##############################################################################
##############################################################################
###
### 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/site-library --timings HPiP_1.7.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2023-03-12 r83975)
* 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 22.04.2 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.7.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       39.069  0.409  39.480
corr_plot     37.351  0.392  37.748
FSmethod      37.190  0.367  37.563
pred_ensembel 18.340  0.321  16.290
getFASTA       0.749  0.013   9.913
enrichfindP    0.426  0.036  14.953
* 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-devel_2023-03-12_r83975-bin/site-library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2023-03-12 r83975) -- "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
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 100.186346 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.579698 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.492275 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.729223 
iter  10 value 92.881635
iter  20 value 86.851096
iter  30 value 86.064237
iter  40 value 86.064021
final  value 86.064020 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.470549 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.235041 
iter  10 value 93.088709
iter  20 value 88.896505
iter  30 value 88.775576
iter  40 value 88.759956
iter  50 value 88.759027
iter  50 value 88.759027
iter  50 value 88.759027
final  value 88.759027 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.492012 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.784568 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.557469 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.223763 
final  value 94.400000 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.916427 
iter  10 value 94.443249
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.812968 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.925437 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.747344 
final  value 94.326054 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.696111 
iter  10 value 85.427917
iter  20 value 82.778235
iter  30 value 82.357208
final  value 82.356755 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.923849 
iter  10 value 94.484702
iter  20 value 88.868012
iter  30 value 87.702059
iter  40 value 86.342183
iter  50 value 85.264385
iter  60 value 84.194694
iter  70 value 83.165289
iter  80 value 82.727727
iter  90 value 82.260936
iter 100 value 81.756239
final  value 81.756239 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.416652 
iter  10 value 94.451856
iter  20 value 84.484623
iter  30 value 83.410574
iter  40 value 83.168926
iter  50 value 83.134957
iter  60 value 83.123459
final  value 83.123457 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.190420 
iter  10 value 93.532392
iter  20 value 85.751299
iter  30 value 84.044359
iter  40 value 83.648449
iter  50 value 82.732790
iter  60 value 82.437145
iter  70 value 82.382490
final  value 82.382463 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.072637 
iter  10 value 89.587933
iter  20 value 83.257717
iter  30 value 82.922962
iter  40 value 82.669874
iter  50 value 82.423208
iter  60 value 82.382464
final  value 82.382463 
converged
Fitting Repeat 5 

# weights:  103
initial  value 114.015116 
iter  10 value 94.578183
iter  20 value 94.488719
iter  30 value 84.946308
iter  40 value 82.795603
iter  50 value 82.242491
iter  60 value 81.785239
iter  70 value 81.347242
iter  80 value 81.111243
iter  90 value 81.020290
final  value 81.019369 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.576041 
iter  10 value 89.665211
iter  20 value 85.711129
iter  30 value 84.894022
iter  40 value 84.272666
iter  50 value 82.612573
iter  60 value 81.652377
iter  70 value 80.592185
iter  80 value 79.928327
iter  90 value 79.711921
iter 100 value 79.464186
final  value 79.464186 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.265630 
iter  10 value 94.496249
iter  20 value 94.421731
iter  30 value 89.827218
iter  40 value 88.127794
iter  50 value 85.086822
iter  60 value 81.064724
iter  70 value 80.503440
iter  80 value 80.259029
iter  90 value 80.213120
iter 100 value 80.203033
final  value 80.203033 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.152985 
iter  10 value 94.351898
iter  20 value 85.179158
iter  30 value 84.314265
iter  40 value 83.697134
iter  50 value 82.792150
iter  60 value 82.587441
iter  70 value 82.405015
iter  80 value 81.741120
iter  90 value 80.215415
iter 100 value 79.596765
final  value 79.596765 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.596235 
iter  10 value 94.508852
iter  20 value 83.375171
iter  30 value 82.876671
iter  40 value 82.633568
iter  50 value 82.564111
iter  60 value 82.407996
iter  70 value 81.054242
iter  80 value 79.838479
iter  90 value 79.701801
iter 100 value 79.659383
final  value 79.659383 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.417549 
iter  10 value 94.722226
iter  20 value 94.333732
iter  30 value 91.663139
iter  40 value 87.188723
iter  50 value 85.169590
iter  60 value 84.006625
iter  70 value 82.608644
iter  80 value 81.661026
iter  90 value 81.243147
iter 100 value 81.174310
final  value 81.174310 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.942145 
iter  10 value 94.718713
iter  20 value 92.301339
iter  30 value 89.911972
iter  40 value 83.126996
iter  50 value 82.029934
iter  60 value 80.604896
iter  70 value 79.639370
iter  80 value 79.440947
iter  90 value 79.223856
iter 100 value 78.940089
final  value 78.940089 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.728987 
iter  10 value 94.899822
iter  20 value 94.499360
iter  30 value 94.010956
iter  40 value 86.471378
iter  50 value 82.190414
iter  60 value 81.797323
iter  70 value 81.384003
iter  80 value 80.050441
iter  90 value 79.354964
iter 100 value 79.136299
final  value 79.136299 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.113502 
iter  10 value 94.965312
iter  20 value 94.400083
iter  30 value 84.418465
iter  40 value 83.807001
