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


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    gcc (GCC) 12.2.1 20220819 (openEuler 12.2.1-14)
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       40.769  0.831  41.669
corr_plot     38.693  0.559  39.318
FSmethod      38.269  0.523  38.864
pred_ensembel 18.421  0.325  16.369
enrichfindP    0.510  0.036  20.096
getFASTA       0.086  0.008  18.095
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

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


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

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

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

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

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

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

# weights:  103
initial  value 95.723231 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.437249 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.670243 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.046491 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.096024 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.795116 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.170419 
iter  10 value 92.762065
iter  20 value 91.628612
final  value 91.586490 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.170560 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.139212 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.675981 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.191377 
iter  10 value 86.047055
iter  20 value 81.840420
iter  30 value 81.574922
final  value 81.574760 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.878411 
iter  10 value 94.090550
iter  20 value 93.613834
final  value 93.612698 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.705805 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.720106 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.172965 
iter  10 value 93.088900
final  value 93.088889 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.074413 
iter  10 value 88.848228
iter  20 value 84.341976
iter  30 value 83.256440
iter  40 value 82.765911
iter  50 value 82.563582
iter  60 value 82.530342
iter  70 value 82.396487
final  value 82.386664 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.871063 
iter  10 value 94.487557
iter  20 value 94.110692
iter  30 value 85.928050
iter  40 value 82.798145
iter  50 value 82.553289
iter  60 value 82.437376
iter  70 value 82.407018
iter  80 value 82.043363
iter  90 value 81.478554
iter 100 value 81.414084
final  value 81.414084 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.487111 
iter  10 value 94.446990
iter  20 value 85.176581
iter  30 value 83.866303
iter  40 value 83.573120
iter  50 value 83.210358
iter  60 value 82.618514
iter  70 value 82.443968
iter  80 value 82.407475
iter  90 value 82.386664
iter  90 value 82.386663
iter  90 value 82.386663
final  value 82.386663 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.676882 
iter  10 value 94.372631
iter  20 value 93.848887
iter  30 value 90.382371
iter  40 value 83.863937
iter  50 value 83.209114
iter  60 value 82.714832
iter  70 value 82.034360
iter  80 value 81.995941
final  value 81.995930 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.693678 
iter  10 value 94.486749
iter  20 value 93.864254
iter  30 value 93.773542
iter  40 value 93.717271
iter  50 value 90.376174
iter  60 value 84.376727
iter  70 value 83.392906
iter  80 value 83.341402
iter  90 value 82.712719
iter 100 value 82.468506
final  value 82.468506 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.482589 
iter  10 value 95.498079
iter  20 value 93.892037
iter  30 value 88.081952
iter  40 value 84.772072
iter  50 value 82.948149
iter  60 value 82.678205
iter  70 value 82.542080
iter  80 value 82.320420
iter  90 value 81.797997
iter 100 value 80.955119
final  value 80.955119 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.114828 
iter  10 value 94.037238
iter  20 value 92.705393
iter  30 value 90.930314
iter  40 value 90.559234
iter  50 value 84.353816
iter  60 value 81.573782
iter  70 value 80.696204
iter  80 value 80.528747
iter  90 value 80.293600
iter 100 value 80.137125
final  value 80.137125 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.465496 
iter  10 value 94.774368
iter  20 value 94.473156
iter  30 value 92.849080
iter  40 value 87.925000
iter  50 value 83.385294
iter  60 value 82.840741
iter  70 value 82.395742
iter  80 value 81.487345
iter  90 value 80.963625
iter 100 value 80.544073
final  value 80.544073 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.622348 
iter  10 value 87.295643
iter  20 value 83.457112
iter  30 value 82.777697
iter  40 value 82.595869
iter  50 value 82.550883
iter  60 value 82.416041
iter  70 value 82.380243
iter  80 value 82.211817
iter  90 value 82.092298
iter 100 value 81.675029
final  value 81.675029 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.986605 
iter  10 value 94.926945
iter  20 value 93.115198
iter  30 value 88.765778
iter  40 value 86.851528
iter  50 value 85.774887
iter  60 value 85.119325
iter  70 value 82.977007
iter  80 value 80.595791
iter  90 value 80.357314
iter 100 value 80.113540
final  value 80.113540 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.536759 
iter  10 value 94.501501
iter  20 value 90.746887
iter  30 value 88.173269
iter  40 value 83.646591
iter  50 value 82.289128
iter  60 value 82.253059
iter  70 value 81.817299
iter  80 value 81.579501
iter  90 value 81.233045
iter 100 value 80.567434
final  value 80.567434 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.282513 
iter  10 value 94.931405
iter  20 value 86.360635
iter  30 value 84.262912
iter  40 value 83.156057
iter  50 value 81.454377
iter  60 value 80.784808
iter  70 value 80.146147
iter  80 value 79.983585
iter  90 value 79.913369
iter 100 value 79.822804
final  value 79.822804 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.879009 
iter  10 value 94.538498
iter  20 value 91.064922
iter  30 value 88.966301
