40 value 82.777757
iter  50 value 81.663176
iter  60 value 81.608942
iter  70 value 81.297061
iter  80 value 80.928830
iter  90 value 80.464515
iter 100 value 80.187171
final  value 80.187171 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.227453 
iter  10 value 93.677228
iter  20 value 90.446060
iter  30 value 84.599428
iter  40 value 84.027775
iter  50 value 83.128783
iter  60 value 81.479335
iter  70 value 80.414960
iter  80 value 80.017237
iter  90 value 79.849990
iter 100 value 79.687858
final  value 79.687858 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.479966 
final  value 94.054391 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.746047 
final  value 94.054463 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.991912 
iter  10 value 94.054873
iter  20 value 94.052975
final  value 94.052915 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.494858 
final  value 94.054625 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.716409 
final  value 94.054689 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.367703 
iter  10 value 86.264855
iter  20 value 86.171455
iter  30 value 85.281952
iter  40 value 85.271359
iter  50 value 85.268232
iter  60 value 85.268088
iter  60 value 85.268087
final  value 85.268087 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.422267 
iter  10 value 94.057736
iter  20 value 93.950264
iter  30 value 93.090932
iter  40 value 91.558071
iter  50 value 86.210065
iter  60 value 85.703930
iter  70 value 84.884575
iter  80 value 84.800078
iter  80 value 84.800077
iter  80 value 84.800077
final  value 84.800077 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.625671 
iter  10 value 93.872569
iter  20 value 87.702423
iter  30 value 86.986833
iter  40 value 86.271832
iter  50 value 86.166361
iter  60 value 85.811853
iter  70 value 85.806595
final  value 85.806480 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.769470 
iter  10 value 94.057632
iter  20 value 93.372354
final  value 93.328889 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.988702 
iter  10 value 94.057854
iter  20 value 94.052940
iter  30 value 93.777614
iter  40 value 92.510023
final  value 92.507288 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.837971 
iter  10 value 92.173167
iter  20 value 88.639534
iter  30 value 88.506107
iter  40 value 88.503430
iter  50 value 88.497594
iter  60 value 88.497262
iter  70 value 88.494630
final  value 88.493344 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.163168 
iter  10 value 94.060376
iter  20 value 88.939377
iter  30 value 85.607123
final  value 85.606953 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.188487 
iter  10 value 93.137001
iter  20 value 93.118946
iter  30 value 92.934291
iter  40 value 88.093589
iter  50 value 87.417289
iter  60 value 86.469403
iter  70 value 86.434751
iter  80 value 86.434207
iter  90 value 86.434059
iter 100 value 85.386728
final  value 85.386728 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.353704 
iter  10 value 94.061160
iter  20 value 94.036412
iter  30 value 92.995398
iter  40 value 92.845269
iter  50 value 92.845117
iter  60 value 92.845013
iter  60 value 92.845013
final  value 92.845013 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.899301 
iter  10 value 93.878295
iter  20 value 93.870381
iter  30 value 92.738597
iter  40 value 92.687956
iter  50 value 85.754441
iter  60 value 85.268178
iter  70 value 85.208811
iter  80 value 81.283843
iter  90 value 80.223879
iter 100 value 79.563068
final  value 79.563068 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.695835 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.865679 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.347405 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 116.178654 
final  value 93.671508 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.211286 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.668667 
final  value 93.671508 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.985637 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.452364 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.320813 
final  value 93.671509 
converged
Fitting Repeat 5 

# weights:  305
initial  value 93.166618 
iter  10 value 87.571646
final  value 87.571429 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.998592 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.513587 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.038789 
iter  10 value 93.508307
iter  20 value 86.327739
iter  30 value 86.313787
final  value 86.313644 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.125365 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.290744 
iter  10 value 92.901880
iter  20 value 86.256703
iter  30 value 86.229993