iter  50 value 83.340173
iter  60 value 81.899555
iter  70 value 80.844282
iter  80 value 80.115506
iter  90 value 79.889983
iter 100 value 79.436718
final  value 79.436718 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.339132 
iter  10 value 94.703265
iter  20 value 94.424102
iter  30 value 89.985609
iter  40 value 84.317796
iter  50 value 83.826822
iter  60 value 83.311642
iter  70 value 81.422837
iter  80 value 80.077098
iter  90 value 79.793366
iter 100 value 79.473748
final  value 79.473748 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.919032 
iter  10 value 94.824483
iter  20 value 93.815229
iter  30 value 82.974625
iter  40 value 80.945166
iter  50 value 80.449859
iter  60 value 80.043050
iter  70 value 79.423332
iter  80 value 79.072929
iter  90 value 78.917572
iter 100 value 78.791620
final  value 78.791620 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.860644 
final  value 94.485905 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.598859 
final  value 94.485987 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.447595 
final  value 93.932680 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.951319 
iter  10 value 94.485835
iter  20 value 94.394973
iter  30 value 88.064474
iter  40 value 88.030867
iter  50 value 88.026933
iter  60 value 88.023701
iter  70 value 88.015590
iter  80 value 88.013782
iter  90 value 88.010778
iter 100 value 83.297476
final  value 83.297476 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.751245 
final  value 94.485720 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.081982 
iter  10 value 94.488965
iter  20 value 94.481917
iter  30 value 83.859995
iter  40 value 83.573862
iter  50 value 83.558860
iter  60 value 83.554176
iter  70 value 83.432309
iter  80 value 83.300908
final  value 83.300764 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.600748 
iter  10 value 94.488873
iter  20 value 94.484282
final  value 94.484260 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.737246 
iter  10 value 94.488821
iter  20 value 94.436080
iter  30 value 87.055783
iter  40 value 82.950614
iter  50 value 82.946307
iter  60 value 82.945336
final  value 82.944907 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.091505 
iter  10 value 94.489102
iter  20 value 94.484401
iter  30 value 93.522398
iter  40 value 84.467967
iter  50 value 82.734461
iter  60 value 80.573191
iter  70 value 80.233602
iter  80 value 80.215401
iter  90 value 80.192977
iter  90 value 80.192977
final  value 80.192977 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.302674 
iter  10 value 94.447810
iter  20 value 94.265683
iter  30 value 85.992310
iter  40 value 85.854276
iter  50 value 85.400899
iter  60 value 84.748474
iter  70 value 81.328255
iter  80 value 79.920772
iter  90 value 79.523186
iter 100 value 79.518082
final  value 79.518082 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.437713 
iter  10 value 93.272725
iter  20 value 92.860855
iter  30 value 91.876907
iter  40 value 91.597035
iter  50 value 90.898941
iter  60 value 90.874814
final  value 90.874641 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.606614 
iter  10 value 94.491361
iter  20 value 91.745845
iter  30 value 83.556768
iter  40 value 83.554329
iter  50 value 83.527156
iter  60 value 83.523157
iter  60 value 83.523157
final  value 83.523157 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.486263 
iter  10 value 94.445722
iter  20 value 94.258404
iter  30 value 91.882342
iter  40 value 91.573363
final  value 91.562970 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.309548 
iter  10 value 94.451421
iter  20 value 94.444723
iter  30 value 89.219527
iter  40 value 83.896149
iter  50 value 83.146093
iter  60 value 83.054553
final  value 83.054525 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.873483 
iter  10 value 94.489576
iter  20 value 90.191925
iter  30 value 89.795319
iter  40 value 89.766656
iter  50 value 83.571121
iter  60 value 83.562365
iter  70 value 83.457230
iter  80 value 83.393997
iter  90 value 83.379121
iter 100 value 82.831761
final  value 82.831761 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.423455 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.810681 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.006931 
iter  10 value 94.484217
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.324503 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.276751 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.136169 
iter  10 value 94.212061
final  value 94.147058 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.980638 
final  value 94.449438 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.522785 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.099804 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.705526 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.292780 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.218816 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.085469 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.469380 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.928422 
final  value 94.453333 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.691315 
iter  10 value 93.904378
iter  20 value 91.796534
iter  30 value 91.667082
iter  40 value 91.637609
iter  50 value 91.611107
iter  60 value 91.599473
final  value 91.599467 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.549512 
iter  10 value 94.522593
iter  20 value 93.914445
iter  30 value 89.168591
iter  40 value 87.141239
iter  50 value 86.339157
iter  60 value 85.167094
iter  70 value 84.442320
iter  80 value 84.288004
iter  90 value 83.747382
iter 100 value 83.626169
final  value 83.626169 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.476079 
iter  10 value 93.604203
iter  20 value 87.991504
iter  30 value 86.837282
iter  40 value 86.514276
iter  50 value 86.409368
iter  60 value 86.276057
iter  70 value 86.098888
iter  80 value 86.097976
iter  80 value 86.097975
iter  80 value 86.097975
final  value 86.097975 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.182984 
iter  10 value 94.486872
iter  20 value 93.862822
iter  30 value 89.655268
iter  40 value 88.015539
iter  50 value 86.825309