iter  40 value 88.537998
iter  50 value 83.264599
iter  60 value 82.476228
iter  70 value 81.987156
iter  80 value 81.878202
iter  90 value 81.365302
iter 100 value 80.727984
final  value 80.727984 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.405245 
iter  10 value 93.506646
iter  20 value 89.978690
iter  30 value 85.136737
iter  40 value 83.527282
iter  50 value 82.288271
iter  60 value 80.950173
iter  70 value 80.397473
iter  80 value 80.271865
iter  90 value 80.129627
iter 100 value 80.012287
final  value 80.012287 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.782021 
iter  10 value 94.550349
iter  20 value 93.859255
iter  30 value 90.380748
iter  40 value 86.365111
iter  50 value 82.816114
iter  60 value 80.956186
iter  70 value 80.517108
iter  80 value 80.145555
iter  90 value 79.926051
iter 100 value 79.882371
final  value 79.882371 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.859502 
final  value 94.486079 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.205833 
iter  10 value 93.747920
iter  20 value 93.629375
final  value 93.629360 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.568704 
iter  10 value 94.485883
iter  20 value 92.689570
iter  30 value 85.648442
iter  40 value 82.653679
iter  50 value 82.451844
iter  60 value 82.445375
final  value 82.445101 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.024289 
iter  10 value 94.485795
iter  20 value 94.479867
iter  30 value 93.644968
iter  40 value 93.621765
final  value 93.615610 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.212090 
final  value 94.486054 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.311608 
iter  10 value 94.490544
iter  20 value 94.419985
final  value 94.027733 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.318577 
iter  10 value 94.465506
iter  20 value 94.441205
iter  30 value 94.438171
iter  40 value 93.697461
iter  50 value 93.681127
final  value 93.679986 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.278933 
iter  10 value 94.031298
iter  20 value 94.027141
final  value 94.026732 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.810238 
iter  10 value 94.489712
iter  20 value 92.360226
iter  30 value 83.943549
iter  40 value 83.465073
iter  50 value 82.396355
iter  60 value 81.393120
iter  70 value 80.280331
iter  80 value 78.824010
iter  90 value 78.614000
iter 100 value 78.444413
final  value 78.444413 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.983590 
iter  10 value 86.702628
iter  20 value 85.710492
iter  30 value 82.727256
iter  40 value 82.695081
iter  50 value 82.680755
iter  60 value 82.679875
final  value 82.679204 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.409216 
iter  10 value 94.035425
iter  20 value 94.029415
iter  30 value 92.251837
iter  40 value 91.855792
final  value 91.855714 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.498292 
iter  10 value 93.810268
iter  20 value 93.802820
final  value 93.802664 
converged
Fitting Repeat 3 

# weights:  507
initial  value 144.663972 
iter  10 value 93.875226
iter  20 value 93.871188
iter  30 value 93.554509
iter  40 value 90.546665
iter  50 value 82.306219
iter  60 value 82.193073
iter  70 value 81.874548
iter  80 value 81.607446
final  value 81.607432 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.355890 
iter  10 value 94.491441
iter  20 value 94.471497
final  value 94.026754 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.200502 
iter  10 value 94.492649
iter  20 value 94.418412
iter  30 value 84.876649
iter  40 value 83.557457
iter  50 value 82.527414
final  value 82.505945 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.563932 
iter  10 value 93.970585
iter  20 value 93.962021
final  value 93.962012 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.072307 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.301201 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.539640 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.951072 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.286774 
final  value 94.022599 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.102697 
iter  10 value 93.962019
final  value 93.962011 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.718285 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 117.160629 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.000985 
iter  10 value 92.211138
final  value 92.211111 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.361308 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.683152 
iter  10 value 94.008696
iter  10 value 94.008696
iter  10 value 94.008696
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.478627 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.114135 
iter  10 value 92.335042
iter  20 value 91.966849
iter  30 value 91.397287
iter  30 value 91.397287
iter  30 value 91.397287
final  value 91.397287 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.947248 
iter  10 value 93.379439
final  value 93.288889 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.186465 
iter  10 value 93.741708
iter  20 value 86.519456
iter  30 value 85.337421
iter  40 value 84.008811
iter  50 value 83.526723
iter  60 value 83.514172
iter  70 value 83.513963
iter  70 value 83.513963
iter  70 value 83.513963
final  value 83.513963 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.304689 
iter  10 value 94.059457
iter  20 value 93.447347
iter  30 value 87.606040
iter  40 value 85.968770
iter  50 value 85.678779
iter  60 value 84.149962
iter  70 value 83.703943
iter  80 value 83.532461
final  value 83.530343 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.909213 
iter  10 value 91.148057
iter  20 value 84.711936
iter  30 value 84.315539
iter  40 value 83.880091
iter  50 value 83.541109
final  value 83.530342 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.795081 
iter  10 value 94.040752
iter  20 value 92.996042
iter  30 value 92.862094
iter  40 value 92.601874
iter  50 value 92.381825
iter  60 value 92.122892
iter  70 value 85.887791
iter  80 value 85.191687
iter  90 value 85.075549
iter 100 value 84.888287