final  value 86.229984 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.884200 
iter  10 value 94.064224
iter  20 value 92.201209
iter  30 value 89.131145
iter  40 value 88.393769
iter  50 value 88.109200
iter  60 value 88.063353
iter  70 value 88.035124
iter  80 value 86.225599
iter  90 value 86.156029
iter 100 value 86.153144
final  value 86.153144 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.415974 
iter  10 value 94.061088
iter  20 value 93.514720
iter  30 value 93.469067
iter  40 value 92.578621
iter  50 value 89.070637
iter  60 value 88.951950
iter  70 value 88.450483
iter  80 value 86.227547
iter  90 value 86.157013
iter 100 value 86.139859
final  value 86.139859 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.799908 
iter  10 value 94.056594
iter  20 value 87.536426
iter  30 value 85.047333
iter  40 value 83.700076
iter  50 value 83.623494
iter  60 value 83.594865
final  value 83.592695 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.880972 
iter  10 value 93.961921
iter  20 value 91.822824
iter  30 value 90.364534
iter  40 value 90.258688
iter  50 value 87.514264
iter  60 value 86.088046
iter  70 value 84.851798
iter  80 value 84.547531
iter  90 value 84.143610
iter 100 value 83.712379
final  value 83.712379 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.406556 
iter  10 value 93.694100
iter  20 value 88.500796
iter  30 value 88.067660
iter  40 value 85.360240
iter  50 value 84.313440
iter  60 value 84.028757
iter  70 value 83.886439
iter  80 value 83.860962
final  value 83.857995 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.807108 
iter  10 value 94.412869
iter  20 value 89.807134
iter  30 value 86.855729
iter  40 value 85.252849
iter  50 value 84.617490
iter  60 value 84.454672
iter  70 value 84.373527
iter  80 value 84.300404
iter  90 value 84.071342
iter 100 value 83.306660
final  value 83.306660 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.022892 
iter  10 value 94.013778
iter  20 value 89.438562
iter  30 value 88.167501
iter  40 value 86.007127
iter  50 value 83.316150
iter  60 value 82.330277
iter  70 value 82.131217
iter  80 value 82.079101
iter  90 value 82.068231
iter 100 value 82.065126
final  value 82.065126 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.421782 
iter  10 value 93.761908
iter  20 value 93.449094
iter  30 value 90.949961
iter  40 value 87.523980
iter  50 value 87.193658
iter  60 value 86.529791
iter  70 value 86.115601
iter  80 value 86.002054
iter  90 value 85.060145
iter 100 value 84.574860
final  value 84.574860 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.888615 
iter  10 value 94.845619
iter  20 value 91.880372
iter  30 value 91.821930
iter  40 value 90.491784
iter  50 value 85.547348
iter  60 value 85.244378
iter  70 value 84.575538
iter  80 value 84.378392
iter  90 value 84.247540
iter 100 value 84.127957
final  value 84.127957 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.818651 
iter  10 value 94.041849
iter  20 value 93.615165
iter  30 value 93.378664
iter  40 value 92.760961
iter  50 value 88.630827
iter  60 value 86.263197
iter  70 value 85.292955
iter  80 value 84.686161
iter  90 value 83.757763
iter 100 value 83.130867
final  value 83.130867 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.286813 
iter  10 value 94.234538
iter  20 value 93.533075
iter  30 value 93.368849
iter  40 value 92.884980
iter  50 value 90.406692
iter  60 value 88.855717
iter  70 value 86.782136
iter  80 value 85.927177
iter  90 value 85.528822
iter 100 value 84.280817
final  value 84.280817 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 142.302126 
iter  10 value 94.111937
iter  20 value 93.810469
iter  30 value 90.789803
iter  40 value 87.936001
iter  50 value 84.118026
iter  60 value 83.296447
iter  70 value 83.057856
iter  80 value 82.755171
iter  90 value 82.564274
iter 100 value 82.541731
final  value 82.541731 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.414139 
iter  10 value 93.900776
iter  20 value 90.255959
iter  30 value 88.167146
iter  40 value 86.928519
iter  50 value 86.191541
iter  60 value 84.573849
iter  70 value 84.152662
iter  80 value 83.986086
iter  90 value 83.832459
iter 100 value 83.717821
final  value 83.717821 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.178924 
iter  10 value 94.055837
iter  20 value 90.528641
iter  30 value 86.293085
iter  40 value 84.019516
iter  50 value 83.722919
iter  60 value 83.073756
iter  70 value 82.738546
iter  80 value 82.687728
iter  90 value 82.509316
iter 100 value 82.254460
final  value 82.254460 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.802157 
iter  10 value 93.910636
iter  20 value 89.472121
iter  30 value 87.817896
iter  40 value 86.694097
iter  50 value 86.299616
iter  60 value 86.122551
iter  70 value 85.575592
iter  80 value 85.301380