iter  60 value 85.799325
iter  70 value 84.895903
iter  80 value 84.673988
iter  90 value 84.533127
iter 100 value 83.948918
final  value 83.948918 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.025972 
iter  10 value 94.488580
iter  20 value 93.232309
iter  30 value 90.133971
iter  40 value 86.943336
iter  50 value 86.061990
iter  60 value 85.873030
iter  70 value 83.986236
iter  80 value 83.940106
iter  90 value 83.906762
iter 100 value 83.882390
final  value 83.882390 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.964708 
iter  10 value 94.718021
iter  20 value 87.777687
iter  30 value 86.896992
iter  40 value 86.710748
iter  50 value 86.506364
iter  60 value 86.448236
iter  70 value 86.347164
iter  80 value 85.431000
iter  90 value 85.100802
iter 100 value 85.028596
final  value 85.028596 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.680262 
iter  10 value 94.380324
iter  20 value 91.231685
iter  30 value 90.035768
iter  40 value 89.231270
iter  50 value 87.824728
iter  60 value 85.836288
iter  70 value 83.441009
iter  80 value 83.098685
iter  90 value 82.722220
iter 100 value 82.695404
final  value 82.695404 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.009082 
iter  10 value 94.608774
iter  20 value 92.080986
iter  30 value 88.890241
iter  40 value 88.262021
iter  50 value 86.138148
iter  60 value 84.380050
iter  70 value 83.842082
iter  80 value 83.668668
iter  90 value 83.120808
iter 100 value 82.838590
final  value 82.838590 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.709168 
iter  10 value 94.358717
iter  20 value 91.986297
iter  30 value 88.749307
iter  40 value 84.994528
iter  50 value 84.856445
iter  60 value 84.701460
iter  70 value 84.414438
iter  80 value 84.055705
iter  90 value 83.864005
iter 100 value 83.821565
final  value 83.821565 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 124.071125 
iter  10 value 94.032504
iter  20 value 90.473382
iter  30 value 88.669213
iter  40 value 87.514531
iter  50 value 86.077814
iter  60 value 85.458946
iter  70 value 85.075243
iter  80 value 84.019913
iter  90 value 83.809940
iter 100 value 83.512608
final  value 83.512608 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.314469 
iter  10 value 94.793753
iter  20 value 86.366528
iter  30 value 83.759413
iter  40 value 83.470666
iter  50 value 82.992955
iter  60 value 82.746296
iter  70 value 82.594284
iter  80 value 82.422221
iter  90 value 82.294907
iter 100 value 82.240204
final  value 82.240204 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.165680 
iter  10 value 94.587971
iter  20 value 93.141286
iter  30 value 92.183870
iter  40 value 88.466895
iter  50 value 85.948371
iter  60 value 84.350542
iter  70 value 83.823468
iter  80 value 83.263344
iter  90 value 83.041653
iter 100 value 82.951501
final  value 82.951501 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.830125 
iter  10 value 94.679949
iter  20 value 94.600932
iter  30 value 90.716000
iter  40 value 85.591111
iter  50 value 84.615342
iter  60 value 84.361571
iter  70 value 84.171812
iter  80 value 84.125657
iter  90 value 83.684717
iter 100 value 83.318945
final  value 83.318945 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.729741 
iter  10 value 94.675751
iter  20 value 94.500289
iter  30 value 89.460040
iter  40 value 89.209752
iter  50 value 88.315065
iter  60 value 87.531382
iter  70 value 86.519053
iter  80 value 85.970994
iter  90 value 85.885542
iter 100 value 85.358996
final  value 85.358996 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.896146 
iter  10 value 94.469007
iter  20 value 88.688423
iter  30 value 87.778780
iter  40 value 85.809786
iter  50 value 84.920500
iter  60 value 84.636896
iter  70 value 84.507107
iter  80 value 84.028472
iter  90 value 83.616749
iter 100 value 83.561049
final  value 83.561049 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.474443 
final  value 94.485775 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.820931 
iter  10 value 94.486000
iter  20 value 94.098871
iter  30 value 88.953053
iter  40 value 88.890415
iter  50 value 88.054779
iter  60 value 87.972022
iter  70 value 87.971913
iter  80 value 87.860301
iter  90 value 87.057523
iter 100 value 86.437489
final  value 86.437489 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.865082 
final  value 94.485667 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.471587 
final  value 94.488181 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.864923 
iter  10 value 94.356067
iter  20 value 93.683805
iter  30 value 88.153767
final  value 88.079774 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.530461 
iter  10 value 94.488547
iter  20 value 94.454526
iter  30 value 94.354454
iter  30 value 94.354454
iter  30 value 94.354454
final  value 94.354454 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.295253 
iter  10 value 94.487986
iter  20 value 94.456950
iter  30 value 93.662179
iter  40 value 93.661634
final  value 93.661624 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.339999 
iter  10 value 94.488829
iter  20 value 94.480321
iter  30 value 94.385915
iter  40 value 92.260006
iter  50 value 90.592247
iter  60 value 90.591412
final  value 90.591358 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.112035 
iter  10 value 94.488593
iter  20 value 94.258555
iter  30 value 92.949741
iter  40 value 91.330579
iter  50 value 91.245572
iter  60 value 91.216132
iter  70 value 91.215984
final  value 91.215977 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.247200 
iter  10 value 94.316857
iter  20 value 94.310968
final  value 94.308555 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.975609 
iter  10 value 94.492432
iter  20 value 94.395429
iter  30 value 88.583024
iter  40 value 86.491463
iter  50 value 86.308268
iter  60 value 83.794698
iter  70 value 83.075015
iter  80 value 82.984333
iter  90 value 82.835172
iter 100 value 82.826663
final  value 82.826663 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.022584 
iter  10 value 94.492051
iter  20 value 94.481144
iter  30 value 93.876248
iter  40 value 88.379450
iter  50 value 88.026598
iter  60 value 85.929929
iter  70 value 85.605036
iter  80 value 85.571235
iter  90 value 85.535361