final  value 84.888287 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.906075 
iter  10 value 93.593080
iter  20 value 88.850652
iter  30 value 87.158357
iter  40 value 85.578913
iter  50 value 84.771840
iter  60 value 84.764015
iter  60 value 84.764015
final  value 84.764015 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.060694 
iter  10 value 94.054915
iter  20 value 88.289664
iter  30 value 84.799224
iter  40 value 84.541642
iter  50 value 84.509894
iter  60 value 84.397789
iter  70 value 83.795389
iter  80 value 83.303043
iter  90 value 82.251086
iter 100 value 82.052879
final  value 82.052879 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.485727 
iter  10 value 94.346595
iter  20 value 86.406001
iter  30 value 84.631126
iter  40 value 82.954041
iter  50 value 81.630485
iter  60 value 81.128342
iter  70 value 81.086486
iter  80 value 81.064471
iter  90 value 81.047022
iter 100 value 81.021824
final  value 81.021824 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.175229 
iter  10 value 94.111592
iter  20 value 90.211609
iter  30 value 87.261732
iter  40 value 85.742868
iter  50 value 84.674424
iter  60 value 82.201776
iter  70 value 81.869405
iter  80 value 81.737519
iter  90 value 81.518851
iter 100 value 81.174429
final  value 81.174429 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.982551 
iter  10 value 94.050637
iter  20 value 92.398726
iter  30 value 86.689365
iter  40 value 84.955739
iter  50 value 84.578898
iter  60 value 84.391499
iter  70 value 84.354003
iter  80 value 84.244800
iter  90 value 83.210238
iter 100 value 82.027759
final  value 82.027759 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.485680 
iter  10 value 94.531678
iter  20 value 92.518664
iter  30 value 85.495460
iter  40 value 84.079534
iter  50 value 83.581892
iter  60 value 82.431285
iter  70 value 82.100436
iter  80 value 81.528441
iter  90 value 81.340272
iter 100 value 81.295989
final  value 81.295989 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.228163 
iter  10 value 93.298299
iter  20 value 89.722676
iter  30 value 85.482517
iter  40 value 84.423927
iter  50 value 83.922404
iter  60 value 83.379930
iter  70 value 82.039963
iter  80 value 81.353707
iter  90 value 81.123289
iter 100 value 81.094394
final  value 81.094394 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.020532 
iter  10 value 93.227632
iter  20 value 88.836655
iter  30 value 87.179150
iter  40 value 83.753843
iter  50 value 82.646595
iter  60 value 81.502696
iter  70 value 81.301472
iter  80 value 81.102126
iter  90 value 80.828148
iter 100 value 80.605740
final  value 80.605740 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.321513 
iter  10 value 95.814940
iter  20 value 85.631701
iter  30 value 84.677509
iter  40 value 83.391365
iter  50 value 83.249806
iter  60 value 82.811211
iter  70 value 82.275302
iter  80 value 81.681576
iter  90 value 81.302242
iter 100 value 81.172867
final  value 81.172867 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.339542 
iter  10 value 94.007519
iter  20 value 88.322016
iter  30 value 85.074215
iter  40 value 84.619934
iter  50 value 84.380527
iter  60 value 83.634387
iter  70 value 82.675374
iter  80 value 82.034832
iter  90 value 81.643606
iter 100 value 81.514348
final  value 81.514348 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 132.396589 
iter  10 value 94.884588
iter  20 value 89.795716
iter  30 value 85.473847
iter  40 value 84.621906
iter  50 value 84.157665
iter  60 value 83.540025
iter  70 value 83.202133
iter  80 value 82.651117
iter  90 value 82.125655
iter 100 value 82.002750
final  value 82.002750 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.370347 
final  value 94.054432 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.631642 
final  value 94.054425 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.231001 
final  value 94.054636 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.092614 
final  value 94.054357 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.755414 
final  value 94.054619 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.683058 
iter  10 value 94.058036
iter  20 value 93.549877
iter  30 value 91.136639
iter  40 value 84.797957
iter  50 value 84.797430
iter  60 value 84.757378
iter  70 value 84.700451
iter  80 value 84.354194
iter  90 value 84.109941
iter 100 value 84.082449
final  value 84.082449 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.188791 
iter  10 value 94.057966
iter  20 value 94.052811
iter  30 value 92.445270
iter  40 value 91.949069
iter  50 value 86.934999
iter  60 value 83.762641
iter  70 value 81.938627
iter  80 value 81.838976
final  value 81.838935 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.194496 
iter  10 value 94.052723
iter  20 value 84.864549
iter  30 value 84.502827
iter  40 value 84.496551
iter  50 value 84.024944
iter  60 value 83.793896
iter  70 value 83.703957
final  value 83.703392 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.029444 
iter  10 value 94.057697
iter  20 value 93.982818
iter  30 value 88.695086
iter  40 value 87.380165
iter  50 value 87.327905
final  value 87.210315 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.289696 
iter  10 value 93.975794
iter  20 value 93.967027
iter  30 value 93.615991
iter  40 value 88.421802
iter  50 value 84.769301
iter  60 value 84.754609
iter  70 value 84.754371
iter  80 value 83.659059
iter  90 value 81.872106
iter 100 value 81.325228
final  value 81.325228 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.845542 
iter  10 value 91.788180
iter  20 value 91.765162
iter  30 value 91.762597
iter  40 value 90.971961
iter  50 value 83.184316
iter  60 value 83.176902
final  value 83.160801 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.711668 
iter  10 value 94.055512
iter  20 value 93.357047
iter  30 value 93.290069
iter  40 value 85.691875
iter  50 value 84.180306
iter  60 value 83.685451
iter  70 value 83.334248
iter  80 value 83.329976
iter  90 value 83.329699
iter 100 value 83.329294
final  value 83.329294 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.493261 
iter  10 value 94.026283
