##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-4.3.1/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R-4.3.1/site-library --timings HPiP_1.8.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
    gcc (GCC) 10.3.1
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.8.0’
* 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 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 ... 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       39.021  0.794  39.900
FSmethod      38.488  0.794  39.358
corr_plot     38.452  0.551  39.080
pred_ensembel 18.403  0.716  16.769
enrichfindP    0.530  0.071  32.462
getFASTA       0.096  0.032  16.044
* 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-3.18-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-4.3.1/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.3.1/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 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (64-bit)

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

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

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

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

# weights:  103
initial  value 97.716191 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.424071 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.387350 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.439783 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.203871 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.501206 
final  value 94.043243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.245925 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.767966 
iter  10 value 91.739769
iter  20 value 91.608244
final  value 91.607805 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.571068 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.087968 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.548916 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.378526 
iter  10 value 93.838019
iter  20 value 91.018650
iter  30 value 83.917498
iter  40 value 83.424378
iter  50 value 83.416938
iter  60 value 83.415581
final  value 83.415553 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.169150 
iter  10 value 91.656570
iter  20 value 91.595054
iter  30 value 91.165708
iter  40 value 91.094417
iter  50 value 91.078470
iter  60 value 91.048279
iter  60 value 91.048279
iter  60 value 91.048279
final  value 91.048279 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.698575 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.024975 
final  value 93.882439 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.483517 
iter  10 value 94.054096
iter  20 value 93.418550
iter  30 value 87.999440
iter  40 value 83.723295
iter  50 value 83.561840
iter  60 value 83.441341
iter  70 value 83.433773
final  value 83.432890 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.684901 
iter  10 value 92.308887
iter  20 value 83.554975
iter  30 value 83.449213
iter  40 value 83.409920
iter  50 value 83.292556
iter  60 value 83.285982
iter  60 value 83.285982
iter  60 value 83.285982
final  value 83.285982 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.385523 
iter  10 value 94.058392
iter  20 value 94.054583
iter  30 value 85.962339
iter  40 value 83.228092
iter  50 value 83.040773
iter  60 value 83.013348
iter  70 value 82.901602
iter  80 value 82.894250
final  value 82.894249 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.945054 
iter  10 value 94.135669
iter  20 value 91.960021
iter  30 value 86.047001
iter  40 value 84.716154
iter  50 value 83.438934
iter  60 value 83.324670
iter  70 value 83.286077
final  value 83.285982 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.605243 
iter  10 value 94.030060
iter  20 value 86.833886
iter  30 value 83.541825
iter  40 value 83.340642
iter  50 value 83.288239
iter  60 value 83.285986
final  value 83.285982 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.849175 
iter  10 value 94.068291
iter  20 value 88.718043
iter  30 value 84.760002
iter  40 value 83.611960
iter  50 value 81.239123
iter  60 value 80.312717
iter  70 value 80.141650
iter  80 value 79.905343
iter  90 value 79.580521
iter 100 value 79.538771
final  value 79.538771 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.726417 
iter  10 value 94.064561
iter  20 value 91.763113
iter  30 value 85.861591
iter  40 value 83.304670
iter  50 value 83.139669
iter  60 value 83.117065
iter  70 value 83.069165
iter  80 value 83.031617
iter  90 value 83.010761
iter 100 value 82.754376
final  value 82.754376 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.889639 
iter  10 value 94.359907
iter  20 value 90.338680
iter  30 value 83.514446
iter  40 value 83.326657
iter  50 value 82.788257
iter  60 value 81.785808
iter  70 value 80.717997
iter  80 value 80.480680
iter  90 value 80.381714
iter 100 value 80.337962
final  value 80.337962 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.357057 
iter  10 value 93.722692
iter  20 value 87.736023
iter  30 value 87.220857