iter  90 value 84.311199
iter 100 value 84.122931
final  value 84.122931 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.482003 
final  value 94.054668 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.854463 
final  value 94.054485 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.826200 
final  value 94.054364 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.744736 
final  value 94.054391 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.911686 
iter  10 value 93.425185
iter  20 value 93.385667
iter  30 value 93.384218
iter  40 value 93.383943
final  value 93.383938 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.230243 
iter  10 value 93.795037
iter  20 value 92.410762
iter  30 value 92.410317
iter  40 value 92.357658
iter  50 value 92.317067
iter  60 value 92.313224
final  value 92.312455 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.428157 
iter  10 value 92.890366
iter  20 value 91.571739
iter  30 value 91.338904
iter  40 value 91.336405
final  value 91.334842 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.696437 
iter  10 value 93.676416
iter  20 value 90.744023
iter  30 value 86.845795
iter  40 value 86.362678
iter  50 value 86.349356
iter  60 value 86.066771
iter  70 value 83.852795
iter  80 value 83.321278
iter  90 value 82.924307
iter 100 value 82.924177
final  value 82.924177 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.243416 
iter  10 value 94.053324
final  value 94.053317 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.804586 
iter  10 value 92.904458
iter  20 value 92.893971
iter  30 value 92.814326
iter  40 value 92.810088
iter  50 value 92.809281
iter  60 value 92.412946
iter  70 value 90.913175
iter  80 value 86.523404
iter  90 value 86.407209
iter 100 value 85.788945
final  value 85.788945 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.119070 
iter  10 value 93.679994
iter  20 value 92.572856
iter  30 value 86.692155
iter  40 value 85.446702
iter  50 value 84.600416
iter  60 value 84.538967
iter  70 value 84.516155
final  value 84.515053 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.984762 
iter  10 value 93.582143
iter  20 value 93.349709
iter  30 value 91.507984
iter  40 value 86.416146
iter  50 value 85.543606
iter  60 value 85.375362
iter  70 value 85.361034
iter  80 value 85.360325
final  value 85.360290 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.307687 
iter  10 value 94.041127
iter  20 value 94.030832
iter  30 value 92.939653
iter  40 value 86.371596
final  value 86.370589 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.569345 
iter  10 value 92.398536
iter  20 value 92.251863
iter  30 value 92.247521
iter  40 value 86.669268
iter  50 value 85.937834
iter  60 value 85.816710
iter  70 value 85.815865
iter  80 value 84.626881
iter  90 value 84.626520
iter 100 value 84.625267
final  value 84.625267 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.598667 
iter  10 value 94.060231
iter  20 value 93.929988
iter  30 value 91.142732
iter  40 value 87.021078
iter  50 value 85.444793
iter  60 value 84.737318
iter  70 value 84.000396
iter  80 value 83.950954
final  value 83.949668 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.535008 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.330983 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.665881 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.609439 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.235629 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.560818 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.039473 
iter  10 value 94.317411
iter  20 value 94.312049
final  value 94.312039 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.037150 
iter  10 value 94.464038
final  value 94.462168 
converged
Fitting Repeat 4 

# weights:  305
initial  value 120.023394 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.926908 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.902829 
iter  10 value 90.075525
iter  20 value 83.713915
iter  30 value 83.509530
final  value 83.505319 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.294824 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.596121 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.374245 
iter  10 value 90.494149
iter  20 value 87.988580
iter  30 value 87.372490
iter  40 value 87.372122
final  value 87.372115 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.226131 
iter  10 value 94.481085
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.004224 
iter  10 value 94.525455
iter  20 value 94.407693
iter  30 value 91.246197
iter  40 value 90.930137
iter  50 value 85.828196
iter  60 value 83.309922
iter  70 value 82.473938
iter  80 value 82.462189
iter  90 value 81.886754
iter 100 value 81.724170
