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


* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2023-01-14 r83615)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
    gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
    GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
* running under: Ubuntu 22.04.1 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.5.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       38.651  0.600  39.254
corr_plot     38.229  0.432  38.664
FSmethod      37.752  0.440  38.193
pred_ensembel 18.779  0.537  17.000
getFASTA       1.018  0.024  10.678
enrichfindP    0.444  0.033  16.203
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
  ‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK
 NONE
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

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

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


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

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

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

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

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

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

# weights:  103
initial  value 101.571740 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.834001 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.981251 
iter  10 value 88.386635
iter  20 value 87.811543
final  value 87.811469 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.588196 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.735100 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.192196 
iter  10 value 92.920683
iter  20 value 92.486458
iter  30 value 92.484823
iter  40 value 92.447719
iter  50 value 92.202202
iter  60 value 92.200993
iter  60 value 92.200992
iter  60 value 92.200992
final  value 92.200992 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.222479 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.743065 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.512394 
final  value 94.046703 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.991444 
iter  10 value 88.994107
iter  20 value 87.076633
iter  30 value 86.949836
iter  40 value 86.947770
final  value 86.947734 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.974470 
iter  10 value 93.854267
final  value 93.826305 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.209656 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.384236 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.518702 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.055230 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.563055 
iter  10 value 94.297288
iter  20 value 88.868698
iter  30 value 87.797068
iter  40 value 87.757847
iter  50 value 87.419871
iter  60 value 87.212978
iter  70 value 87.138717
iter  80 value 87.125725
iter  90 value 86.242742
iter 100 value 85.718791
final  value 85.718791 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.213863 
iter  10 value 94.461974
iter  20 value 93.938016
iter  30 value 92.296694
iter  40 value 91.740624
iter  50 value 88.401166
iter  60 value 87.311303
iter  70 value 86.625616
iter  80 value 86.538606
iter  90 value 86.489591
iter 100 value 86.469682
final  value 86.469682 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.479865 
iter  10 value 94.544987
iter  20 value 93.679808
iter  30 value 88.800364
iter  40 value 87.853915
iter  50 value 87.373054
iter  60 value 87.221089
iter  70 value 87.198680
final  value 87.198010 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.260124 
iter  10 value 92.949345
iter  20 value 89.375204
iter  30 value 87.282011
iter  40 value 86.773499
iter  50 value 86.304893
iter  60 value 86.216654
iter  70 value 86.216323
final  value 86.216321 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.392956 
iter  10 value 94.493088
iter  20 value 94.168422
iter  30 value 88.813479
iter  40 value 87.164838
iter  50 value 86.590554
final  value 86.589845 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.769695 
iter  10 value 94.437410
iter  20 value 93.710065
iter  30 value 88.724988
iter  40 value 88.063998
iter  50 value 87.829467
iter  60 value 87.293216
iter  70 value 85.714890
iter  80 value 85.279405
iter  90 value 85.064952
iter 100 value 84.756903
final  value 84.756903 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.861411 
iter  10 value 94.160966
iter  20 value 88.444547
iter  30 value 88.129691
iter  40 value 87.315615
iter  50 value 86.291782
iter  60 value 86.139820
iter  70 value 85.790633
iter  80 value 85.045717
iter  90 value 84.154980
iter 100 value 84.061121
final  value 84.061121 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.745263 
iter  10 value 94.032435
iter  20 value 89.042782
iter  30 value 86.921239
iter  40 value 85.023991
iter  50 value 84.716805
iter  60 value 83.475549
iter  70 value 83.084795
iter  80 value 82.590008
iter  90 value 82.335427
iter 100 value 82.217530
final  value 82.217530 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.190007 
iter  10 value 94.398446
iter  20 value 88.883015
iter  30 value 88.387785
iter  40 value 87.187583
iter  50 value 85.094610
iter  60 value 84.125477
iter  70 value 83.640821
iter  80 value 83.556218
iter  90 value 83.509144
iter 100 value 83.482657
final  value 83.482657 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.193506 
iter  10 value 94.128830
iter  20 value 89.656715
iter  30 value 86.328998
iter  40 value 84.316583
iter  50 value 82.857158
iter  60 value 82.385415
iter  70 value 82.325540
iter  80 value 82.144945
iter  90 value 82.110187
iter 100 value 82.103273