iter 100 value 85.535112
final  value 85.535112 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.404541 
iter  10 value 94.491423
iter  20 value 92.766812
iter  30 value 92.607603
iter  40 value 91.596389
iter  50 value 91.406241
final  value 91.342538 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.795406 
iter  10 value 94.493245
iter  20 value 94.171741
iter  30 value 88.818384
iter  40 value 88.817226
iter  50 value 88.765218
iter  60 value 87.835731
iter  70 value 86.779522
iter  80 value 86.779112
iter  90 value 86.768864
iter 100 value 86.755785
final  value 86.755785 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.901060 
iter  10 value 94.362249
iter  20 value 94.333130
iter  30 value 94.308472
iter  40 value 94.304573
final  value 94.304492 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.279044 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.236015 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.084514 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.873696 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.403829 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.082873 
final  value 93.008964 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.235594 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.169094 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.987487 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.097353 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.047079 
final  value 93.356643 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.327804 
iter  10 value 91.736482
iter  20 value 91.732288
final  value 91.732281 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.148759 
final  value 93.455030 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.536893 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.595040 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.445802 
iter  10 value 94.016990
iter  20 value 92.964179
iter  30 value 92.929553
iter  40 value 92.894489
iter  50 value 92.019512
iter  60 value 86.768371
iter  70 value 83.361402
iter  80 value 82.588598
iter  90 value 82.267869
iter 100 value 81.729953
final  value 81.729953 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.058687 
iter  10 value 94.054394
iter  20 value 92.986507
iter  30 value 92.915548
iter  40 value 92.768900
iter  50 value 92.716761
iter  60 value 87.737406
iter  70 value 86.012167
iter  80 value 83.366073
iter  90 value 82.282732
iter 100 value 81.619799
final  value 81.619799 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 112.351903 
iter  10 value 93.403001
iter  20 value 92.765556
iter  30 value 89.957269
iter  40 value 85.939005
iter  50 value 83.787606
iter  60 value 83.493253
iter  70 value 83.079796
iter  80 value 82.054724
iter  90 value 81.626907
iter 100 value 81.225010
final  value 81.225010 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 111.878531 
iter  10 value 94.028944
iter  20 value 93.571768
iter  30 value 93.438770
iter  40 value 90.465810
iter  50 value 84.943562
iter  60 value 82.396191
iter  70 value 81.933191
iter  80 value 81.116218
iter  90 value 80.963302
iter 100 value 80.795902
final  value 80.795902 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.925103 
iter  10 value 93.813064
iter  20 value 93.063351
iter  30 value 91.349127
iter  40 value 86.950551
iter  50 value 83.542208
iter  60 value 82.144690
iter  70 value 82.057540
iter  80 value 81.993152
iter  90 value 81.559560
iter 100 value 81.137981
final  value 81.137981 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.220715 
iter  10 value 94.207354
iter  20 value 94.035558
iter  30 value 88.590140
iter  40 value 86.319391
iter  50 value 85.352996
iter  60 value 85.102604
iter  70 value 84.997359
iter  80 value 83.463822
iter  90 value 81.534083
iter 100 value 80.221811
final  value 80.221811 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.357392 
iter  10 value 93.667731
iter  20 value 89.230685
iter  30 value 86.796483
iter  40 value 86.377818
iter  50 value 84.690365
iter  60 value 84.052477
iter  70 value 81.115573
iter  80 value 79.773184
iter  90 value 79.044069
iter 100 value 78.774317
final  value 78.774317 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 140.754588 
iter  10 value 100.468482
iter  20 value 94.121342
iter  30 value 87.756438
iter  40 value 84.774025
iter  50 value 84.152344
iter  60 value 84.026498
iter  70 value 83.943431
iter  80 value 83.665220
iter  90 value 83.618891
iter 100 value 83.408295
final  value 83.408295 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.917864 
iter  10 value 93.888709
iter  20 value 92.934014
iter  30 value 86.085275
iter  40 value 85.146933
iter  50 value 83.169261
iter  60 value 82.017211
iter  70 value 81.427021
iter  80 value 80.906689
iter  90 value 80.317523
iter 100 value 79.580204
final  value 79.580204 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.235326 
iter  10 value 94.106927
iter  20 value 93.909297
iter  30 value 88.199955
iter  40 value 85.542838
iter  50 value 85.412405
iter  60 value 82.282053
iter  70 value 79.868341
iter  80 value 79.044293
iter  90 value 78.860351
iter 100 value 78.737038
final  value 78.737038 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.409447 
iter  10 value 93.940154
iter  20 value 91.525793
iter  30 value 86.497283
iter  40 value 83.962393
iter  50 value 83.645647
iter  60 value 81.968750
iter  70 value 80.701482
iter  80 value 80.339862
iter  90 value 80.213391
iter 100 value 79.824389
final  value 79.824389 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.638023 
iter  10 value 93.836619
iter  20 value 85.754883
iter  30 value 82.988711
iter  40 value 81.977246
iter  50 value 81.528735
iter  60 value 79.810706
iter  70 value 78.935737
iter  80 value 78.864838
iter  90 value 78.772572
iter 100 value 78.730262
final  value 78.730262 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.382477 
iter  10 value 94.085060
iter  20 value 86.607365
iter  30 value 84.953411
iter  40 value 83.507513
iter  50 value 82.151942
iter  60 value 80.848189
iter  70 value 79.608394
iter  80 value 79.251106
iter  90 value 79.203220
iter 100 value 79.189176
final  value 79.189176 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.497431 