iter  40 value 86.006535
iter  50 value 85.627688
iter  60 value 83.754956
iter  70 value 83.433111
iter  80 value 83.203850
iter  90 value 83.107497
iter 100 value 82.022012
final  value 82.022012 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.358545 
iter  10 value 93.919030
iter  20 value 85.908048
iter  30 value 85.401379
iter  40 value 85.070354
iter  50 value 83.862137
iter  60 value 83.306316
iter  70 value 80.655047
iter  80 value 80.069649
iter  90 value 79.973918
iter 100 value 79.890159
final  value 79.890159 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.514584 
iter  10 value 93.871005
iter  20 value 85.652119
iter  30 value 83.423737
iter  40 value 83.131418
iter  50 value 82.855007
iter  60 value 82.659501
iter  70 value 82.586107
iter  80 value 82.565337
iter  90 value 82.172232
iter 100 value 81.516214
final  value 81.516214 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.098147 
iter  10 value 94.848746
iter  20 value 86.204361
iter  30 value 84.664892
iter  40 value 84.557296
iter  50 value 84.164725
iter  60 value 83.902291
iter  70 value 83.674666
iter  80 value 83.263470
iter  90 value 81.288413
iter 100 value 80.799302
final  value 80.799302 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.612871 
iter  10 value 94.072097
iter  20 value 91.350629
iter  30 value 86.186307
iter  40 value 83.482355
iter  50 value 83.020432
iter  60 value 81.951084
iter  70 value 81.487827
iter  80 value 81.011872
iter  90 value 79.967126
iter 100 value 79.731696
final  value 79.731696 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.060986 
iter  10 value 93.759522
iter  20 value 88.076779
iter  30 value 86.336735
iter  40 value 83.682617
iter  50 value 83.139946
iter  60 value 82.304403
iter  70 value 81.927718
iter  80 value 81.393065
iter  90 value 80.914169
iter 100 value 80.539665
final  value 80.539665 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.133443 
iter  10 value 94.333289
iter  20 value 93.451727
iter  30 value 93.081698
iter  40 value 89.371271
iter  50 value 83.706972
iter  60 value 82.726278
iter  70 value 82.109313
iter  80 value 81.805162
iter  90 value 81.602101
iter 100 value 81.284256
final  value 81.284256 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.315159 
final  value 94.054441 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.708604 
final  value 94.054473 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.126993 
iter  10 value 94.054548
final  value 94.052931 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.378737 
final  value 94.054750 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.376075 
final  value 94.054397 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.500490 
iter  10 value 94.057785
final  value 94.054880 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.422706 
iter  10 value 94.057860
iter  20 value 93.041891
iter  30 value 85.254079
iter  40 value 85.218304
final  value 85.218085 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.681283 
iter  10 value 94.048070
iter  20 value 94.035413
iter  30 value 93.774645
iter  40 value 91.272943
iter  50 value 82.844175
iter  60 value 81.601472
iter  70 value 80.598743
iter  80 value 79.949833
iter  90 value 79.791881
final  value 79.791721 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.387633 
iter  10 value 94.047963
iter  20 value 93.060489
iter  30 value 85.231158
iter  40 value 84.094924
iter  50 value 84.084133
iter  60 value 83.967533
iter  70 value 83.963669
iter  80 value 82.374437
iter  90 value 82.178185
iter 100 value 82.175400
final  value 82.175400 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.271661 
iter  10 value 94.030194
iter  20 value 94.025936
iter  30 value 93.938915
iter  40 value 91.189245
iter  50 value 83.270013
iter  60 value 83.244634
iter  70 value 83.244410
iter  80 value 82.497290
iter  90 value 79.775421
iter 100 value 79.119841
final  value 79.119841 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.065193 
iter  10 value 94.051965
iter  20 value 94.051558
iter  30 value 94.019428
iter  40 value 90.615016
iter  50 value 85.462038
iter  60 value 85.461233
iter  70 value 85.461181
iter  80 value 84.790244
iter  90 value 82.179623
iter 100 value 82.148232
final  value 82.148232 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.690019 
iter  10 value 94.060056
iter  20 value 93.824402
iter  30 value 88.032494
iter  40 value 85.551582
iter  50 value 85.510534
iter  60 value 85.508604
iter  70 value 85.507922
iter  80 value 85.460582
final  value 85.460544 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.050468 
iter  10 value 86.718173
iter  20 value 84.684163
iter  30 value 84.664307
iter  40 value 82.107974
iter  50 value 82.102918
iter  60 value 82.080723
iter  70 value 82.026304
final  value 82.023387 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.448307 
iter  10 value 94.063228
iter  20 value 94.060495
iter  30 value 94.051155
iter  40 value 94.050531
iter  50 value 94.043584
iter  60 value 83.239077
iter  70 value 82.266871
iter  80 value 82.266163