final  value 82.103273 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.377301 
iter  10 value 94.468506
iter  20 value 91.808302
iter  30 value 86.624313
iter  40 value 84.226102
iter  50 value 83.457544
iter  60 value 83.394659
iter  70 value 83.293766
iter  80 value 83.199610
iter  90 value 83.170483
iter 100 value 83.107260
final  value 83.107260 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 152.160425 
iter  10 value 94.838579
iter  20 value 92.426052
iter  30 value 88.312001
iter  40 value 87.069343
iter  50 value 85.491652
iter  60 value 83.358767
iter  70 value 83.103039
iter  80 value 82.836945
iter  90 value 82.562857
iter 100 value 82.365174
final  value 82.365174 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.710684 
iter  10 value 94.179499
iter  20 value 90.738410
iter  30 value 88.820050
iter  40 value 86.449049
iter  50 value 85.025261
iter  60 value 84.393115
iter  70 value 84.227553
iter  80 value 84.174098
iter  90 value 84.032491
iter 100 value 83.870192
final  value 83.870192 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 124.153615 
iter  10 value 94.931585
iter  20 value 91.989587
iter  30 value 88.615513
iter  40 value 87.799942
iter  50 value 87.420124
iter  60 value 86.666994
iter  70 value 85.154779
iter  80 value 84.265863
iter  90 value 82.948417
iter 100 value 82.363949
final  value 82.363949 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.004230 
iter  10 value 94.450766
iter  20 value 93.612051
iter  30 value 87.258212
iter  40 value 86.286268
iter  50 value 84.826230
iter  60 value 83.492722
iter  70 value 83.273529
iter  80 value 83.050437
iter  90 value 82.753601
iter 100 value 82.561529
final  value 82.561529 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.176658 
final  value 94.485603 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.852945 
final  value 94.485922 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.499675 
final  value 94.485760 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.174125 
final  value 94.485794 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.735853 
iter  10 value 94.486051
final  value 94.484216 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.207980 
iter  10 value 94.316924
iter  20 value 94.312389
iter  30 value 86.721895
iter  40 value 86.039805
iter  50 value 86.037895
iter  60 value 86.004595
iter  70 value 85.992422
iter  80 value 85.989481
iter  90 value 85.970994
iter 100 value 85.909706
final  value 85.909706 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.788723 
iter  10 value 89.546593
iter  20 value 89.500308
iter  30 value 89.498013
iter  40 value 89.287849
iter  50 value 88.742033
iter  60 value 87.026598
iter  70 value 86.965663
final  value 86.965347 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.271569 
iter  10 value 94.280276
iter  20 value 94.275851
final  value 94.275758 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.308403 
iter  10 value 94.280406
iter  20 value 94.276616
iter  30 value 94.273711
iter  40 value 87.322178
iter  50 value 87.321050
iter  60 value 87.320738
iter  70 value 87.184960
final  value 87.037640 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.805234 
iter  10 value 94.489372
iter  20 value 94.368497
iter  30 value 94.105538
final  value 94.105350 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.850226 
iter  10 value 94.492519
iter  20 value 94.438411
iter  30 value 92.951323
iter  40 value 91.465200
iter  50 value 91.445620
iter  60 value 91.262111
iter  70 value 91.172183
iter  80 value 91.147489
final  value 91.146955 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.414078 
iter  10 value 94.283717
iter  20 value 94.282710
iter  30 value 94.281610
iter  40 value 94.047664
iter  50 value 88.428403
iter  60 value 88.338194
iter  70 value 88.092456
final  value 88.092243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.896007 
iter  10 value 94.492219
iter  20 value 87.985429
iter  30 value 87.540673
iter  40 value 87.424590
iter  50 value 87.074863
iter  60 value 87.072424
final  value 87.070591 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.232585 
iter  10 value 94.491610
iter  20 value 94.484123
iter  30 value 90.587109
iter  40 value 89.352528
iter  50 value 89.031813
iter  60 value 88.975649
iter  70 value 88.967700
iter  80 value 88.966987
iter  90 value 88.959087
iter 100 value 87.706043
final  value 87.706043 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.563206 
iter  10 value 94.283116
iter  20 value 94.275092
iter  30 value 86.821682
iter  40 value 85.811811
iter  50 value 85.529278
iter  60 value 85.528278
final  value 85.528265 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.891493 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.345512 
iter  10 value 94.469326
iter  20 value 94.443244
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.592542 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.591661 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.626537 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.993262 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.819425 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.734842 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.886474 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.712819 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.425553 
final  value 94.427726 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.265627 
iter  10 value 92.237088
iter  20 value 86.017107
final  value 86.017102 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.284809 
iter  10 value 91.756776
iter  20 value 89.801983
final  value 89.800030 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.040175 
final  value 94.443244 
converged
Fitting Repeat 5 