iter  20 value 94.016229
iter  30 value 94.008978
iter  40 value 92.565612
iter  50 value 85.222951
iter  60 value 84.474368
iter  70 value 83.766723
iter  80 value 83.590336
iter  90 value 83.429195
iter 100 value 83.426149
final  value 83.426149 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.057861 
iter  10 value 94.016803
iter  20 value 94.014213
iter  30 value 94.013080
iter  40 value 88.882521
iter  50 value 84.537904
iter  60 value 84.328991
iter  70 value 84.297776
iter  80 value 84.078054
iter  90 value 84.077691
iter 100 value 84.076365
final  value 84.076365 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.062712 
iter  10 value 94.059328
iter  20 value 93.833801
iter  30 value 89.825715
iter  40 value 89.676292
iter  50 value 89.475558
iter  60 value 89.311761
iter  70 value 87.696767
iter  80 value 84.040912
iter  90 value 82.963109
iter 100 value 82.620014
final  value 82.620014 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.204549 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.526362 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.555964 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.056939 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.233607 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.980058 
iter  10 value 94.011429
iter  10 value 94.011429
iter  10 value 94.011429
final  value 94.011429 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.428621 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.047185 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.404395 
iter  10 value 86.375017
iter  20 value 84.498660
final  value 84.498138 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.356991 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.324215 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.874409 
iter  10 value 94.116956
iter  20 value 93.795502
iter  30 value 93.793883
iter  40 value 92.888762
iter  50 value 91.531011
iter  60 value 91.412261
iter  70 value 88.061369
iter  80 value 86.097088
iter  90 value 86.096134
final  value 86.096130 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.831114 
final  value 94.452424 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.324438 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.438209 
iter  10 value 93.006836
final  value 92.906854 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.331792 
iter  10 value 94.487801
iter  20 value 93.695637
iter  30 value 87.935725
iter  40 value 83.172720
iter  50 value 82.648340
iter  60 value 81.426713
iter  70 value 81.179865
iter  80 value 81.154861
iter  90 value 81.091930
iter 100 value 81.040880
final  value 81.040880 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 111.596155 
iter  10 value 94.519932
iter  20 value 94.486721
iter  30 value 88.448274
iter  40 value 86.245022
iter  50 value 85.790263
iter  60 value 85.732968
iter  70 value 85.663024
iter  80 value 85.442022
final  value 85.434125 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.008085 
iter  10 value 94.353954
iter  20 value 88.804677
iter  30 value 86.267876
iter  40 value 85.829421
iter  50 value 85.703483
iter  60 value 85.500448
iter  70 value 85.434127
final  value 85.434125 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.606293 
iter  10 value 94.469082
iter  20 value 87.445323
iter  30 value 87.277997
iter  40 value 85.987288
iter  50 value 85.580041
iter  60 value 85.578794
iter  70 value 85.434186
final  value 85.434126 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.715987 
iter  10 value 94.486521
iter  20 value 94.254568
iter  30 value 93.900819
iter  40 value 93.893087
iter  50 value 93.892821
iter  60 value 93.892289
iter  70 value 87.845930
iter  80 value 84.632023
iter  90 value 84.301490
iter 100 value 83.809256
final  value 83.809256 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.786675 
iter  10 value 95.002287
iter  20 value 94.299459
iter  30 value 87.407073
iter  40 value 86.286463
iter  50 value 85.318420
iter  60 value 83.531270
iter  70 value 81.116103
iter  80 value 80.281518
iter  90 value 80.122944
iter 100 value 79.987659
final  value 79.987659 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.536882 
iter  10 value 94.383681
iter  20 value 94.066737
iter  30 value 85.215725
iter  40 value 84.931605
iter  50 value 83.099116
iter  60 value 82.391692
iter  70 value 82.141333
iter  80 value 81.960798
iter  90 value 81.901333
iter 100 value 81.758086
final  value 81.758086 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 122.062029 
iter  10 value 94.789456
iter  20 value 93.271436
iter  30 value 91.622794
iter  40 value 91.354770
iter  50 value 91.292133
iter  60 value 88.661315
iter  70 value 86.333455
iter  80 value 85.770068
iter  90 value 85.667077
iter 100 value 83.000088
final  value 83.000088 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.950838 
iter  10 value 94.472194
iter  20 value 88.519368
iter  30 value 85.009149
iter  40 value 82.221246
iter  50 value 80.869528
iter  60 value 80.619075
iter  70 value 80.066110
iter  80 value 79.795420
iter  90 value 79.618892
iter 100 value 79.473830
final  value 79.473830 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.791249 
iter  10 value 94.379676
iter  20 value 88.517310
iter  30 value 87.474861
iter  40 value 87.152051
iter  50 value 85.436186
iter  60 value 83.604691
iter  70 value 80.893661
iter  80 value 80.526744
iter  90 value 80.503001
iter 100 value 80.358948
final  value 80.358948 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 137.617076 
iter  10 value 97.165018
iter  20 value 91.661791
iter  30 value 85.494983
iter  40 value 82.757188
iter  50 value 81.868726
iter  60 value 81.064727
iter  70 value 80.536178
iter  80 value 80.349075
iter  90 value 80.337739
iter 100 value 80.251824
final  value 80.251824 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.323135 
iter  10 value 93.926588
iter  20 value 86.246139
iter  30 value 84.559313
iter  40 value 82.952968
iter  50 value 81.072275
iter  60 value 79.864913
iter  70 value 79.659810
iter  80 value 79.616704
iter  90 value 79.538471