iter  10 value 93.229136
iter  20 value 83.822696
iter  30 value 81.649233
iter  40 value 80.194484
iter  50 value 79.599527
iter  60 value 79.426443
iter  70 value 79.287003
iter  80 value 79.256292
iter  90 value 79.204466
iter 100 value 78.952067
final  value 78.952067 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.057441 
iter  10 value 94.382745
iter  20 value 94.075826
iter  30 value 93.783340
iter  40 value 89.413428
iter  50 value 87.595176
iter  60 value 84.557392
iter  70 value 82.704355
iter  80 value 81.310547
iter  90 value 80.387796
iter 100 value 80.180660
final  value 80.180660 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.959577 
final  value 94.054541 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.384385 
final  value 94.054398 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.056693 
final  value 94.054594 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.667046 
final  value 94.054361 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.068643 
iter  10 value 93.978274
iter  20 value 93.977188
iter  30 value 93.340077
final  value 93.337652 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.607188 
iter  10 value 94.038040
iter  20 value 94.033247
iter  30 value 89.149199
iter  40 value 83.967359
iter  50 value 83.952417
iter  60 value 83.817318
final  value 83.816859 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.444740 
iter  10 value 90.901734
iter  20 value 83.871422
iter  30 value 80.193488
iter  40 value 79.187669
iter  50 value 78.820196
iter  60 value 78.817579
iter  70 value 78.815088
iter  80 value 78.810413
iter  90 value 78.806653
iter 100 value 78.750490
final  value 78.750490 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.400555 
iter  10 value 94.066082
iter  20 value 94.058684
iter  30 value 92.839578
iter  40 value 92.837235
iter  50 value 92.835188
iter  60 value 92.803892
iter  70 value 83.576937
iter  80 value 83.549463
iter  90 value 83.540313
iter 100 value 83.538688
final  value 83.538688 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.639360 
iter  10 value 92.608430
iter  20 value 92.606763
iter  30 value 92.602209
iter  40 value 92.530260
iter  50 value 88.061735
iter  60 value 87.983664
iter  70 value 85.849755
final  value 85.847261 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.391885 
iter  10 value 92.836073
iter  20 value 92.831752
iter  30 value 92.684692
iter  40 value 82.947427
iter  50 value 82.167181
iter  60 value 82.081476
iter  70 value 81.926474
iter  80 value 81.901611
iter  90 value 81.901492
iter 100 value 81.899620
final  value 81.899620 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.004499 
iter  10 value 94.040405
iter  20 value 93.503117
iter  30 value 91.666781
iter  40 value 82.784879
iter  50 value 81.425733
iter  60 value 81.192165
iter  70 value 79.602783
iter  80 value 78.623020
iter  90 value 78.512702
iter 100 value 78.510734
final  value 78.510734 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.446071 
iter  10 value 87.234302
iter  20 value 84.095333
iter  30 value 84.087347
iter  40 value 84.083116
iter  50 value 83.937498
iter  60 value 82.906419
iter  70 value 79.649407
iter  80 value 79.160941
iter  90 value 78.478345
iter 100 value 78.462675
final  value 78.462675 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.488386 
iter  10 value 94.060354
iter  20 value 91.770983
iter  30 value 83.738725
iter  40 value 83.419811
iter  50 value 83.214495
iter  60 value 83.137017
iter  70 value 83.134641
iter  80 value 83.132643
iter  90 value 83.131952
iter 100 value 83.066697
final  value 83.066697 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.326542 
iter  10 value 93.675857
iter  20 value 92.152026
iter  30 value 86.263370
iter  40 value 85.333256
iter  50 value 85.328645
iter  60 value 83.715889
iter  70 value 83.715216
iter  80 value 83.707657
iter  90 value 83.662268
iter 100 value 83.568075
final  value 83.568075 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.988894 
iter  10 value 93.711760
iter  20 value 93.308952
iter  30 value 93.304961
iter  40 value 91.394221
iter  50 value 83.991766
iter  60 value 83.743880
iter  70 value 83.706965
final  value 83.706961 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.760922 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.409829 
iter  10 value 94.307552
iter  20 value 94.304611
final  value 94.304609 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.331334 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.696813 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.672507 
iter  10 value 88.590642
final  value 88.580617 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.245927 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.070636 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.577616 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 151.024024 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.374470 
final  value 94.046703 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.462577 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.035162 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.501635 
iter  10 value 92.159721
iter  20 value 91.683410
iter  30 value 91.673403
final  value 91.673078 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.999601 
iter  10 value 94.466667
iter  10 value 94.466667
iter  10 value 94.466667
final  value 94.466667 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.344362 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.833671 
iter  10 value 94.468428
iter  20 value 92.503253
iter  30 value 85.603173
iter  40 value 85.490873
iter  50 value 84.913837
iter  60 value 84.591048
iter  70 value 84.414589
iter  80 value 84.392263
final  value 84.392216 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.645851 
iter  10 value 94.307999
iter  20 value 90.302918
iter  30 value 88.046401
iter  40 value 87.403605
iter  50 value 86.082448
iter  60 value 85.552880
iter  70 value 85.036359
iter  80 value 83.151357
iter  90 value 83.072102
final  value 83.072067 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.722302 
iter  10 value 94.489284
iter  20 value 94.059084
iter  30 value 87.209958