iter  90 value 82.100202
iter 100 value 81.010287
final  value 81.010287 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.183609 
iter  10 value 94.060693
iter  20 value 94.046463
iter  30 value 84.812337
iter  40 value 82.970361
iter  50 value 80.214183
iter  60 value 80.113783
final  value 80.113771 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.209417 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.277791 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.548834 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.637710 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.941350 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.030664 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.112277 
iter  10 value 91.728958
iter  20 value 91.577732
final  value 91.576614 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.731091 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.598589 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.029917 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.259696 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.229082 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.278792 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.320885 
iter  10 value 94.427726
iter  10 value 94.427726
iter  10 value 94.427726
final  value 94.427726 
converged
Fitting Repeat 5 

# weights:  507
initial  value 128.642663 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.089684 
iter  10 value 94.259227
iter  20 value 92.087778
iter  30 value 87.481189
iter  40 value 86.677490
iter  50 value 85.788402
iter  60 value 85.328264
iter  70 value 83.387481
iter  80 value 82.002930
final  value 82.002364 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.690193 
iter  10 value 94.403195
iter  20 value 94.067997
iter  30 value 93.902519
iter  40 value 93.409940
iter  50 value 86.731243
iter  60 value 86.302985
iter  70 value 84.497928
iter  80 value 83.316199
iter  90 value 82.896843
iter 100 value 82.357692
final  value 82.357692 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.440270 
iter  10 value 94.519729
iter  20 value 94.441060
iter  30 value 91.046597
iter  40 value 86.567286
iter  50 value 86.225057
iter  60 value 85.922285
iter  70 value 85.331100
iter  80 value 84.484482
iter  90 value 82.734089
iter 100 value 82.007796
final  value 82.007796 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.559144 
iter  10 value 94.443209
iter  20 value 86.954657
iter  30 value 86.263703
iter  40 value 84.737393
iter  50 value 83.369941
iter  60 value 82.578267
iter  70 value 82.151721
iter  80 value 82.004337
final  value 82.002364 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.531046 
iter  10 value 94.476622
iter  20 value 87.537593
iter  30 value 86.846743
iter  40 value 86.214557
iter  50 value 85.536629
iter  60 value 84.011120
iter  70 value 83.328159
iter  80 value 83.316230
iter  80 value 83.316229
final  value 83.316229 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.266312 
iter  10 value 93.719719
iter  20 value 89.985365
iter  30 value 87.627390
iter  40 value 84.995946
iter  50 value 83.555624
iter  60 value 82.606498
iter  70 value 81.289486
iter  80 value 80.799751
iter  90 value 80.729465
iter 100 value 80.675998
final  value 80.675998 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.209872 
iter  10 value 94.346843
iter  20 value 93.232564
iter  30 value 89.936243
iter  40 value 89.375612
iter  50 value 85.165343
iter  60 value 82.979166
iter  70 value 82.038336
iter  80 value 81.938671
iter  90 value 81.370407
iter 100 value 81.227663
final  value 81.227663 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.906092 
iter  10 value 94.499883
iter  20 value 87.923012
iter  30 value 85.955167
iter  40 value 83.378440
iter  50 value 83.260617
iter  60 value 83.229612
iter  70 value 82.733778
iter  80 value 81.369831
iter  90 value 80.778965
iter 100 value 80.655748
final  value 80.655748 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.690522 
iter  10 value 94.435340
iter  20 value 94.008690
iter  30 value 93.888067
iter  40 value 92.514903
iter  50 value 86.271741
iter  60 value 85.746401
iter  70 value 85.187020
iter  80 value 84.073925
iter  90 value 83.308711
iter 100 value 81.712105
final  value 81.712105 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.616393 
iter  10 value 94.499189
iter  20 value 93.701278
iter  30 value 86.424650
iter  40 value 84.641570
iter  50 value 83.302937
iter  60 value 82.617560
iter  70 value 81.478337
iter  80 value 80.844475
iter  90 value 80.648514
iter 100 value 80.521565
final  value 80.521565 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.851049 
iter  10 value 94.536978
iter  20 value 91.107365
iter  30 value 90.655690
iter  40 value 88.159124
iter  50 value 84.780935
iter  60 value 82.856324
iter  70 value 81.158561
iter  80 value 80.626240
iter  90 value 80.541520
iter 100 value 80.386227
final  value 80.386227 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.918757 
iter  10 value 94.545145
iter  20 value 91.909643