final  value 81.724170 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.850060 
iter  10 value 93.799576
iter  20 value 88.876590
iter  30 value 87.709598
iter  40 value 86.752733
iter  50 value 86.321932
iter  60 value 84.501149
iter  70 value 84.045909
iter  80 value 84.039835
iter  90 value 84.037072
iter 100 value 84.007047
final  value 84.007047 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.815318 
iter  10 value 93.944556
iter  20 value 90.506174
iter  30 value 87.533583
iter  40 value 85.353104
iter  50 value 84.595829
iter  60 value 83.638606
iter  70 value 83.047932
iter  80 value 82.154628
iter  90 value 82.118246
iter 100 value 81.916999
final  value 81.916999 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.415921 
iter  10 value 94.488521
iter  20 value 93.904136
iter  30 value 93.830788
iter  40 value 86.470419
iter  50 value 85.057280
iter  60 value 84.415744
iter  70 value 84.089005
iter  80 value 83.958390
iter  90 value 83.513703
iter 100 value 83.244253
final  value 83.244253 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.260735 
iter  10 value 93.884432
iter  20 value 85.733690
iter  30 value 85.187278
iter  40 value 85.106374
iter  50 value 83.345113
iter  60 value 83.132523
iter  70 value 82.279312
iter  80 value 81.710730
iter  90 value 81.607871
iter 100 value 81.587924
final  value 81.587924 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.069397 
iter  10 value 91.359306
iter  20 value 87.189018
iter  30 value 84.953966
iter  40 value 84.089739
iter  50 value 83.564130
iter  60 value 81.300322
iter  70 value 80.867205
iter  80 value 80.777207
iter  90 value 80.734155
iter 100 value 80.700383
final  value 80.700383 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.691800 
iter  10 value 93.913898
iter  20 value 87.675300
iter  30 value 85.649003
iter  40 value 85.147504
iter  50 value 85.064496
iter  60 value 84.786694
iter  70 value 83.699600
iter  80 value 82.971729
iter  90 value 82.742694
iter 100 value 82.134145
final  value 82.134145 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.755750 
iter  10 value 94.616060
iter  20 value 89.992469
iter  30 value 88.001382
iter  40 value 87.062898
iter  50 value 82.991932
iter  60 value 81.601939
iter  70 value 80.862023
iter  80 value 80.666896
iter  90 value 80.655103
iter 100 value 80.607330
final  value 80.607330 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.673372 
iter  10 value 91.619203
iter  20 value 84.480674
iter  30 value 81.670091
iter  40 value 81.150720
iter  50 value 80.884237
iter  60 value 80.845018
iter  70 value 80.754065
iter  80 value 80.680225
iter  90 value 80.625331
iter 100 value 80.558604
final  value 80.558604 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.023771 
iter  10 value 94.496964
iter  20 value 92.463297
iter  30 value 87.630825
iter  40 value 86.374704
iter  50 value 83.745740
iter  60 value 81.693051
iter  70 value 81.033094
iter  80 value 80.942941
iter  90 value 80.642656
iter 100 value 80.505635
final  value 80.505635 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 130.684893 
iter  10 value 94.723162
iter  20 value 88.903090
iter  30 value 84.939730
iter  40 value 84.027535
iter  50 value 83.918464
iter  60 value 82.928550
iter  70 value 82.070452
iter  80 value 81.860702
iter  90 value 81.643403
iter 100 value 80.785881
final  value 80.785881 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.665777 
iter  10 value 94.945439
iter  20 value 89.385867
iter  30 value 87.683280
iter  40 value 84.008002
iter  50 value 82.567286
iter  60 value 81.811068
iter  70 value 81.684706
iter  80 value 80.993147
iter  90 value 80.717656
iter 100 value 80.617996
final  value 80.617996 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.326478 
iter  10 value 98.111529
iter  20 value 97.108902
iter  30 value 89.650418
iter  40 value 88.231016
iter  50 value 87.361672
iter  60 value 86.279895
iter  70 value 84.082033
iter  80 value 82.983269
iter  90 value 82.398449
iter 100 value 81.763125
final  value 81.763125 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.547416 
iter  10 value 95.057508
iter  20 value 93.369000
iter  30 value 85.335310
iter  40 value 84.641855
iter  50 value 83.611735
iter  60 value 81.518355
iter  70 value 81.143085
iter  80 value 80.960462
iter  90 value 80.852300
iter 100 value 80.838722
final  value 80.838722 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.810517 
iter  10 value 94.485332
iter  20 value 92.933443
iter  30 value 85.935883
iter  40 value 85.002884
iter  50 value 84.697397
iter  60 value 84.393225
iter  70 value 83.823295
iter  80 value 82.697981
iter  90 value 81.501066
iter 100 value 80.831017
final  value 80.831017 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.252599 