iter  40 value 86.046937
iter  50 value 85.249456
iter  60 value 84.206536
iter  70 value 83.788010
iter  80 value 83.381172
final  value 83.380175 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.781975 
iter  10 value 94.486562
iter  20 value 94.409636
iter  30 value 89.901343
iter  40 value 89.636145
iter  50 value 87.579180
iter  60 value 86.296858
iter  70 value 84.194523
iter  80 value 83.435092
iter  90 value 83.129657
iter 100 value 83.072070
final  value 83.072070 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.502746 
iter  10 value 94.298165
iter  20 value 87.443156
iter  30 value 85.914498
iter  40 value 85.380495
iter  50 value 85.235497
iter  60 value 85.108371
iter  70 value 84.919598
iter  80 value 84.871861
final  value 84.870327 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.829072 
iter  10 value 94.222667
iter  20 value 88.736816
iter  30 value 86.141634
iter  40 value 85.246436
iter  50 value 85.020450
iter  60 value 84.872932
iter  70 value 84.611592
iter  80 value 84.578787
iter  90 value 84.211651
iter 100 value 82.858627
final  value 82.858627 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.208350 
iter  10 value 94.546774
iter  20 value 93.848058
iter  30 value 90.103613
iter  40 value 89.434628
iter  50 value 86.663903
iter  60 value 84.660926
iter  70 value 84.277663
iter  80 value 84.032030
iter  90 value 83.544137
iter 100 value 82.894117
final  value 82.894117 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.410713 
iter  10 value 85.972371
iter  20 value 85.429820
iter  30 value 84.267834
iter  40 value 83.786540
iter  50 value 83.125813
iter  60 value 82.379567
iter  70 value 81.859220
iter  80 value 81.733112
iter  90 value 81.693374
iter 100 value 81.657703
final  value 81.657703 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.038200 
iter  10 value 94.522380
iter  20 value 94.304541
iter  30 value 89.206137
iter  40 value 87.752409
iter  50 value 87.332101
iter  60 value 85.610719
iter  70 value 82.424887
iter  80 value 81.959150
iter  90 value 81.826293
iter 100 value 81.695225
final  value 81.695225 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.055625 
iter  10 value 94.456993
iter  20 value 89.888384
iter  30 value 86.928820
iter  40 value 86.059973
iter  50 value 85.151093
iter  60 value 84.208488
iter  70 value 84.164006
iter  80 value 84.093515
iter  90 value 83.637689
iter 100 value 82.086007
final  value 82.086007 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.839757 
iter  10 value 94.795175
iter  20 value 94.453526
iter  30 value 89.780296
iter  40 value 87.630846
iter  50 value 83.911377
iter  60 value 82.622976
iter  70 value 82.223644
iter  80 value 82.071480
iter  90 value 81.956018
iter 100 value 81.650307
final  value 81.650307 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.485575 
iter  10 value 96.133487
iter  20 value 95.347324
iter  30 value 85.965344
iter  40 value 85.531648
iter  50 value 84.710469
iter  60 value 82.824067
iter  70 value 82.189762
iter  80 value 82.086627
iter  90 value 81.729664
iter 100 value 81.656271
final  value 81.656271 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.825848 
iter  10 value 94.694845
iter  20 value 92.158918
iter  30 value 89.886538
iter  40 value 88.616774
iter  50 value 84.792353
iter  60 value 83.398039
iter  70 value 82.416044
iter  80 value 82.152691
iter  90 value 81.932672
iter 100 value 81.675074
final  value 81.675074 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 124.402581 
iter  10 value 94.466472
iter  20 value 92.275608
iter  30 value 89.913978
iter  40 value 89.119277
iter  50 value 88.957918
iter  60 value 88.729025
iter  70 value 86.860030
iter  80 value 85.532738
iter  90 value 83.086643
iter 100 value 82.881536
final  value 82.881536 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.597044 
iter  10 value 94.785046
iter  20 value 94.490343
iter  30 value 94.488773
iter  40 value 94.441490
iter  50 value 92.962492
iter  60 value 89.482302
iter  70 value 88.148692
iter  80 value 86.327723
iter  90 value 85.493080
iter 100 value 84.395393
final  value 84.395393 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.228055 
iter  10 value 94.485884
final  value 94.484215 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.779799 
final  value 94.485892 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.549521 
final  value 94.485958 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.875229 
iter  10 value 94.486005
final  value 94.484219 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.759171 
final  value 94.486019 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.591608 
iter  10 value 94.488956
iter  20 value 94.447154
iter  30 value 88.638144
iter  40 value 87.156079
iter  50 value 81.446880
iter  60 value 80.373082
iter  70 value 80.370175
iter  80 value 80.369588
final  value 80.369385 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.410147 
iter  10 value 94.052312
iter  20 value 93.363726
iter  30 value 88.741549
iter  40 value 88.598410
iter  50 value 88.583725
final  value 88.583673 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.894555 
iter  10 value 94.471661
iter  20 value 94.468758
iter  20 value 94.468758
iter  20 value 94.468758
final  value 94.468758 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.276551 
iter  10 value 94.488945
iter  20 value 94.484232
final  value 94.484227 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.129444 
iter  10 value 94.488695
iter  20 value 94.484452
iter  30 value 91.450500
iter  40 value 87.374354
iter  50 value 87.292840
iter  60 value 87.292569
iter  70 value 87.283562
iter  80 value 86.685682
iter  90 value 80.851616
iter 100 value 80.275669
final  value 80.275669 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.654370 
iter  10 value 94.492666
iter  20 value 94.161632
iter  30 value 88.822196
iter  40 value 88.742089
iter  50 value 86.867431
iter  60 value 86.838729
iter  70 value 86.210219
iter  80 value 83.718399
iter  90 value 83.691645
iter 100 value 83.688948
final  value 83.688948 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.693421 
iter  10 value 94.392120
iter  20 value 85.016303
iter  30 value 84.727485
iter  40 value 83.776574