iter  30 value 88.323998
iter  40 value 87.393692
iter  50 value 84.338745
iter  60 value 82.598224
iter  70 value 82.016402
iter  80 value 80.988340
iter  90 value 80.606407
iter 100 value 80.431408
final  value 80.431408 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.240533 
iter  10 value 93.951273
iter  20 value 88.310154
iter  30 value 87.209962
iter  40 value 86.523903
iter  50 value 85.800057
iter  60 value 85.684393
iter  70 value 83.849360
iter  80 value 82.775960
iter  90 value 81.314559
iter 100 value 81.213201
final  value 81.213201 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.812223 
iter  10 value 94.464491
iter  20 value 94.043260
iter  30 value 90.284232
iter  40 value 88.891603
iter  50 value 88.260833
iter  60 value 87.068322
iter  70 value 82.415292
iter  80 value 81.192977
iter  90 value 80.868025
iter 100 value 80.396692
final  value 80.396692 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.797855 
iter  10 value 94.788431
iter  20 value 90.390243
iter  30 value 85.683453
iter  40 value 83.160828
iter  50 value 81.276681
iter  60 value 80.751450
iter  70 value 80.652712
iter  80 value 80.597199
iter  90 value 80.543762
iter 100 value 80.424222
final  value 80.424222 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.686354 
final  value 94.356076 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.442200 
final  value 94.485655 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.974980 
final  value 94.489020 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.382919 
final  value 94.485780 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.156003 
final  value 94.485977 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.099547 
iter  10 value 94.359359
iter  20 value 94.355359
iter  30 value 88.575801
iter  40 value 85.396103
iter  50 value 84.995490
iter  60 value 82.807121
iter  70 value 82.793062
final  value 82.792923 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.426463 
iter  10 value 94.432633
iter  20 value 94.347798
iter  30 value 94.112762
iter  40 value 88.895753
iter  50 value 85.251265
iter  60 value 85.016454
iter  70 value 84.942151
iter  80 value 83.692212
iter  90 value 79.610526
iter 100 value 79.372611
final  value 79.372611 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.604974 
iter  10 value 94.489142
iter  20 value 94.403597
iter  30 value 91.432953
iter  40 value 91.251794
iter  50 value 91.251631
iter  60 value 91.250544
iter  70 value 91.207956
iter  80 value 87.472045
iter  90 value 86.016975
iter 100 value 85.983538
final  value 85.983538 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.476790 
iter  10 value 94.487901
iter  20 value 86.334640
iter  30 value 86.028256
iter  40 value 85.670680
iter  50 value 85.647961
iter  60 value 85.647615
final  value 85.647505 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.710496 
iter  10 value 94.487270
iter  20 value 94.354530
final  value 94.354458 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.677558 
iter  10 value 94.492425
iter  20 value 94.484330
iter  30 value 93.155470
iter  40 value 87.256458
iter  50 value 81.906869
iter  60 value 79.616133
iter  70 value 79.349215
iter  80 value 79.275442
iter  90 value 79.274238
iter 100 value 79.268816
final  value 79.268816 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.550906 
iter  10 value 86.890275
iter  20 value 86.170415
iter  30 value 85.394544
iter  40 value 85.389654
iter  50 value 85.303339
iter  60 value 85.169445
iter  70 value 83.922740
iter  80 value 83.224196
iter  90 value 83.017785
iter 100 value 82.660555
final  value 82.660555 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.661976 
iter  10 value 94.463318
iter  20 value 93.817942
final  value 93.816068 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.445455 
iter  10 value 94.361509
iter  20 value 94.358906
iter  20 value 94.358906
iter  20 value 94.358906
final  value 94.358906 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.399701 
iter  10 value 94.344734
iter  20 value 94.340415
iter  30 value 94.336811
iter  40 value 93.687554
iter  50 value 84.313034
iter  60 value 83.189312
iter  70 value 82.971257
iter  80 value 80.138723
iter  90 value 79.986395
iter 100 value 79.962591
final  value 79.962591 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.991612 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.886574 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.438329 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.961487 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.826129 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.750795 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.440791 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 117.749631 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.191256 
iter  10 value 89.583653
iter  20 value 87.034078
iter  30 value 87.016052
iter  40 value 86.273167
iter  50 value 85.887476
iter  60 value 84.369286
iter  70 value 84.305965