final  value 94.486202 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.490282 
final  value 94.485850 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.897989 
final  value 94.486100 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.529717 
iter  10 value 94.485883
final  value 94.484215 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.937376 
final  value 94.486010 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.907006 
iter  10 value 94.316770
iter  20 value 94.313642
iter  30 value 92.561732
iter  40 value 91.244829
iter  50 value 91.224541
final  value 91.224527 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.704754 
iter  10 value 94.102923
iter  20 value 94.092722
iter  30 value 91.597174
iter  40 value 91.309891
iter  50 value 89.476601
iter  60 value 89.077693
iter  70 value 88.949604
iter  80 value 88.946848
iter  90 value 88.925440
iter 100 value 88.910902
final  value 88.910902 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.889673 
iter  10 value 90.301390
iter  20 value 85.011666
iter  30 value 84.749907
iter  40 value 84.748126
iter  50 value 84.729391
iter  60 value 83.941745
iter  70 value 82.489743
iter  80 value 82.476210
iter  90 value 82.471905
iter 100 value 82.332944
final  value 82.332944 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.923438 
iter  10 value 94.317047
iter  20 value 94.312348
iter  30 value 93.935214
iter  40 value 85.893807
iter  50 value 84.672732
iter  60 value 84.656532
iter  70 value 84.654237
iter  80 value 84.654097
final  value 84.653992 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.439733 
iter  10 value 94.488826
iter  20 value 94.027043
iter  30 value 86.967381
iter  40 value 86.574405
iter  50 value 86.573059
iter  50 value 86.573059
final  value 86.573059 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.135499 
iter  10 value 94.417185
iter  20 value 93.776540
final  value 93.721687 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.727440 
iter  10 value 94.488604
iter  20 value 94.484266
iter  30 value 94.272614
iter  40 value 89.526550
iter  50 value 84.652662
iter  60 value 82.529585
iter  70 value 80.927507
iter  80 value 80.921982
iter  90 value 80.919817
iter 100 value 80.432467
final  value 80.432467 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.378065 
iter  10 value 94.485070
iter  20 value 94.327796
iter  30 value 94.279469
iter  40 value 93.681809
iter  50 value 86.523171
iter  60 value 84.449341
iter  70 value 82.142315
iter  80 value 81.192979
iter  90 value 81.182615
iter 100 value 81.126619
final  value 81.126619 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.096198 
iter  10 value 94.475241
iter  20 value 94.467268
iter  30 value 94.159335
iter  40 value 91.934714
iter  40 value 91.934714
iter  40 value 91.934714
final  value 91.934714 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.994001 
iter  10 value 94.474633
iter  20 value 94.467248
iter  30 value 92.093005
final  value 92.088752 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.502858 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.455233 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.337688 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.327114 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.571426 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.135498 
iter  10 value 85.621576
iter  20 value 84.491709
iter  20 value 84.491709
iter  20 value 84.491709
final  value 84.491709 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.854463 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.571031 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.296650 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.097855 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.892571 
final  value 94.165746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.431223 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.249806 
iter  10 value 94.468479
iter  20 value 94.466829
final  value 94.466827 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.701721 
iter  10 value 94.069022
iter  20 value 91.831777
iter  30 value 91.826093
final  value 91.826088 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.274450 
iter  10 value 93.970510
iter  20 value 93.601520
iter  30 value 93.592654
final  value 93.592619 
converged
Fitting Repeat 1 

# weights:  103
initial  value 114.468214 
iter  10 value 94.317743
iter  20 value 82.620867
iter  30 value 82.064495
iter  40 value 81.577292
iter  50 value 81.475900
iter  60 value 81.436827
final  value 81.433010 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.563357 
iter  10 value 94.337508
iter  20 value 84.467217
iter  30 value 81.568086
iter  40 value 79.798678
iter  50 value 79.566269
iter  60 value 78.928069
iter  70 value 78.243226