# weights:  507
initial  value 130.221406 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.221086 
iter  10 value 94.482984
iter  20 value 90.731996
iter  30 value 82.982005
iter  40 value 82.818195
iter  50 value 82.576359
iter  60 value 82.457253
iter  70 value 82.426151
final  value 82.420440 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.935748 
iter  10 value 94.487803
iter  20 value 90.235558
iter  30 value 84.037768
iter  40 value 82.926045
iter  50 value 82.618226
iter  60 value 82.491032
iter  70 value 82.413391
final  value 82.411529 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.917571 
iter  10 value 92.953090
iter  20 value 83.510609
iter  30 value 82.574139
iter  40 value 82.433468
iter  50 value 82.411569
final  value 82.411529 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.017245 
iter  10 value 93.780243
iter  20 value 84.365100
iter  30 value 82.351646
iter  40 value 82.092894
final  value 82.088146 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.299540 
iter  10 value 93.837600
iter  20 value 91.342898
iter  30 value 89.821669
iter  40 value 88.735847
iter  50 value 87.184062
iter  60 value 84.333723
iter  70 value 83.834238
iter  80 value 82.476148
iter  90 value 82.421495
final  value 82.421473 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.410545 
iter  10 value 94.419560
iter  20 value 84.224582
iter  30 value 83.686159
iter  40 value 81.987107
iter  50 value 80.918603
iter  60 value 80.653984
iter  70 value 80.605646
iter  80 value 80.412431
iter  90 value 80.172913
iter 100 value 80.032486
final  value 80.032486 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.301728 
iter  10 value 93.250062
iter  20 value 92.001875
iter  30 value 91.081438
iter  40 value 88.151203
iter  50 value 83.003398
iter  60 value 81.400082
iter  70 value 79.291195
iter  80 value 78.560411
iter  90 value 78.319409
iter 100 value 78.192855
final  value 78.192855 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.182159 
iter  10 value 94.791704
iter  20 value 89.562638
iter  30 value 84.789736
iter  40 value 83.288642
iter  50 value 82.848219
iter  60 value 79.846494
iter  70 value 79.309744
iter  80 value 79.142769
iter  90 value 78.975514
iter 100 value 78.753897
final  value 78.753897 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.050715 
iter  10 value 93.104062
iter  20 value 86.270887
iter  30 value 83.483649
iter  40 value 82.040737
iter  50 value 81.789110
iter  60 value 81.660438
iter  70 value 81.439703
iter  80 value 79.798485
iter  90 value 78.808411
iter 100 value 78.649043
final  value 78.649043 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.853920 
iter  10 value 94.340269
iter  20 value 87.047253
iter  30 value 82.003946
iter  40 value 80.181382
iter  50 value 79.414788
iter  60 value 79.289025
iter  70 value 79.261567
iter  80 value 78.686680
iter  90 value 78.623465
iter 100 value 78.407081
final  value 78.407081 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.970095 
iter  10 value 94.520834
iter  20 value 91.093636
iter  30 value 86.137444
iter  40 value 83.859056
iter  50 value 82.474249
iter  60 value 81.881090
iter  70 value 81.707442
iter  80 value 81.402927
iter  90 value 81.222900
iter 100 value 79.740619
final  value 79.740619 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.403822 
iter  10 value 94.283633
iter  20 value 84.943189
iter  30 value 83.091585
iter  40 value 82.385244
iter  50 value 80.831624
iter  60 value 80.108186
iter  70 value 79.703384
iter  80 value 79.601920
iter  90 value 79.229279
iter 100 value 78.808634
final  value 78.808634 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.343326 
iter  10 value 94.457720
iter  20 value 94.244819
iter  30 value 88.737735
iter  40 value 82.970681
iter  50 value 79.790397
iter  60 value 78.512479
iter  70 value 78.139074
iter  80 value 78.100569
iter  90 value 78.070294
iter 100 value 78.039620
final  value 78.039620 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 139.550161 
iter  10 value 95.986829
iter  20 value 86.671202
iter  30 value 81.423041
iter  40 value 80.072543
iter  50 value 79.066399
iter  60 value 78.642254
iter  70 value 78.039997
iter  80 value 77.759165
iter  90 value 77.685279
iter 100 value 77.562814
final  value 77.562814 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.455973 
iter  10 value 94.951812
iter  20 value 94.452244
iter  30 value 92.273865
iter  40 value 90.008463
iter  50 value 89.562384
iter  60 value 89.107161
iter  70 value 86.000003
iter  80 value 82.120134
iter  90 value 80.947852
iter 100 value 80.624808
final  value 80.624808 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.120662 
final  value 94.485961 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.056312 
final  value 94.485676 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.292968 
final  value 94.485945 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.255676 
final  value 94.485826 
converged
Fitting Repeat 5 