iter 100 value 79.460715
final  value 79.460715 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.636573 
iter  10 value 94.425708
iter  20 value 89.680031
iter  30 value 85.151150
iter  40 value 84.490675
iter  50 value 83.247795
iter  60 value 82.508752
iter  70 value 82.080739
iter  80 value 81.498242
iter  90 value 80.756625
iter 100 value 80.394111
final  value 80.394111 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.550342 
iter  10 value 94.421211
iter  20 value 87.305438
iter  30 value 86.977118
iter  40 value 84.173873
iter  50 value 82.025628
iter  60 value 80.933548
iter  70 value 79.668907
iter  80 value 79.474762
iter  90 value 79.416225
iter 100 value 79.383044
final  value 79.383044 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.407084 
iter  10 value 94.538764
iter  20 value 87.802779
iter  30 value 84.965909
iter  40 value 84.342756
iter  50 value 82.401210
iter  60 value 80.747650
iter  70 value 80.525465
iter  80 value 80.097094
iter  90 value 79.793046
iter 100 value 79.529175
final  value 79.529175 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.199970 
iter  10 value 94.463027
iter  20 value 94.140799
iter  30 value 88.485726
iter  40 value 88.422398
iter  50 value 88.420538
iter  60 value 88.420459
iter  60 value 88.420458
iter  60 value 88.420457
final  value 88.420457 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.355900 
final  value 94.486064 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.074850 
final  value 94.485657 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.895672 
final  value 94.485791 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.043291 
final  value 94.485788 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.810912 
iter  10 value 94.466455
iter  20 value 94.464688
iter  30 value 94.462680
iter  40 value 94.018148
iter  50 value 92.637204
iter  60 value 92.615208
final  value 92.615188 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.236890 
iter  10 value 93.815082
iter  20 value 93.797862
final  value 93.796071 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.733216 
iter  10 value 93.187591
iter  20 value 93.166143
final  value 93.165904 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.658213 
iter  10 value 93.305279
iter  20 value 93.300480
iter  30 value 93.293713
iter  40 value 92.883916
iter  50 value 83.402817
iter  60 value 81.146572
iter  70 value 80.450653
iter  80 value 80.447680
final  value 80.447668 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.472763 
iter  10 value 93.604275
iter  20 value 87.339822
iter  30 value 87.217190
iter  40 value 87.216760
iter  50 value 85.713931
iter  60 value 84.298342
iter  70 value 84.020106
final  value 84.019595 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.386597 
iter  10 value 90.603692
iter  20 value 83.341347
iter  30 value 83.292744
final  value 83.290307 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.888688 
iter  10 value 93.818028
iter  20 value 93.796254
final  value 93.795607 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.179937 
iter  10 value 94.035373
iter  20 value 94.031004
iter  30 value 94.029623
iter  40 value 94.013108
iter  50 value 93.809636
iter  60 value 93.795543
final  value 93.795539 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.053635 
iter  10 value 93.844739
iter  20 value 93.708441
iter  30 value 92.407677
iter  40 value 91.961963
iter  50 value 91.952612
iter  60 value 91.872702
iter  70 value 91.856082
iter  80 value 91.855666
final  value 91.855182 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.861019 
iter  10 value 94.035410
iter  20 value 88.975385
iter  30 value 86.757849
iter  40 value 85.593828
iter  50 value 85.561641
iter  50 value 85.561641
iter  50 value 85.561641
final  value 85.561641 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.727441 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.950482 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.309288 
iter  10 value 93.213448
final  value 93.210526 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.560987 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.049807 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.671924 
final  value 93.867392 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.714492 
iter  10 value 87.753168
iter  20 value 87.745155
final  value 87.745010 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.808309 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.414224 
iter  10 value 93.425221
iter  20 value 93.304365
iter  30 value 93.304243
iter  30 value 93.304243
iter  30 value 93.304243
final  value 93.304243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.018397 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.310548 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.441949 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.147812 
iter  10 value 88.319890
final  value 88.139994 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.753190 
iter  10 value 93.856673
final  value 93.855556 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.919430 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.425560 
iter  10 value 94.070126
iter  20 value 93.887082
iter  30 value 91.368443
iter  40 value 86.588112
iter  50 value 86.354117
iter  60 value 86.108772
iter  70 value 85.593574
iter  80 value 84.656293
iter  90 value 83.852242
iter 100 value 83.456704
final  value 83.456704 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.732637 
iter  10 value 92.857092
iter  20 value 89.747866
iter  30 value 88.384674
iter  40 value 86.608888
iter  50 value 86.386188
iter  60 value 85.689852
iter  70 value 85.480683
final  value 85.480171 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.761017 
iter  10 value 93.828262
iter  20 value 90.984601
iter  30 value 88.373583
iter  40 value 86.706808
iter  50 value 86.579525
iter  60 value 86.510486
iter  70 value 86.462153
iter  80 value 86.401490
iter  90 value 85.900288
iter 100 value 85.875335
final  value 85.875335 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.837642 
iter  10 value 94.056746