final  value 84.305871 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.196265 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.625396 
iter  10 value 87.090818
iter  20 value 86.736450
final  value 86.602485 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.894485 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.636820 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.984536 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.978819 
iter  10 value 94.291841
iter  20 value 94.288575
final  value 94.288571 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.698457 
iter  10 value 94.486769
iter  20 value 94.212198
iter  30 value 88.961942
iter  40 value 87.909298
iter  50 value 86.337841
iter  60 value 85.103704
iter  70 value 84.015232
iter  80 value 83.893342
iter  90 value 83.878846
final  value 83.878706 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.111676 
iter  10 value 94.657351
iter  20 value 94.426218
iter  30 value 94.097108
iter  40 value 89.046546
iter  50 value 86.238941
iter  60 value 84.717712
iter  70 value 84.490422
iter  80 value 84.151675
iter  90 value 83.967720
iter 100 value 83.883126
final  value 83.883126 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.703265 
iter  10 value 94.426405
iter  20 value 89.103884
iter  30 value 87.304631
iter  40 value 86.201098
iter  50 value 86.060976
iter  60 value 84.781636
iter  70 value 84.423893
iter  80 value 84.084961
iter  90 value 83.879378
final  value 83.878706 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.667857 
iter  10 value 94.517688
iter  20 value 94.467068
iter  30 value 93.495109
iter  40 value 88.624276
iter  50 value 88.237253
iter  60 value 87.781953
iter  70 value 85.467833
iter  80 value 84.211848
iter  90 value 83.973388
iter 100 value 83.884009
final  value 83.884009 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.220758 
iter  10 value 94.477238
iter  20 value 88.679791
iter  30 value 86.618083
iter  40 value 86.180082
iter  50 value 85.855726
iter  60 value 85.718107
iter  70 value 85.698057
final  value 85.698055 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.888847 
iter  10 value 94.462131
iter  20 value 89.148711
iter  30 value 86.722159
iter  40 value 86.141881
iter  50 value 83.917748
iter  60 value 83.739118
iter  70 value 83.429383
iter  80 value 83.144808
iter  90 value 82.874369
iter 100 value 82.854292
final  value 82.854292 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.834855 
iter  10 value 94.700814
iter  20 value 93.461872
iter  30 value 86.767838
iter  40 value 86.386227
iter  50 value 85.785130
iter  60 value 84.591177
iter  70 value 83.816768
iter  80 value 83.562003
iter  90 value 83.491624
iter 100 value 83.305753
final  value 83.305753 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.048534 
iter  10 value 95.172695
iter  20 value 88.024661
iter  30 value 87.795843
iter  40 value 84.385328
iter  50 value 83.768661
iter  60 value 83.542781
iter  70 value 83.157186
iter  80 value 82.828179
iter  90 value 82.750564
iter 100 value 82.666264
final  value 82.666264 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.067243 
iter  10 value 94.590184
iter  20 value 92.683484
iter  30 value 91.820252
iter  40 value 88.021186
iter  50 value 86.215278
iter  60 value 85.045491
iter  70 value 83.710242
iter  80 value 83.529850
iter  90 value 83.414463
iter 100 value 83.280421
final  value 83.280421 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.170500 
iter  10 value 94.615901
iter  20 value 92.286302
iter  30 value 86.491923
iter  40 value 85.925311
iter  50 value 84.435886
iter  60 value 83.660967
iter  70 value 83.499483
iter  80 value 83.288187
iter  90 value 83.141483
iter 100 value 82.998787
final  value 82.998787 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.683221 
iter  10 value 98.702310
iter  20 value 97.120034
iter  30 value 94.383770
iter  40 value 91.785832
iter  50 value 90.142251
iter  60 value 85.876085
iter  70 value 85.063475
iter  80 value 82.983810
iter  90 value 82.654130
iter 100 value 82.597937
final  value 82.597937 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.806253 
iter  10 value 95.085018
iter  20 value 88.763493
iter  30 value 86.897422
iter  40 value 86.030648
iter  50 value 85.555820
iter  60 value 84.943307
iter  70 value 83.622219
iter  80 value 83.361627
iter  90 value 83.189863
iter 100 value 82.996012
final  value 82.996012 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.232355 
iter  10 value 96.650662
iter  20 value 91.426931
iter  30 value 90.153546
iter  40 value 88.334831
iter  50 value 85.963486
iter  60 value 84.847288
iter  70 value 83.932790
iter  80 value 83.743017
iter  90 value 83.629397
iter 100 value 83.529091
final  value 83.529091 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.247814 
iter  10 value 96.031314
iter  20 value 91.674397
iter  30 value 87.811390
iter  40 value 85.564822
iter  50 value 85.209563
iter  60 value 83.779522
iter  70 value 83.327072
iter  80 value 83.172590
iter  90 value 83.124125
iter 100 value 83.048683
final  value 83.048683 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.794041 