iter  80 value 78.163256
final  value 78.163254 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.066868 
iter  10 value 92.950517
iter  20 value 85.649254
iter  30 value 81.683620
iter  40 value 81.387287
iter  50 value 81.239120
iter  60 value 81.095345
iter  70 value 80.912210
iter  80 value 80.897198
iter  90 value 80.815910
final  value 80.815821 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.312795 
iter  10 value 94.512069
iter  20 value 94.476096
iter  30 value 94.299406
iter  40 value 93.537549
iter  50 value 93.433871
iter  60 value 93.380355
iter  70 value 93.377077
iter  80 value 82.181090
iter  90 value 81.512933
iter 100 value 81.409463
final  value 81.409463 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.872439 
iter  10 value 94.377272
iter  20 value 92.213413
iter  30 value 85.547711
iter  40 value 83.467635
iter  50 value 82.084052
iter  60 value 81.371927
iter  70 value 80.737711
final  value 80.733077 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.139813 
iter  10 value 94.411278
iter  20 value 93.462561
iter  30 value 90.340898
iter  40 value 90.259944
iter  50 value 85.715250
iter  60 value 82.062783
iter  70 value 80.406137
iter  80 value 78.427318
iter  90 value 76.929689
iter 100 value 76.620423
final  value 76.620423 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.147362 
iter  10 value 92.927959
iter  20 value 91.956787
iter  30 value 91.827268
iter  40 value 90.049802
iter  50 value 82.946322
iter  60 value 79.869668
iter  70 value 79.259466
iter  80 value 78.853445
iter  90 value 78.269666
iter 100 value 78.024518
final  value 78.024518 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.954833 
iter  10 value 94.549452
iter  20 value 93.832523
iter  30 value 88.877905
iter  40 value 87.889437
iter  50 value 85.496770
iter  60 value 81.826086
iter  70 value 79.895888
iter  80 value 77.152545
iter  90 value 76.263908
iter 100 value 75.920982
final  value 75.920982 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.238932 
iter  10 value 94.451607
iter  20 value 87.022985
iter  30 value 86.062112
iter  40 value 83.272869
iter  50 value 80.202519
iter  60 value 79.357882
iter  70 value 79.110448
iter  80 value 78.235022
iter  90 value 77.442400
iter 100 value 77.197109
final  value 77.197109 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.952179 
iter  10 value 94.449468
iter  20 value 90.685581
iter  30 value 89.612470
iter  40 value 85.792150
iter  50 value 82.005967
iter  60 value 81.556111
iter  70 value 79.365878
iter  80 value 77.485499
iter  90 value 77.218549
iter 100 value 76.519233
final  value 76.519233 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.953243 
iter  10 value 89.967422
iter  20 value 82.833835
iter  30 value 81.724058
iter  40 value 81.503254
iter  50 value 81.058255
iter  60 value 81.017151
iter  70 value 80.885713
iter  80 value 79.710774
iter  90 value 78.152537
iter 100 value 77.498912
final  value 77.498912 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.136393 
iter  10 value 94.531968
iter  20 value 81.475761
iter  30 value 80.028059
iter  40 value 79.233684
iter  50 value 78.523271
iter  60 value 78.380887
iter  70 value 78.020419
iter  80 value 77.486766
iter  90 value 76.456025
iter 100 value 76.353150
final  value 76.353150 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.988929 
iter  10 value 94.851142
iter  20 value 92.896564
iter  30 value 90.259371
iter  40 value 89.602885
iter  50 value 84.940658
iter  60 value 81.530392
iter  70 value 78.487503
iter  80 value 77.432762
iter  90 value 77.230672
iter 100 value 76.989720
final  value 76.989720 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.020249 
iter  10 value 94.460560
iter  20 value 93.625443
iter  30 value 85.011442
iter  40 value 83.421982
iter  50 value 81.947836
iter  60 value 79.022056
iter  70 value 77.607626
iter  80 value 76.861401
iter  90 value 76.189960
iter 100 value 76.124880
final  value 76.124880 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.909100 
iter  10 value 95.027014
iter  20 value 90.019453
iter  30 value 87.744005
iter  40 value 85.942623
iter  50 value 85.564368
iter  60 value 82.737014
iter  70 value 79.739415
iter  80 value 79.481929
iter  90 value 78.860704
iter 100 value 78.648178
final  value 78.648178 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.351193 
final  value 94.485934 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.722108 
iter  10 value 94.435838
final  value 93.111846 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.891187 
final  value 94.485910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.516660 
final  value 94.485837 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.738288 
final  value 94.485850 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.888584 