# weights:  103
initial  value 90.209374 
iter  10 value 84.006385
iter  20 value 81.132248
iter  30 value 81.126759
iter  40 value 81.125600
iter  50 value 81.124052
iter  60 value 80.956737
iter  70 value 80.791469
iter  70 value 80.791469
iter  70 value 80.791469
final  value 80.791469 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.364911 
iter  10 value 94.487647
iter  20 value 94.476901
iter  30 value 88.865306
final  value 83.265483 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.237250 
iter  10 value 94.448089
iter  20 value 94.444016
iter  30 value 82.079935
iter  40 value 80.041257
iter  50 value 79.980650
iter  60 value 79.957886
iter  70 value 79.224874
iter  80 value 79.049980
iter  90 value 78.101405
iter 100 value 77.576724
final  value 77.576724 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.198648 
iter  10 value 94.448304
iter  20 value 94.267257
iter  30 value 92.743711
iter  40 value 84.066317
iter  50 value 82.477836
iter  60 value 82.301521
iter  70 value 82.266687
iter  80 value 82.175194
iter  90 value 78.130124
iter 100 value 77.912955
final  value 77.912955 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.470978 
iter  10 value 94.448087
iter  20 value 94.424962
iter  30 value 85.422717
iter  40 value 81.135346
iter  50 value 81.126283
final  value 81.126136 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.324716 
iter  10 value 94.447863
iter  20 value 94.439816
iter  30 value 94.254754
final  value 94.254731 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.216008 
iter  10 value 94.452006
iter  20 value 94.428439
iter  30 value 90.246381
iter  40 value 90.221908
final  value 90.220821 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.295265 
iter  10 value 94.469455
iter  20 value 94.463922
iter  30 value 93.691265
iter  40 value 93.653647
iter  50 value 93.291035
iter  60 value 92.929243
iter  70 value 92.784121
iter  80 value 92.528820
iter  90 value 89.333674
iter 100 value 83.784626
final  value 83.784626 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.138426 
iter  10 value 86.643233
iter  20 value 86.632934
iter  30 value 86.626091
iter  30 value 86.626090
iter  40 value 86.625510
iter  50 value 83.119815
iter  60 value 81.196686
iter  70 value 80.981899
iter  80 value 80.981644
iter  90 value 80.948418
iter 100 value 80.940061
final  value 80.940061 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.736313 
final  value 94.492839 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.441489 
iter  10 value 94.492672
iter  20 value 94.384393
iter  30 value 86.253885
iter  40 value 85.714195
iter  50 value 84.119928
iter  60 value 82.648423
iter  70 value 82.370752
iter  80 value 82.365264
iter  90 value 82.354714
iter 100 value 81.732827
final  value 81.732827 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.484601 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.882457 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.443709 
iter  10 value 91.506173
iter  10 value 91.506173
iter  10 value 91.506173
final  value 91.506173 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.003324 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.520085 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.437672 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.850833 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.077307 
iter  10 value 91.770094
iter  20 value 81.812759
final  value 81.772829 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.049814 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.389471 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.544067 
iter  10 value 93.289015
iter  20 value 93.274358
iter  30 value 93.180233
iter  30 value 93.180233
iter  30 value 93.180233
final  value 93.180233 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.730067 
iter  10 value 93.569540
iter  20 value 93.511304
final  value 93.511111 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.745102 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.648121 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.917010 
iter  10 value 94.010012
iter  20 value 85.937218
iter  30 value 84.379093
iter  40 value 84.084267
iter  50 value 84.059806
iter  60 value 84.059248
iter  60 value 84.059248
final  value 84.059248 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.623351 
iter  10 value 92.639690
iter  20 value 86.439093
iter  30 value 83.807248
iter  40 value 83.135319
iter  50 value 82.163815
iter  60 value 81.100160
iter  70 value 81.072152
final  value 81.072110 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.717131 
iter  10 value 94.058235
iter  20 value 89.382791
iter  30 value 83.806027
iter  40 value 82.172474
iter  50 value 81.648829
iter  60 value 81.198398
iter  70 value 80.980736
final  value 80.965992 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.234223 
iter  10 value 94.085070
iter  20 value 88.485632
iter  30 value 83.385510
iter  40 value 82.967709
iter  50 value 82.758020
iter  60 value 82.190085
iter  70 value 81.702099
iter  80 value 81.464733
iter  90 value 81.200658
iter 100 value 81.081072
final  value 81.081072 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.314368 
iter  10 value 94.057268
iter  20 value 92.625414
iter  30 value 85.981865
iter  40 value 85.199702
iter  50 value 82.394067
iter  60 value 81.600335
iter  70 value 80.987813
iter  80 value 80.586065
iter  90 value 80.580598
final  value 80.577838 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.922777 
iter  10 value 94.056693
iter  20 value 92.271113
iter  30 value 82.761061
iter  40 value 82.336280
iter  50 value 81.730713
iter  60 value 81.277656
iter  70 value 81.100220
iter  80 value 81.076658
final  value 81.072110 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.302275 
iter  10 value 93.742861
iter  20 value 83.827823
iter  30 value 82.453205
iter  40 value 81.582217
iter  50 value 81.456572
iter  60 value 81.177261
iter  70 value 80.923992
iter  80 value 80.905258
iter  90 value 80.727815
iter 100 value 79.842240
final  value 79.842240 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.519601 
iter  10 value 94.416647
iter  20 value 93.959457
iter  30 value 87.090215
iter  40 value 86.438539
iter  50 value 80.909346
iter  60 value 78.177208
iter  70 value 78.043420
iter  80 value 77.864638
iter  90 value 77.803889
iter 100 value 77.532739
final  value 77.532739 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.843966 
iter  10 value 93.507272
iter  20 value 86.066695
iter  30 value 85.700989
iter  40 value 85.059473
iter  50 value 82.846764
iter  60 value 79.382558
iter  70 value 78.441977
iter  80 value 78.175687
iter  90 value 78.041022
iter 100 value 77.933717
final  value 77.933717 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.706987 
iter  10 value 94.050105
iter  20 value 82.205554
iter  30 value 80.190396
iter  40 value 79.352964
iter  50 value 78.323100
iter  60 value 78.225024
iter  70 value 77.722529
iter  80 value 77.560376
iter  90 value 77.490024
iter 100 value 77.398057
final  value 77.398057 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.953226 
iter  10 value 94.249873
iter  20 value 93.838596
iter  30 value 91.237796
iter  40 value 85.943647
iter  50 value 84.819736
iter  60 value 84.221006
iter  70 value 80.596315
iter  80 value 79.175670
iter  90 value 78.763086
iter 100 value 78.162292
final  value 78.162292 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.071434 