iter  10 value 94.186854
iter  20 value 87.757862
iter  30 value 86.738903
iter  40 value 86.355135
iter  50 value 86.123574
iter  60 value 86.087533
iter  70 value 86.033525
iter  80 value 84.880302
iter  90 value 84.629539
iter 100 value 84.485747
final  value 84.485747 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.585346 
final  value 94.486081 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.543426 
final  value 94.485674 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.707205 
final  value 94.486024 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.409019 
final  value 94.485853 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.490426 
iter  10 value 94.356171
iter  20 value 94.354508
iter  30 value 86.983852
iter  40 value 86.287762
final  value 86.265936 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.075762 
iter  10 value 94.359240
iter  20 value 93.486887
iter  30 value 86.747518
iter  40 value 86.213586
iter  50 value 86.077903
final  value 86.077897 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.889754 
iter  10 value 93.652083
iter  20 value 92.868203
iter  30 value 92.863389
iter  40 value 87.625164
iter  50 value 87.443337
iter  60 value 87.376248
iter  70 value 86.263849
iter  80 value 85.513898
iter  90 value 85.443194
final  value 85.442794 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.823793 
iter  10 value 94.358986
iter  20 value 93.825428
iter  30 value 86.132552
iter  40 value 85.585138
iter  50 value 85.322121
iter  60 value 85.000511
iter  70 value 84.998387
iter  80 value 84.967328
iter  90 value 83.636668
iter 100 value 83.252263
final  value 83.252263 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.749647 
iter  10 value 94.359793
iter  20 value 94.332715
iter  30 value 94.054233
iter  40 value 90.529965
iter  50 value 87.383008
iter  60 value 85.677821
final  value 85.663868 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.312948 
iter  10 value 94.490073
iter  20 value 94.484925
iter  30 value 93.637845
iter  40 value 87.306719
iter  50 value 87.102977
iter  60 value 85.361139
iter  70 value 85.301847
iter  80 value 85.107682
iter  90 value 85.028360
iter 100 value 85.006335
final  value 85.006335 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 99.532137 
iter  10 value 94.362198
iter  20 value 94.354990
final  value 94.354914 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.063286 
iter  10 value 92.853078
iter  20 value 92.842111
iter  30 value 84.571138
iter  40 value 83.760539
iter  50 value 83.753558
iter  60 value 83.747389
iter  70 value 83.740141
final  value 83.739723 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.535785 
iter  10 value 94.362091
iter  20 value 94.048656
iter  30 value 86.194257
iter  40 value 85.747684
iter  50 value 85.601580
iter  60 value 85.411274
final  value 85.411053 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.040064 
iter  10 value 94.492058
iter  20 value 94.180573
iter  30 value 86.560122
iter  40 value 85.689582
iter  50 value 85.454743
iter  60 value 85.355703
iter  70 value 85.309081
final  value 85.307894 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.655082 
iter  10 value 94.362614
iter  20 value 92.472126
iter  30 value 86.226398
iter  40 value 85.695657
iter  50 value 85.644847
iter  60 value 85.631141
iter  70 value 85.383423
iter  80 value 84.048312
iter  90 value 83.965017
iter 100 value 83.963786
final  value 83.963786 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.877456 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.346384 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.635444 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.396486 
final  value 94.484208 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.634151 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.527139 
iter  10 value 94.484212
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.006902 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.444264 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.669186 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.963598 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.184817 
iter  10 value 93.822256
final  value 93.809646 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.822517 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.005099 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.966567 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.480256 
iter  10 value 94.275982
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.484701 
iter  10 value 94.386756
iter  20 value 94.065340
iter  30 value 93.854288
iter  40 value 90.065728
iter  50 value 88.869337
iter  60 value 87.881079
iter  70 value 86.883743
iter  80 value 82.119059
iter  90 value 82.035561
iter 100 value 81.748144
final  value 81.748144 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.367403 
iter  10 value 93.331543
iter  20 value 85.929957
iter  30 value 85.022995
iter  40 value 84.899099
iter  50 value 84.858891