iter  20 value 93.955747
iter  30 value 92.396596
iter  40 value 91.061370
iter  50 value 89.023830
iter  60 value 88.684636
iter  70 value 88.111726
iter  80 value 86.393504
iter  90 value 86.319547
iter 100 value 86.151163
final  value 86.151163 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.364140 
iter  10 value 93.982177
iter  20 value 89.720589
iter  30 value 87.180298
iter  40 value 86.772687
iter  50 value 86.623772
iter  60 value 86.137688
iter  70 value 85.772830
iter  80 value 85.517871
iter  90 value 84.793712
iter 100 value 83.879881
final  value 83.879881 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 115.006432 
iter  10 value 94.064946
iter  20 value 91.928349
iter  30 value 87.182708
iter  40 value 86.651706
iter  50 value 84.225634
iter  60 value 83.547264
iter  70 value 82.719494
iter  80 value 82.480107
iter  90 value 82.423408
iter 100 value 82.278204
final  value 82.278204 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.239843 
iter  10 value 94.050834
iter  20 value 91.155572
iter  30 value 88.509944
iter  40 value 87.024894
iter  50 value 85.921983
iter  60 value 84.302204
iter  70 value 83.700451
iter  80 value 83.659444
iter  90 value 83.485981
iter 100 value 83.420648
final  value 83.420648 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.697269 
iter  10 value 94.041898
iter  20 value 88.606126
iter  30 value 87.200377
iter  40 value 83.855020
iter  50 value 82.893830
iter  60 value 82.569330
iter  70 value 82.381481
iter  80 value 82.278968
iter  90 value 82.114565
iter 100 value 82.068497
final  value 82.068497 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.620233 
iter  10 value 94.196902
iter  20 value 94.147767
iter  30 value 93.963724
iter  40 value 89.167599
iter  50 value 88.459863
iter  60 value 86.643908
iter  70 value 83.428855
iter  80 value 82.850381
iter  90 value 82.253364
iter 100 value 82.155870
final  value 82.155870 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 123.392720 
iter  10 value 94.191070
iter  20 value 91.104909
iter  30 value 88.940028
iter  40 value 86.412815
iter  50 value 84.434300
iter  60 value 83.574237
iter  70 value 83.068859
iter  80 value 82.664625
iter  90 value 82.517443
iter 100 value 82.237944
final  value 82.237944 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.266741 
iter  10 value 94.019201
iter  20 value 93.919512
iter  30 value 90.268120
iter  40 value 87.576572
iter  50 value 86.634214
iter  60 value 84.771920
iter  70 value 83.771462
iter  80 value 83.454528
iter  90 value 83.336592
iter 100 value 83.175464
final  value 83.175464 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.249255 
iter  10 value 94.408320
iter  20 value 87.778861
iter  30 value 85.835330
iter  40 value 85.685183
iter  50 value 85.380317
iter  60 value 84.850497
iter  70 value 84.300171
iter  80 value 82.902028
iter  90 value 82.557248
iter 100 value 82.440410
final  value 82.440410 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.624661 
iter  10 value 93.940339
iter  20 value 89.155727
iter  30 value 87.233316
iter  40 value 86.598049
iter  50 value 86.304427
iter  60 value 84.791475
iter  70 value 83.701162
iter  80 value 82.377042
iter  90 value 82.109065
iter 100 value 82.026195
final  value 82.026195 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.457801 
iter  10 value 94.714897
iter  20 value 89.233661
iter  30 value 88.108904
iter  40 value 87.522319
iter  50 value 83.988768
iter  60 value 82.666208
iter  70 value 82.301242
iter  80 value 82.263196
iter  90 value 82.147660
iter 100 value 82.122281
final  value 82.122281 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.236357 
iter  10 value 93.963465
iter  20 value 88.721941
iter  30 value 87.290678
iter  40 value 85.512397
iter  50 value 83.323542
iter  60 value 82.715105
iter  70 value 82.550445
iter  80 value 82.487065
iter  90 value 82.377697
iter 100 value 82.222875
final  value 82.222875 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.305732 
final  value 94.054539 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.650676 
final  value 94.054496 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.766450 
final  value 94.054567 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.596294 
final  value 94.054288 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.518314 
final  value 94.054486 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.672540 
iter  10 value 94.057427
iter  20 value 94.053079
iter  30 value 93.957463
iter  40 value 93.004807
iter  50 value 88.512426
iter  60 value 87.460721
iter  70 value 86.950776
iter  80 value 86.946717
final  value 86.946639 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.093383 
iter  10 value 93.252623
iter  20 value 93.188242
iter  30 value 93.186471
iter  40 value 93.185856
iter  50 value 91.951234
iter  60 value 89.701036
iter  70 value 86.492100
iter  80 value 83.961897
iter  90 value 83.929356
iter 100 value 83.928080
final  value 83.928080 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.577228 
iter  10 value 93.702474
iter  20 value 93.697176
iter  30 value 93.694014
final  value 93.693228 
converged
Fitting Repeat 4 

# weights:  305
initial  value 93.913588 
iter  10 value 86.011558
iter  20 value 85.786751
iter  30 value 85.564748
iter  40 value 84.805352
final  value 84.663471 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.138971 
iter  10 value 94.058083
iter  20 value 93.942281
iter  30 value 86.383444
iter  40 value 86.381680
iter  50 value 86.380147
iter  60 value 85.883646
iter  70 value 85.854669
iter  80 value 85.849801
iter  90 value 85.785867
iter 100 value 85.610371
final  value 85.610371 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.182232 
iter  10 value 93.877019
iter  20 value 93.870414
iter  30 value 93.863376
iter  40 value 93.126004
iter  50 value 92.995247
iter  60 value 92.578746
iter  70 value 86.632393
iter  80 value 85.292326
iter  90 value 84.932533
iter 100 value 84.926638
final  value 84.926638 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.723490 
iter  10 value 91.965490
iter  20 value 85.900947