iter  10 value 94.994947
iter  20 value 89.754114
iter  30 value 85.716564
iter  40 value 82.883740
iter  50 value 80.675146
iter  60 value 79.360214
iter  70 value 78.408786
iter  80 value 77.700697
iter  90 value 77.514553
iter 100 value 77.120435
final  value 77.120435 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.482229 
iter  10 value 94.078250
iter  20 value 89.004188
iter  30 value 88.256287
iter  40 value 85.212350
iter  50 value 83.208706
iter  60 value 82.171315
iter  70 value 81.252395
iter  80 value 79.254846
iter  90 value 78.087014
iter 100 value 77.685281
final  value 77.685281 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.337962 
iter  10 value 94.039436
iter  20 value 93.414016
iter  30 value 86.913732
iter  40 value 86.488494
iter  50 value 86.169606
iter  60 value 84.539712
iter  70 value 81.575173
iter  80 value 79.069039
iter  90 value 78.350635
iter 100 value 78.024821
final  value 78.024821 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.364242 
iter  10 value 100.021634
iter  20 value 87.047548
iter  30 value 85.205330
iter  40 value 83.740781
iter  50 value 83.351035
iter  60 value 82.333956
iter  70 value 80.982431
iter  80 value 80.050748
iter  90 value 79.756935
iter 100 value 79.701858
final  value 79.701858 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.386718 
iter  10 value 94.133978
iter  20 value 85.143799
iter  30 value 83.948373
iter  40 value 83.020812
iter  50 value 82.649401
iter  60 value 81.961396
iter  70 value 80.957415
iter  80 value 79.989828
iter  90 value 79.294702
iter 100 value 79.198532
final  value 79.198532 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.276429 
final  value 93.917644 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.324971 
final  value 94.054427 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.444071 
final  value 94.054585 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.023742 
final  value 94.054277 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.708522 
final  value 94.054642 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.595808 
iter  10 value 94.057576
iter  20 value 94.050568
iter  30 value 93.645035
iter  40 value 93.126954
iter  50 value 81.833392
iter  60 value 81.286934
final  value 81.282599 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.635714 
iter  10 value 94.056671
iter  20 value 93.944039
final  value 93.944004 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.962329 
iter  10 value 94.057953
iter  20 value 94.052966
iter  30 value 86.693889
iter  40 value 85.288321
iter  50 value 85.180188
iter  60 value 85.171997
final  value 85.171961 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.629166 
iter  10 value 94.057632
iter  20 value 94.052944
iter  30 value 92.996628
iter  40 value 83.016011
iter  50 value 82.365835
iter  60 value 82.218515
iter  70 value 81.915396
iter  80 value 81.908433
iter  90 value 81.903600
final  value 81.903542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.523270 
iter  10 value 93.920916
iter  20 value 93.916436
iter  30 value 84.527418
final  value 84.526122 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.136202 
iter  10 value 93.612707
iter  20 value 93.605268
iter  30 value 92.009419
iter  40 value 82.545959
iter  50 value 81.914218
iter  60 value 81.856560
iter  70 value 81.830842
iter  80 value 81.828127
iter  90 value 81.771100
iter 100 value 80.534092
final  value 80.534092 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.710241 
iter  10 value 94.061991
iter  20 value 94.001462
iter  30 value 93.487897
iter  40 value 86.552874
iter  50 value 86.179885
iter  60 value 86.179749
iter  70 value 86.171719
iter  80 value 85.816459
iter  90 value 85.487548
final  value 85.486103 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.710398 
iter  10 value 87.914564
iter  20 value 82.636764
iter  30 value 82.620201
iter  40 value 81.955751
iter  50 value 81.863275
iter  60 value 81.567421
iter  70 value 81.560294
iter  80 value 81.528128
iter  90 value 80.965563
iter 100 value 80.620809
final  value 80.620809 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.421562 
iter  10 value 93.296840
iter  20 value 93.290656
iter  30 value 93.290314
final  value 93.290281 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.084588 
iter  10 value 93.555745
iter  20 value 93.529125
iter  30 value 92.876123
iter  40 value 85.641239
iter  50 value 85.274365
iter  60 value 85.206079
iter  70 value 85.205124
iter  80 value 84.544800
iter  90 value 84.541998
iter 100 value 83.844038
final  value 83.844038 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.329105 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.827711 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.143284 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.595060 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.221786 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.131927 
iter  10 value 94.443183
iter  10 value 94.443182
iter  10 value 94.443182
final  value 94.443182 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.276748 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.838229 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.842063 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.349995 
iter  10 value 94.325203
final  value 94.275364 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.747646 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.286316 
iter  10 value 94.147546
iter  20 value 94.114681
final  value 94.103916 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.626887 
final  value 94.461538 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.014563 
iter  10 value 94.467618
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.932945 
iter  10 value 90.989392
iter  20 value 89.717109
iter  30 value 89.715372
final  value 89.715368 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.424194 
iter  10 value 94.204554
iter  20 value 88.718257
iter  30 value 88.394535
iter  40 value 86.696332
iter  50 value 85.440333
iter  60 value 85.172085
iter  70 value 84.836511
iter  80 value 84.731395
iter  90 value 84.721714
final  value 84.719501 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.333838 
iter  10 value 94.497933
iter  20 value 94.486486
iter  30 value 91.026927
iter  40 value 89.384285
iter  50 value 89.030622
iter  60 value 87.923136
iter  70 value 87.294592
iter  80 value 87.173656
final  value 87.152998 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.058501 
iter  10 value 94.489400
iter  20 value 94.483207
iter  30 value 90.379405
iter  40 value 89.752847
iter  50 value 88.644212
iter  60 value 86.776288
iter  70 value 86.542128
iter  80 value 86.437729
iter  90 value 86.354715
iter 100 value 86.250952
final  value 86.250952 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.966155 
final  value 94.488534 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.968927 
iter  10 value 94.446397
iter  20 value 89.180107
iter  30 value 88.901884
iter  40 value 87.659918
iter  50 value 87.533244
iter  60 value 87.454136
iter  70 value 87.411519
final  value 87.411322 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.623080 
iter  10 value 92.340144
iter  20 value 88.982985
iter  30 value 88.475746
iter  40 value 86.640246
iter  50 value 86.462557
iter  60 value 85.895131
iter  70 value 85.347024
iter  80 value 84.991681
iter  90 value 84.928021
iter 100 value 84.924103