final  value 84.858838 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.434536 
iter  10 value 94.396491
iter  20 value 88.114277
iter  30 value 86.538282
iter  40 value 85.512187
iter  50 value 83.921756
iter  60 value 83.586882
iter  70 value 83.446944
iter  80 value 83.382226
final  value 83.381997 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.284271 
iter  10 value 94.487258
iter  20 value 90.824111
iter  30 value 90.363803
iter  40 value 90.321579
iter  50 value 90.311267
iter  50 value 90.311266
iter  50 value 90.311266
final  value 90.311266 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.522401 
iter  10 value 94.471688
iter  20 value 91.552640
iter  30 value 90.384149
iter  40 value 90.343371
iter  50 value 90.313027
final  value 90.311266 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.748626 
iter  10 value 94.453828
iter  20 value 91.870754
iter  30 value 87.279467
iter  40 value 86.999045
iter  50 value 85.567273
iter  60 value 84.499221
iter  70 value 82.016406
iter  80 value 80.956141
iter  90 value 80.806444
iter 100 value 80.583066
final  value 80.583066 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.424465 
iter  10 value 94.525186
iter  20 value 94.485765
iter  30 value 93.949691
iter  40 value 93.882621
iter  50 value 86.709147
iter  60 value 84.174813
iter  70 value 82.536866
iter  80 value 81.463281
iter  90 value 81.045027
iter 100 value 80.121086
final  value 80.121086 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.532617 
iter  10 value 91.867167
iter  20 value 87.392801
iter  30 value 86.579021
iter  40 value 84.913467
iter  50 value 82.326177
iter  60 value 81.241859
iter  70 value 80.408819
iter  80 value 80.333829
iter  90 value 80.268667
iter 100 value 80.187758
final  value 80.187758 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.622480 
iter  10 value 94.654098
iter  20 value 94.230612
iter  30 value 93.929475
iter  40 value 93.817083
iter  50 value 92.917489
iter  60 value 88.436512
iter  70 value 85.491368
iter  80 value 83.642759
iter  90 value 82.977434
iter 100 value 82.842179
final  value 82.842179 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.194434 
iter  10 value 94.666041
iter  20 value 94.508546
iter  30 value 93.720959
iter  40 value 86.752232
iter  50 value 85.986145
iter  60 value 85.416798
iter  70 value 83.232773
iter  80 value 81.409556
iter  90 value 80.908865
iter 100 value 80.777300
final  value 80.777300 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.044479 
iter  10 value 99.924502
iter  20 value 96.387545
iter  30 value 89.338775
iter  40 value 87.960136
iter  50 value 86.959840
iter  60 value 86.302973
iter  70 value 82.886395
iter  80 value 81.212868
iter  90 value 80.547886
iter 100 value 80.387890
final  value 80.387890 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.610882 
iter  10 value 97.219877
iter  20 value 90.811816
iter  30 value 88.843739
iter  40 value 86.905669
iter  50 value 86.216990
iter  60 value 85.505490
iter  70 value 84.172864
iter  80 value 82.488969
iter  90 value 82.235120
iter 100 value 81.821650
final  value 81.821650 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.143085 
iter  10 value 94.426251
iter  20 value 89.421143
iter  30 value 83.214444
iter  40 value 82.184458
iter  50 value 81.791586
iter  60 value 81.720837
iter  70 value 81.702218
iter  80 value 81.155720
iter  90 value 80.530797
iter 100 value 80.183441
final  value 80.183441 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.764951 
iter  10 value 94.578615
iter  20 value 90.386638
iter  30 value 90.060703
iter  40 value 88.785783
iter  50 value 87.708782
iter  60 value 84.151058
iter  70 value 83.275240
iter  80 value 82.948586
iter  90 value 82.831132
iter 100 value 82.389173
final  value 82.389173 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.000416 
iter  10 value 94.850252
iter  20 value 92.968156
iter  30 value 89.019817
iter  40 value 86.642775
iter  50 value 83.725881
iter  60 value 83.376276
iter  70 value 82.758629
iter  80 value 82.481666
iter  90 value 82.363467
iter 100 value 82.123319
final  value 82.123319 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.719367 
final  value 94.486119 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.728399 
final  value 94.485744 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.645103 
iter  10 value 94.485770
iter  20 value 94.484207
iter  20 value 94.484207
final  value 94.484207 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.295753 
final  value 94.485640 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.521274 
final  value 94.485937 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.469992 
iter  10 value 94.488908
iter  20 value 94.484127
iter  20 value 94.484127
final  value 94.026710 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.505944 
iter  10 value 93.815000
iter  20 value 93.741703
iter  30 value 93.619632
iter  40 value 88.360533
iter  50 value 80.890674
iter  60 value 80.664643
iter  70 value 80.359163
iter  80 value 79.977209
iter  90 value 79.780808
iter 100 value 79.780225