iter  30 value 85.855040
iter  40 value 84.607123
iter  50 value 82.997695
iter  60 value 82.301706
iter  70 value 80.908499
iter  80 value 80.614057
iter  90 value 80.414347
iter 100 value 80.326938
final  value 80.326938 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.074547 
iter  10 value 94.060117
iter  20 value 94.033545
iter  30 value 89.659972
iter  40 value 87.052580
iter  50 value 87.048589
final  value 87.048401 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.359585 
iter  10 value 93.781175
iter  20 value 93.779235
iter  30 value 90.911040
iter  40 value 87.225403
iter  50 value 86.785437
iter  60 value 85.382862
iter  70 value 85.239471
iter  80 value 84.710576
iter  90 value 83.856990
iter 100 value 83.835084
final  value 83.835084 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.214152 
iter  10 value 93.383710
iter  20 value 88.487488
iter  30 value 85.171690
iter  40 value 85.169279
iter  40 value 85.169279
final  value 85.169274 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.540789 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.039149 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.813831 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.732382 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.793938 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.326153 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.053539 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.027670 
final  value 94.461538 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.888635 
iter  10 value 94.352663
iter  20 value 94.336267
final  value 94.336207 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.100317 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.641536 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.516943 
iter  10 value 89.054485
iter  20 value 83.294848
final  value 83.288839 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.190652 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 123.136965 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.058690 
iter  10 value 85.833103
iter  20 value 80.695963
iter  30 value 80.274678
iter  40 value 80.271812
final  value 80.271515 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.889356 
iter  10 value 94.386408
iter  20 value 87.648220
iter  30 value 86.929376
iter  40 value 85.655140
iter  50 value 80.145588
iter  60 value 79.911467
iter  70 value 79.902478
iter  80 value 79.894518
final  value 79.893266 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.477603 
iter  10 value 94.397791
iter  20 value 94.381270
iter  30 value 83.272924
iter  40 value 81.389040
iter  50 value 81.179577
iter  60 value 81.150646
iter  70 value 81.051342
iter  80 value 80.565268
iter  90 value 80.526416
iter 100 value 80.507994
final  value 80.507994 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.620091 
iter  10 value 94.494177
iter  20 value 92.370196
iter  30 value 83.639907
iter  40 value 82.287531
iter  50 value 80.947232
iter  60 value 80.744250
iter  70 value 80.521919
iter  80 value 80.518471
iter  90 value 80.511228
iter 100 value 80.507993
final  value 80.507993 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.113440 
iter  10 value 94.511941
iter  20 value 94.466813
iter  30 value 86.069314
iter  40 value 84.935149
iter  50 value 84.787776
iter  60 value 81.181701
iter  70 value 80.495939
iter  80 value 79.658215
iter  90 value 79.090758
iter 100 value 78.344974
final  value 78.344974 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.298072 
iter  10 value 94.486752
iter  20 value 94.409554
iter  30 value 94.394758
iter  40 value 94.383046
iter  50 value 91.626984
iter  60 value 82.716650
iter  70 value 82.619032
iter  80 value 82.599769
iter  90 value 82.511176
iter 100 value 81.369363
final  value 81.369363 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.332844 
iter  10 value 87.323473
iter  20 value 82.006268
iter  30 value 81.583301
iter  40 value 81.137645
iter  50 value 79.827250
iter  60 value 79.635632
iter  70 value 79.583770
iter  80 value 79.578248
iter  90 value 79.372049
iter 100 value 78.351623
final  value 78.351623 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 128.461209 
iter  10 value 94.933981
iter  20 value 86.058031
iter  30 value 84.518869
iter  40 value 81.482991
iter  50 value 80.228828
iter  60 value 79.027903
iter  70 value 77.904304
iter  80 value 77.443995
iter  90 value 77.318773
iter 100 value 76.774007
final  value 76.774007 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.205118 
iter  10 value 96.423026
iter  20 value 88.348215
iter  30 value 85.976420
iter  40 value 83.290281
iter  50 value 82.323390
iter  60 value 82.187305
iter  70 value 82.059532
iter  80 value 81.995980
iter  90 value 81.042677
iter 100 value 78.337441
final  value 78.337441 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.620343 
iter  10 value 94.872114
iter  20 value 94.380303
iter  30 value 82.467853
iter  40 value 81.772240
iter  50 value 80.124589
iter  60 value 78.959687
iter  70 value 78.672468
iter  80 value 77.758278
iter  90 value 77.324788
iter 100 value 77.062716
final  value 77.062716 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.345888 
iter  10 value 91.881571
iter  20 value 83.427166
iter  30 value 80.383877
iter  40 value 80.279079
iter  50 value 80.154545
iter  60 value 79.628023
iter  70 value 78.412771
iter  80 value 78.040940
iter  90 value 77.682287
iter 100 value 77.494378
final  value 77.494378 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.054362 
iter  10 value 94.548063
iter  20 value 90.767671
iter  30 value 86.057114
iter  40 value 84.028582
iter  50 value 83.172620
iter  60 value 81.412694
iter  70 value 79.929897
iter  80 value 79.096108
iter  90 value 78.793369
iter 100 value 78.550578
final  value 78.550578 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.035679 
iter  10 value 94.446050
iter  20 value 87.269684
iter  30 value 82.586201
iter  40 value 80.842128
iter  50 value 80.588946
iter  60 value 79.375435
iter  70 value 78.405280
iter  80 value 77.680198
iter  90 value 77.119841