final  value 84.924103 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.307562 
iter  10 value 94.450269
iter  20 value 89.904315
iter  30 value 88.052944
iter  40 value 87.797262
iter  50 value 87.590043
iter  60 value 87.509669
iter  70 value 87.416718
iter  80 value 87.332749
iter  90 value 86.623315
iter 100 value 86.491611
final  value 86.491611 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.803192 
iter  10 value 93.718458
iter  20 value 87.843951
iter  30 value 87.375415
iter  40 value 86.079364
iter  50 value 85.378697
iter  60 value 84.534865
iter  70 value 84.303934
iter  80 value 83.983540
iter  90 value 83.900173
iter 100 value 83.840864
final  value 83.840864 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.012978 
iter  10 value 94.675917
iter  20 value 94.648416
iter  30 value 91.161205
iter  40 value 90.470033
iter  50 value 89.394905
iter  60 value 88.603185
iter  70 value 86.783800
iter  80 value 86.258929
iter  90 value 85.867762
iter 100 value 85.670702
final  value 85.670702 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.461632 
iter  10 value 96.665313
iter  20 value 94.851856
iter  30 value 89.411308
iter  40 value 88.318850
iter  50 value 88.059617
iter  60 value 87.092286
iter  70 value 85.473934
iter  80 value 85.264909
iter  90 value 85.080300
iter 100 value 84.387470
final  value 84.387470 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 136.233906 
iter  10 value 94.945924
iter  20 value 88.782017
iter  30 value 86.434630
iter  40 value 85.392142
iter  50 value 84.773165
iter  60 value 84.074893
iter  70 value 83.296665
iter  80 value 83.027144
iter  90 value 82.937439
iter 100 value 82.907670
final  value 82.907670 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.797583 
iter  10 value 94.528952
iter  20 value 94.336457
iter  30 value 92.069480
iter  40 value 89.740882
iter  50 value 89.304521
iter  60 value 87.971192
iter  70 value 86.037000
iter  80 value 85.337104
iter  90 value 84.944108
iter 100 value 84.751201
final  value 84.751201 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.181661 
iter  10 value 95.216413
iter  20 value 94.492750
iter  30 value 94.416029
iter  40 value 93.144826
iter  50 value 88.803176
iter  60 value 86.309185
iter  70 value 85.706268
iter  80 value 85.097258
iter  90 value 84.724380
iter 100 value 84.502403
final  value 84.502403 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.915072 
iter  10 value 94.375453
iter  20 value 91.977108
iter  30 value 91.104658
iter  40 value 88.289467
iter  50 value 86.066362
iter  60 value 85.316014
iter  70 value 84.472483
iter  80 value 84.029362
iter  90 value 83.831486
iter 100 value 83.685024
final  value 83.685024 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.599161 
iter  10 value 94.575325
iter  20 value 94.490268
iter  30 value 94.476200
iter  40 value 93.404686
iter  50 value 86.336695
iter  60 value 84.456177
iter  70 value 84.072220
iter  80 value 83.867467
iter  90 value 83.619543
iter 100 value 83.571668
final  value 83.571668 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.154267 
iter  10 value 94.486073
iter  20 value 94.484291
iter  30 value 93.306971
iter  40 value 88.958611
iter  50 value 88.941852
iter  60 value 88.940754
iter  70 value 88.651310
iter  80 value 88.647693
final  value 88.647525 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.831450 
final  value 94.485929 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.526837 
iter  10 value 94.485773
iter  20 value 94.484225
iter  30 value 94.172706
iter  40 value 90.969491
iter  50 value 87.964465
iter  60 value 87.913052
iter  70 value 87.903544
final  value 87.903484 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.900311 
iter  10 value 94.485898
final  value 94.484207 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.313534 
final  value 94.485634 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.268164 
iter  10 value 94.488990
iter  20 value 89.893219
iter  30 value 87.318510
iter  40 value 86.550965
iter  50 value 86.312570
iter  60 value 85.968829
iter  70 value 85.405475
iter  80 value 85.327442
iter  90 value 85.309364
iter 100 value 84.822661
final  value 84.822661 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.761229 
iter  10 value 94.471977
iter  20 value 94.467927
iter  30 value 94.462569
iter  40 value 93.371536
iter  50 value 89.664674
iter  60 value 88.082406
iter  70 value 87.136955
iter  80 value 87.131852
iter  90 value 87.129876
iter 100 value 87.127623
final  value 87.127623 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.203470 
iter  10 value 94.488941
iter  20 value 94.470443
final  value 94.467425 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.345008 
iter  10 value 94.489091
iter  20 value 94.484213
iter  30 value 94.419793
iter  40 value 92.436436
iter  50 value 92.292439
final  value 92.290010 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.132584 
iter  10 value 94.471583
iter  20 value 94.467781
final  value 94.467522 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.363908 
iter  10 value 94.492235
iter  20 value 94.448253
iter  30 value 93.392730
iter  40 value 89.764306
iter  50 value 89.316689
final  value 89.311460 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.382529 
iter  10 value 94.469504
iter  20 value 92.253161
iter  30 value 88.678774
iter  40 value 87.097918
iter  50 value 82.942404
iter  60 value 82.401193
iter  70 value 82.285962
iter  80 value 82.280536
iter  90 value 82.280303
iter 100 value 82.280038
final  value 82.280038 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.039340 
iter  10 value 94.492854
iter  20 value 94.477253
iter  30 value 94.443337
final  value 94.443328 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.822799 
iter  10 value 94.436023
iter  20 value 94.393880
iter  30 value 94.393146
iter  40 value 89.727368
iter  50 value 89.720261
iter  60 value 87.765067
final  value 87.747931 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.863963 
iter  10 value 94.492455
iter  20 value 94.165313
iter  30 value 90.821242
iter  40 value 90.241087
iter  50 value 89.171432
iter  60 value 89.101651
iter  70 value 88.673646
iter  80 value 88.613416
iter  90 value 88.609365
iter 100 value 88.043962
final  value 88.043962 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 116.316640 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.816029 
final  value 93.653870 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.959669 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.556018 
final  value 93.410244 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.207341 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.962742 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.386000 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 122.548360 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.840757 
iter  10 value 93.504815
iter  20 value 93.322366
iter  30 value 93.303065
final  value 93.302943 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.201995 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.324221 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.197048 
iter  10 value 93.069215
iter  20 value 92.062305
iter  30 value 90.429271
iter  40 value 89.684971
iter  50 value 87.940100
iter  60 value 84.467348
iter  70 value 84.295682
iter  80 value 84.225570
iter  90 value 84.220924
final  value 84.220909 
converged
Fitting Repeat 3 