final  value 83.776482 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.558563 
iter  10 value 94.475156
iter  20 value 94.471148
iter  30 value 94.470225
iter  40 value 94.182743
iter  50 value 89.802644
iter  60 value 88.021788
iter  70 value 84.277920
iter  80 value 81.077840
iter  90 value 80.950771
iter 100 value 80.548395
final  value 80.548395 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.941880 
iter  10 value 94.492436
iter  20 value 94.458997
iter  30 value 93.944399
iter  40 value 90.449236
iter  50 value 90.356803
iter  60 value 90.356506
iter  70 value 90.111406
iter  80 value 89.864035
iter  90 value 89.862808
iter 100 value 89.862541
final  value 89.862541 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.690497 
iter  10 value 94.475657
iter  20 value 94.471198
iter  30 value 94.440527
iter  40 value 87.527072
iter  50 value 85.740661
iter  60 value 83.779151
iter  70 value 81.016614
iter  80 value 80.305919
iter  90 value 80.202173
iter 100 value 80.073264
final  value 80.073264 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.486513 
iter  10 value 92.646020
iter  20 value 83.509838
iter  30 value 83.412102
iter  40 value 82.474469
final  value 82.461043 
converged
Fitting Repeat 2 

# weights:  103
initial  value 123.494438 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.469820 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.109008 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.182690 
final  value 92.211111 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.268318 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.929963 
iter  10 value 93.328267
final  value 93.328261 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.870827 
iter  10 value 93.328281
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.186993 
iter  10 value 92.211121
final  value 92.211111 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.145624 
iter  10 value 93.809177
iter  20 value 93.804885
final  value 93.804878 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.690892 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.001044 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.488084 
iter  10 value 93.048077
iter  20 value 88.804750
iter  30 value 82.752459
iter  40 value 82.740245
iter  50 value 82.717918
iter  60 value 82.715109
iter  60 value 82.715109
iter  60 value 82.715109
final  value 82.715109 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.587940 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.393609 
iter  10 value 91.666797
final  value 91.666671 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.865542 
iter  10 value 94.108058
iter  20 value 85.191474
iter  30 value 83.307401
iter  40 value 82.088988
iter  50 value 79.164867
iter  60 value 78.219921
iter  70 value 78.021300
iter  80 value 77.685861
iter  90 value 77.560021
final  value 77.559995 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.538447 
iter  10 value 93.893292
iter  20 value 83.575339
iter  30 value 82.569121
iter  40 value 81.396188
iter  50 value 81.231520
iter  60 value 81.182336
iter  70 value 81.169001
final  value 81.169001 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.801690 
iter  10 value 94.047622
iter  20 value 83.257654
iter  30 value 82.437227
iter  40 value 81.653654
iter  50 value 81.612605
iter  60 value 81.595427
final  value 81.593652 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.407648 
iter  10 value 93.953337
iter  20 value 93.537070
iter  30 value 93.009503
iter  40 value 90.463813
iter  50 value 88.142775
iter  60 value 87.964621
iter  70 value 86.685070
iter  80 value 82.189122
iter  90 value 81.626853
iter 100 value 81.443508
final  value 81.443508 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.681503 
iter  10 value 94.597851
iter  20 value 93.719199
iter  30 value 88.460949
iter  40 value 82.699749
iter  50 value 82.370452
iter  60 value 81.604266
iter  70 value 81.027447
iter  80 value 81.020998
final  value 81.020902 
converged
Fitting Repeat 1 

# weights:  305
initial  value 131.567487 
iter  10 value 94.618267
iter  20 value 91.609316
iter  30 value 85.093449
iter  40 value 84.344995
iter  50 value 83.255758
iter  60 value 78.894551
iter  70 value 77.515633
iter  80 value 77.254243
iter  90 value 76.934233
iter 100 value 76.768143
final  value 76.768143 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.482707 
iter  10 value 94.100506
iter  20 value 93.936416
iter  30 value 93.187369
iter  40 value 88.466494
iter  50 value 80.540121
iter  60 value 78.158470
iter  70 value 76.720616
iter  80 value 76.249367
iter  90 value 76.177273
iter 100 value 76.089895
final  value 76.089895 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.400771 
iter  10 value 94.045108
iter  20 value 88.837813
iter  30 value 82.736741
iter  40 value 81.851851
iter  50 value 79.747708
iter  60 value 78.336906
iter  70 value 77.867410
iter  80 value 77.808830
iter  90 value 77.792796
final  value 77.792790 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.460334 
iter  10 value 94.090560
iter  20 value 93.919306
iter  30 value 87.718860
iter  40 value 85.551107
iter  50 value 82.535670
iter  60 value 81.544531
iter  70 value 81.471974
iter  80 value 80.851669
iter  90 value 79.399625
iter 100 value 79.250171
final  value 79.250171 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.927151 
iter  10 value 94.011311
iter  20 value 82.979031
iter  30 value 79.629343
iter  40 value 78.535911
iter  50 value 78.154214
iter  60 value 77.741083
iter  70 value 77.457994
iter  80 value 77.448474
iter  90 value 77.438263
iter 100 value 77.348984
final  value 77.348984 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.249519 
iter  10 value 94.309276
iter  20 value 88.178812
iter  30 value 84.072156
iter  40 value 81.697037
iter  50 value 81.022890
iter  60 value 78.898503
iter  70 value 77.520967
iter  80 value 76.739731
iter  90 value 76.477553
iter 100 value 76.415162
final  value 76.415162 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.957356 
iter  10 value 90.950097
iter  20 value 84.202439
iter  30 value 83.365042
iter  40 value 82.015003
iter  50 value 80.904435
iter  60 value 80.314215
iter  70 value 79.750962