iter 100 value 76.509683
final  value 76.509683 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.632190 
iter  10 value 94.485945
iter  20 value 89.553381
iter  30 value 84.850357
iter  40 value 81.554255
iter  50 value 79.122475
iter  60 value 77.952101
iter  70 value 77.845578
iter  80 value 77.792191
iter  90 value 77.634220
iter 100 value 77.082147
final  value 77.082147 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.595553 
iter  10 value 94.610374
iter  20 value 87.321353
iter  30 value 84.267002
iter  40 value 79.196391
iter  50 value 78.633576
iter  60 value 76.722455
iter  70 value 76.502353
iter  80 value 76.292191
iter  90 value 75.982079
iter 100 value 75.884413
final  value 75.884413 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.168409 
iter  10 value 94.365336
iter  20 value 83.729015
iter  30 value 80.582748
iter  40 value 80.245805
iter  50 value 78.871330
iter  60 value 77.223092
iter  70 value 76.830002
iter  80 value 76.483363
iter  90 value 76.429665
iter 100 value 76.367732
final  value 76.367732 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.696400 
final  value 94.485731 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.558620 
iter  10 value 94.313416
final  value 94.309810 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.541297 
final  value 94.485909 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.326799 
iter  10 value 94.486007
iter  20 value 94.484224
final  value 94.484222 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.688034 
final  value 94.485779 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.337577 
iter  10 value 94.489000
iter  20 value 94.484237
final  value 94.484216 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.525426 
iter  10 value 94.488845
iter  20 value 94.311560
iter  30 value 85.625827
iter  40 value 81.942218
iter  50 value 81.823469
iter  60 value 81.822436
iter  70 value 81.821195
iter  80 value 81.820816
iter  90 value 81.820550
iter 100 value 81.809811
final  value 81.809811 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.321620 
iter  10 value 94.149456
iter  20 value 93.825561
iter  30 value 87.830817
iter  40 value 86.899335
iter  50 value 86.425370
iter  60 value 86.424462
final  value 86.424458 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.421791 
iter  10 value 89.837873
iter  20 value 89.774594
iter  30 value 87.585755
iter  40 value 87.330726
iter  50 value 87.328459
iter  60 value 87.327487
iter  70 value 87.326545
iter  80 value 86.642901
iter  90 value 82.983630
iter 100 value 81.465857
final  value 81.465857 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.091485 
iter  10 value 94.360708
iter  20 value 93.824899
iter  30 value 86.157044
iter  40 value 86.064357
iter  50 value 84.880351
final  value 84.483146 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.817537 
iter  10 value 94.489702
iter  20 value 91.402979
iter  30 value 86.793004
iter  40 value 84.594115
iter  50 value 84.069410
iter  60 value 79.905459
iter  70 value 79.587641
final  value 79.586370 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.177362 
iter  10 value 94.362453
iter  20 value 94.335978
iter  30 value 93.943927
final  value 93.931846 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.032269 
iter  10 value 94.492265
iter  20 value 94.409310
iter  30 value 94.291667
iter  40 value 91.210270
iter  50 value 81.960691
iter  60 value 81.723972
iter  70 value 81.381197
iter  80 value 81.195942
iter  90 value 81.192878
iter 100 value 81.189756
final  value 81.189756 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.926975 
iter  10 value 94.304054
iter  20 value 92.307216
iter  30 value 84.870135
iter  40 value 82.629090
iter  50 value 82.611570
iter  60 value 82.609852
iter  70 value 82.606198
iter  80 value 82.122211
iter  90 value 80.268070
iter 100 value 78.126753
final  value 78.126753 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.229021 
iter  10 value 88.790383
iter  20 value 85.760009
iter  30 value 85.642391
iter  40 value 85.641094
iter  50 value 85.639839
iter  60 value 85.639561
iter  70 value 85.638228
iter  80 value 85.634144
iter  90 value 84.001606
iter 100 value 79.037391
final  value 79.037391 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 124.115429 
iter  10 value 117.896087
iter  20 value 117.861380
iter  30 value 115.941971
iter  40 value 110.963160
iter  50 value 108.183442
iter  60 value 104.713745
iter  70 value 103.396966
iter  80 value 103.338226
iter  90 value 103.319358
iter 100 value 103.159420
final  value 103.159420 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 120.982930 
iter  10 value 117.754728
iter  20 value 108.533879
iter  30 value 107.368240
iter  40 value 106.932249
iter  50 value 106.189242
iter  60 value 105.579472
iter  70 value 105.566339
iter  70 value 105.566339
iter  70 value 105.566339
final  value 105.566339 
converged
Fitting Repeat 3 

# weights:  103
initial  value 125.796221 
iter  10 value 117.989958
iter  20 value 117.894404
iter  30 value 117.617013
iter  40 value 108.031533
iter  50 value 107.281187
iter  60 value 105.254669
iter  70 value 103.114094
iter  80 value 102.607022
iter  90 value 102.565246
iter 100 value 102.559318
final  value 102.559318 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 139.225353 
iter  10 value 117.897974
iter  20 value 113.582420
iter  30 value 109.853091
iter  40 value 105.469287
iter  50 value 105.309376
iter  60 value 105.264411
iter  70 value 105.260185
iter  80 value 105.258334
iter  80 value 105.258333
iter  80 value 105.258333
final  value 105.258333 
converged
Fitting Repeat 5 

# weights:  103
initial  value 120.806277 
iter  10 value 117.894415
iter  20 value 117.713086
iter  30 value 117.558091
iter  40 value 108.694833
iter  50 value 107.705924
iter  60 value 107.464386
iter  70 value 106.236026
iter  80 value 103.219935
iter  90 value 102.912577
iter 100 value 102.614117
final  value 102.614117 
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 -- Thu Sep 12 06:03:21 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 53.398   1.337  71.066