# weights:  507
initial  value 132.439471 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.161371 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.905147 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.711588 
iter  10 value 94.054963
iter  20 value 93.631444
iter  30 value 93.438791
iter  40 value 93.357409
iter  50 value 87.512695
iter  60 value 87.107655
iter  70 value 83.014653
iter  80 value 82.313380
iter  90 value 82.197887
iter 100 value 82.087861
final  value 82.087861 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.073950 
iter  10 value 93.751503
iter  20 value 85.337071
iter  30 value 85.047747
iter  40 value 82.988072
iter  50 value 82.938793
final  value 82.938693 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.613635 
iter  10 value 94.058725
iter  20 value 93.853335
iter  30 value 91.293748
iter  40 value 88.498190
iter  50 value 87.394801
iter  60 value 86.639009
iter  70 value 86.427199
iter  80 value 83.507522
iter  90 value 80.544499
iter 100 value 80.149303
final  value 80.149303 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.051082 
iter  10 value 94.036470
iter  20 value 92.612349
iter  30 value 86.936682
iter  40 value 82.636028
iter  50 value 81.705728
iter  60 value 80.635878
iter  70 value 80.178863
iter  80 value 79.823495
iter  90 value 79.812122
final  value 79.811342 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.381994 
iter  10 value 93.501842
iter  20 value 91.844905
iter  30 value 82.710605
iter  40 value 82.072964
iter  50 value 81.911352
iter  60 value 80.457387
iter  70 value 79.944733
iter  80 value 79.811444
final  value 79.811342 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.904569 
iter  10 value 94.002255
iter  20 value 84.524303
iter  30 value 82.691770
iter  40 value 82.224734
iter  50 value 80.587160
iter  60 value 80.217603
iter  70 value 80.026651
iter  80 value 79.890556
iter  90 value 79.886895
iter 100 value 79.858416
final  value 79.858416 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.276803 
iter  10 value 93.914229
iter  20 value 90.009372
iter  30 value 86.357466
iter  40 value 83.952532
iter  50 value 81.283464
iter  60 value 80.513858
iter  70 value 80.256726
iter  80 value 80.033224
iter  90 value 79.820426
iter 100 value 79.781752
final  value 79.781752 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.071332 
iter  10 value 92.553666
iter  20 value 87.927072
iter  30 value 87.560391
iter  40 value 87.238458
iter  50 value 84.571633
iter  60 value 84.038462
iter  70 value 81.944532
iter  80 value 81.371837
iter  90 value 79.983742
iter 100 value 79.238073
final  value 79.238073 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 122.154973 
iter  10 value 94.528785
iter  20 value 85.913512
iter  30 value 84.559700
iter  40 value 84.004109
iter  50 value 83.914789
iter  60 value 83.544931
iter  70 value 83.095367
iter  80 value 82.888402
iter  90 value 82.219996
iter 100 value 80.158777
final  value 80.158777 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.636927 
iter  10 value 93.809524
iter  20 value 93.705206
iter  30 value 87.083175
iter  40 value 84.512469
iter  50 value 83.834874
iter  60 value 83.352234
iter  70 value 80.840327
iter  80 value 79.951908
iter  90 value 79.760955
iter 100 value 79.040493
final  value 79.040493 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.222909 
iter  10 value 93.930043
iter  20 value 88.037951
iter  30 value 87.211483
iter  40 value 82.077344
iter  50 value 80.130059
iter  60 value 79.803355
iter  70 value 79.185023
iter  80 value 78.533757
iter  90 value 78.341890
iter 100 value 78.289963
final  value 78.289963 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.118288 
iter  10 value 93.775684
iter  20 value 91.823624
iter  30 value 84.949562
iter  40 value 84.111352
iter  50 value 81.752770
iter  60 value 81.193213
iter  70 value 80.952323
iter  80 value 80.830825
iter  90 value 80.714260
iter 100 value 80.341584
final  value 80.341584 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.961434 
iter  10 value 91.096359
iter  20 value 84.789736
iter  30 value 80.966130
iter  40 value 80.353122
iter  50 value 79.486899
iter  60 value 79.226358
iter  70 value 79.158438
iter  80 value 79.045366
iter  90 value 78.937836
iter 100 value 78.892545
final  value 78.892545 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.316977 
iter  10 value 85.350438
iter  20 value 84.686523
iter  30 value 84.238853
iter  40 value 83.476849
iter  50 value 82.776958
iter  60 value 81.151156
iter  70 value 79.919226
iter  80 value 79.604758
iter  90 value 79.222647
iter 100 value 79.156076
final  value 79.156076 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.195192 
iter  10 value 94.036193
iter  20 value 92.044204
iter  30 value 87.047590
iter  40 value 83.664366
iter  50 value 81.030227
iter  60 value 79.909268
iter  70 value 79.493739
iter  80 value 79.103077
iter  90 value 78.909384
iter 100 value 78.656305
final  value 78.656305 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.158392 
final  value 94.054551 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.068382 
final  value 94.054381 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.332149 
iter  10 value 94.054501
iter  20 value 94.052824
iter  30 value 93.493755
iter  40 value 93.249924
final  value 93.247547 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.714249 
final  value 94.054480 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.495194 
final  value 94.054448 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.160668 
iter  10 value 94.063807
iter  20 value 94.058868
iter  30 value 89.847485
iter  40 value 84.694046
iter  50 value 82.815220
iter  60 value 82.747228
iter  70 value 82.745914
iter  80 value 82.745434
iter  90 value 82.298107
iter 100 value 81.653911
final  value 81.653911 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.075250 
iter  10 value 94.124246
iter  20 value 93.619993
iter  30 value 89.343315
iter  40 value 86.434378
iter  50 value 86.394287
iter  60 value 86.227100
iter  70 value 86.195632
iter  80 value 84.916792
iter  90 value 84.887388
iter 100 value 84.887180
final  value 84.887180 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.520524 
iter  10 value 94.056331
iter  20 value 87.809512
iter  30 value 86.927879
iter  40 value 86.910336
final  value 86.910241 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.021478 
iter  10 value 94.057907
iter  20 value 94.052933
iter  30 value 93.644667
iter  40 value 83.995729
iter  50 value 82.949565
iter  60 value 82.247938
iter  70 value 81.809571
final  value 81.809568 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.159197 
iter  10 value 94.057528
iter  20 value 93.386961
iter  30 value 93.256116
final  value 93.247582 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.829208 
iter  10 value 93.590382
iter  20 value 93.581902
iter  30 value 93.306288
iter  40 value 93.248131
final  value 93.247835 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.453637 
iter  10 value 86.770648
iter  20 value 81.406247
iter  30 value 80.892756
iter  40 value 80.682317
iter  50 value 80.668837
iter  60 value 80.648303
final  value 80.646820 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.754385 
iter  10 value 93.775794
iter  20 value 93.498232
iter  30 value 93.418978
iter  40 value 93.266900
iter  50 value 93.255839
final  value 93.251699 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.417452 
iter  10 value 88.548298
iter  20 value 83.541393
iter  30 value 82.875732
iter  40 value 82.874662
iter  50 value 82.870903
iter  60 value 82.764572
iter  70 value 82.624773
iter  80 value 82.415334
iter  90 value 82.408731
final  value 82.408612 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.311457 
iter  10 value 93.350011
iter  20 value 93.255940
iter  30 value 88.504040
iter  40 value 82.518739
iter  50 value 81.901503
iter  60 value 78.749572
iter  70 value 77.850454
iter  80 value 77.659793
iter  90 value 77.212572
iter 100 value 77.017050
final  value 77.017050 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 118.484769 
iter  10 value 117.199218
iter  20 value 117.196577
iter  30 value 112.709317
iter  40 value 106.557652
iter  50 value 105.074892
iter  60 value 105.070467
final  value 105.069684 
converged
Fitting Repeat 2 