iter  10 value 94.489177
iter  20 value 94.483514
iter  30 value 89.786402
iter  40 value 85.337149
iter  50 value 85.022323
iter  60 value 85.020204
iter  70 value 85.018206
iter  80 value 84.958513
iter  90 value 84.957241
iter 100 value 84.955444
final  value 84.955444 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 94.152392 
iter  10 value 89.604142
iter  20 value 89.548348
iter  30 value 89.546392
iter  40 value 88.940424
iter  50 value 88.246501
iter  60 value 88.040085
iter  70 value 87.823390
iter  80 value 87.822935
iter  90 value 87.745435
iter 100 value 87.745360
final  value 87.745360 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.896292 
iter  10 value 94.489559
iter  20 value 94.483822
iter  30 value 94.349928
iter  40 value 87.835457
iter  50 value 82.147373
iter  60 value 80.515919
iter  70 value 79.981174
final  value 79.981170 
converged
Fitting Repeat 4 

# weights:  305
initial  value 128.480195 
iter  10 value 94.489489
iter  20 value 94.453332
iter  30 value 93.228496
iter  40 value 93.213553
iter  50 value 92.218955
iter  60 value 92.012299
iter  70 value 91.944234
iter  80 value 91.942427
iter  90 value 91.942194
final  value 91.942077 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.122027 
iter  10 value 94.484523
iter  20 value 94.369299
iter  30 value 85.456290
iter  40 value 82.231939
iter  50 value 82.227704
iter  60 value 82.225249
iter  70 value 81.796858
iter  80 value 81.785177
iter  90 value 81.692192
iter 100 value 81.679608
final  value 81.679608 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.447245 
iter  10 value 93.882642
iter  20 value 93.266399
iter  30 value 93.104579
iter  40 value 93.091184
iter  50 value 84.929818
iter  60 value 84.696273
iter  70 value 84.638779
final  value 84.637454 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.690159 
iter  10 value 94.489044
iter  20 value 93.316546
iter  30 value 83.789039
iter  40 value 82.728096
iter  50 value 79.731154
iter  60 value 79.513457
iter  70 value 79.510869
iter  80 value 79.505959
iter  90 value 79.503866
iter 100 value 79.469582
final  value 79.469582 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.691805 
iter  10 value 94.490363
iter  20 value 94.484215
iter  30 value 93.783298
iter  40 value 88.641737
iter  50 value 88.244169
iter  60 value 88.242828
iter  70 value 88.240312
final  value 88.239351 
converged
Fitting Repeat 4 

# weights:  507
initial  value 126.712974 
iter  10 value 94.491978
iter  20 value 94.378505
iter  30 value 86.402045
final  value 86.402043 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.581218 
iter  10 value 94.491103
iter  20 value 91.916071
iter  30 value 85.538087
iter  40 value 83.690903
iter  50 value 83.349616
iter  60 value 83.348839
iter  70 value 83.347520
iter  80 value 82.394505
iter  90 value 82.271337
iter 100 value 82.270287
final  value 82.270287 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.527748 
iter  10 value 117.767289
iter  20 value 117.387686
iter  30 value 115.494264
iter  40 value 114.186736
iter  50 value 113.696651
iter  60 value 107.131469
iter  70 value 104.614418
iter  80 value 104.584386
iter  90 value 104.577952
iter 100 value 104.575625
final  value 104.575625 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 155.636193 
iter  10 value 117.898592
iter  20 value 117.890094
iter  30 value 117.531916
iter  40 value 109.596908
iter  50 value 108.864676
iter  60 value 108.459706
iter  70 value 107.174701
iter  80 value 107.174049
final  value 107.173889 
converged
Fitting Repeat 3 

# weights:  507
initial  value 152.390568 
iter  10 value 117.778243
iter  20 value 117.770123
iter  30 value 117.734522
iter  40 value 117.706836
iter  50 value 114.310819
iter  60 value 104.165024
iter  70 value 104.111123
iter  80 value 104.056170
iter  90 value 103.966136
iter 100 value 101.803190
final  value 101.803190 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.372632 
iter  10 value 117.765425
iter  20 value 117.750344
iter  30 value 117.736110
iter  40 value 117.688637
iter  50 value 116.608332
iter  60 value 105.361010
iter  70 value 105.358626
iter  80 value 102.994713
iter  90 value 102.064277
iter 100 value 100.570591
final  value 100.570591 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.314736 
iter  10 value 117.739163
iter  20 value 117.521611
iter  30 value 117.207406
iter  40 value 117.202953
iter  50 value 105.404471
iter  60 value 104.410862
iter  70 value 104.279138
iter  80 value 103.995886
iter  90 value 103.995699
final  value 103.995694 
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 -- Mon Mar 24 07:35:40 2025 
*********************************************** 
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 
 55.257   1.278 153.999