iter  80 value 78.786709
iter  90 value 78.310383
iter 100 value 77.718621
final  value 77.718621 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.289166 
iter  10 value 96.158193
iter  20 value 88.810495
iter  30 value 83.675489
iter  40 value 80.446896
iter  50 value 78.406465
iter  60 value 77.287992
iter  70 value 76.988899
iter  80 value 76.822710
iter  90 value 76.701319
iter 100 value 76.630180
final  value 76.630180 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.859672 
iter  10 value 94.051658
iter  20 value 86.925912
iter  30 value 83.163044
iter  40 value 82.695273
iter  50 value 81.862728
iter  60 value 80.532164
iter  70 value 78.998701
iter  80 value 76.939593
iter  90 value 76.264357
iter 100 value 76.019317
final  value 76.019317 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.886360 
iter  10 value 96.776669
iter  20 value 85.569396
iter  30 value 80.661534
iter  40 value 79.728927
iter  50 value 78.594660
iter  60 value 78.330183
iter  70 value 78.159325
iter  80 value 77.859765
iter  90 value 77.398979
iter 100 value 77.130465
final  value 77.130465 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.372159 
final  value 94.054599 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.254483 
iter  10 value 94.054589
iter  20 value 94.052914
iter  30 value 93.778668
final  value 93.714611 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.565103 
final  value 93.358333 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.115746 
iter  10 value 94.054390
iter  20 value 94.052913
iter  30 value 93.755767
final  value 93.357246 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.545866 
iter  10 value 93.330198
iter  20 value 93.328900
final  value 93.328610 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.846292 
iter  10 value 93.333907
iter  20 value 93.333106
iter  30 value 93.116650
iter  40 value 93.111339
iter  40 value 93.111339
final  value 93.111339 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.513694 
iter  10 value 94.056795
iter  20 value 94.052920
final  value 94.052919 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.702076 
iter  10 value 94.057247
iter  20 value 93.977024
iter  30 value 93.329534
final  value 93.329527 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.706252 
iter  10 value 92.807810
iter  20 value 83.725632
iter  30 value 80.515745
iter  40 value 80.171792
iter  50 value 80.010968
iter  60 value 79.773717
iter  70 value 79.768204
iter  80 value 79.757338
iter  90 value 79.757124
iter 100 value 79.754511
final  value 79.754511 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.183392 
iter  10 value 94.057810
iter  20 value 93.606952
iter  30 value 93.143419
final  value 93.111387 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.180192 
iter  10 value 93.336955
iter  20 value 93.330566
iter  30 value 93.154556
iter  40 value 82.529156
iter  50 value 82.051626
iter  60 value 78.833517
iter  70 value 78.717901
iter  80 value 78.703462
iter  90 value 78.703372
iter 100 value 78.636312
final  value 78.636312 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 91.542995 
iter  10 value 83.594789
iter  20 value 81.720409
iter  30 value 81.126507
iter  40 value 80.910536
iter  50 value 80.908829
iter  60 value 80.039567
iter  70 value 79.704135
iter  80 value 79.703012
iter  90 value 79.701969
final  value 79.701960 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.796736 
iter  10 value 94.061015
iter  20 value 94.054591
iter  30 value 92.898235
iter  40 value 90.080657
iter  50 value 81.752369
iter  60 value 81.658232
iter  70 value 78.829681
iter  80 value 78.587828
iter  90 value 78.568539
iter 100 value 78.567929
final  value 78.567929 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.671515 
iter  10 value 94.060396
iter  20 value 91.556891
iter  30 value 91.508383
iter  40 value 90.927377
iter  50 value 90.822833
iter  60 value 90.822407
iter  60 value 90.822406
iter  60 value 90.822406
final  value 90.822406 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.456793 
iter  10 value 88.443150
iter  20 value 82.379825
iter  30 value 81.648200
iter  40 value 81.376071
iter  50 value 79.833119
iter  60 value 79.811700
iter  70 value 79.650951
iter  80 value 79.496201
iter  90 value 79.493915
iter 100 value 79.441736
final  value 79.441736 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.033535 
iter  10 value 117.266195
iter  20 value 107.939143
iter  30 value 106.544801
iter  40 value 105.156354
iter  50 value 104.673116
iter  60 value 103.616399
iter  70 value 102.517386
iter  80 value 102.139603
iter  90 value 101.611522
iter 100 value 101.110489
final  value 101.110489 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 135.964789 
iter  10 value 118.548266
iter  20 value 114.470738
iter  30 value 106.183997
iter  40 value 105.608978
iter  50 value 105.297217
iter  60 value 104.306931
iter  70 value 103.178765
iter  80 value 102.799892
iter  90 value 102.353402
iter 100 value 102.029357
final  value 102.029357 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 139.354375 
iter  10 value 116.956271
iter  20 value 108.350488
iter  30 value 105.722205
iter  40 value 105.158102
iter  50 value 104.021352
iter  60 value 102.547099
iter  70 value 102.168723
iter  80 value 101.430332
iter  90 value 101.141009
iter 100 value 100.863303
final  value 100.863303 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.792045 
iter  10 value 117.702322
iter  20 value 110.394686
iter  30 value 108.522543
iter  40 value 103.672507
iter  50 value 102.167894
iter  60 value 101.361235
iter  70 value 101.137574
iter  80 value 101.020033
iter  90 value 101.007201
iter 100 value 100.965999
final  value 100.965999 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 147.232538 
iter  10 value 117.327984
iter  20 value 107.198607
iter  30 value 103.542832
iter  40 value 102.934880
iter  50 value 102.107468
iter  60 value 101.759549
iter  70 value 101.564218
iter  80 value 101.168893
iter  90 value 101.151819
iter 100 value 101.124682
final  value 101.124682 
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 -- Tue May  9 18:44:53 2023 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 54.666   1.418  66.855