# weights:  305
initial  value 124.132203 
iter  10 value 117.895000
iter  20 value 117.642641
iter  30 value 106.672525
iter  40 value 102.797274
iter  50 value 101.751005
iter  60 value 101.485612
iter  70 value 101.460422
iter  80 value 101.105860
final  value 101.105761 
converged
Fitting Repeat 3 

# weights:  305
initial  value 144.499533 
iter  10 value 117.895575
iter  20 value 117.664014
iter  30 value 115.616610
final  value 115.616592 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.150151 
iter  10 value 117.895915
iter  20 value 117.834716
iter  30 value 117.515002
iter  40 value 117.513214
iter  50 value 117.512160
iter  60 value 117.511392
iter  70 value 117.509826
iter  80 value 117.070670
iter  90 value 115.696042
iter 100 value 115.165379
final  value 115.165379 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 127.203909 
iter  10 value 117.894995
iter  20 value 117.890374
iter  30 value 112.591213
iter  40 value 107.006038
iter  50 value 107.005037
iter  60 value 106.693530
iter  70 value 103.609007
iter  80 value 101.615803
iter  90 value 100.693238
iter 100 value 99.940485
final  value 99.940485 
stopped after 100 iterations
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 -- Wed Feb 22 06:43:30 2023 
*********************************************** 
Number of test functions: 8 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures
Number of test functions: 8 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: The `.data` argument of `add_column()` must have unique names as of tibble
3.0.0.
ℹ Use `.name_repair = "minimal"`.
ℹ The deprecated feature was likely used in the tibble package.
  Please report the issue at <https://github.com/tidyverse/tibble/issues>. 
2: `repeats` has no meaning for this resampling method. 
3: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 52.751   1.519  98.714