final  value 79.780225 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.130020 
iter  10 value 92.370316
iter  20 value 89.844062
iter  30 value 88.956774
iter  40 value 87.291055
iter  50 value 87.289602
iter  60 value 87.042792
iter  70 value 86.141050
iter  80 value 85.527846
iter  90 value 82.508630
iter 100 value 80.831072
final  value 80.831072 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.065311 
iter  10 value 94.488972
iter  20 value 94.484302
iter  30 value 94.405810
iter  40 value 86.776136
iter  50 value 86.543590
iter  60 value 85.591036
iter  70 value 80.638607
iter  80 value 80.229874
iter  90 value 79.935805
iter 100 value 79.897908
final  value 79.897908 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.514274 
iter  10 value 94.489150
iter  20 value 94.484440
iter  30 value 94.431547
iter  40 value 88.099047
iter  50 value 86.223350
iter  60 value 85.084129
iter  70 value 84.985386
iter  80 value 84.630787
iter  90 value 84.495538
final  value 84.494976 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.559574 
iter  10 value 94.492387
iter  20 value 94.304536
iter  30 value 92.455265
iter  40 value 91.642321
iter  50 value 91.633901
iter  60 value 91.240073
iter  70 value 91.067913
iter  80 value 91.060576
final  value 91.060506 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.440267 
iter  10 value 94.375469
iter  20 value 94.034281
iter  30 value 94.028773
iter  40 value 88.603209
iter  50 value 87.069228
iter  60 value 86.361885
iter  70 value 83.839813
iter  80 value 83.830231
iter  90 value 83.829016
iter 100 value 83.826531
final  value 83.826531 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.330736 
iter  10 value 87.039565
iter  20 value 87.022404
iter  30 value 87.015430
iter  40 value 86.568345
iter  50 value 85.909222
iter  60 value 82.434681
iter  70 value 80.970332
iter  80 value 80.399261
iter  90 value 79.990515
iter 100 value 79.614067
final  value 79.614067 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.807606 
iter  10 value 94.035008
iter  20 value 94.027857
iter  30 value 91.580098
iter  40 value 84.078725
iter  50 value 84.077942
iter  60 value 84.070774
final  value 84.070676 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.598938 
iter  10 value 94.484955
iter  20 value 86.355147
iter  30 value 85.401140
iter  40 value 85.343512
iter  40 value 85.343511
iter  40 value 85.343511
final  value 85.343511 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.038734 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.217756 
iter  10 value 89.307402
iter  20 value 88.914846
iter  30 value 88.869395
final  value 88.869060 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.222480 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.766391 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.635859 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.265336 
final  value 93.869755 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.636794 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.724697 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.691225 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.715954 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.262271 
iter  10 value 93.729737
iter  20 value 93.714427
iter  30 value 93.628113
iter  40 value 93.591493
iter  50 value 93.591288
final  value 93.591274 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.631776 
iter  10 value 94.008698
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.374332 
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.343478 
final  value 93.817004 
converged
Fitting Repeat 5 

# weights:  507
initial  value 127.833169 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.895966 
iter  10 value 94.076028
iter  20 value 94.022540
iter  30 value 90.019995
iter  40 value 85.401669
iter  50 value 82.144935
iter  60 value 81.129492
iter  70 value 80.900941
iter  80 value 78.575369
iter  90 value 78.394597
iter 100 value 78.316659
final  value 78.316659 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.070480 
iter  10 value 94.133717
iter  20 value 93.977896
iter  30 value 93.874933
iter  40 value 85.301149
iter  50 value 82.505289
iter  60 value 82.382729
iter  70 value 82.298506
iter  80 value 81.625626
iter  90 value 80.374417
iter 100 value 79.512014
final  value 79.512014 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.845547 
iter  10 value 94.059062
iter  20 value 94.054816
iter  30 value 87.166821
iter  40 value 85.583938
iter  50 value 83.587601
iter  60 value 82.233903
iter  70 value 81.603401
iter  80 value 81.589669
final  value 81.589075 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.394877 
iter  10 value 93.814846
iter  20 value 86.637342
iter  30 value 85.094938
iter  40 value 83.056519
iter  50 value 82.672409
iter  60 value 82.585186
iter  70 value 82.231507
iter  80 value 82.060476
iter  90 value 82.039476
final  value 82.038412 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.692852 
iter  10 value 94.057001
iter  20 value 93.885801
iter  30 value 93.847696
iter  40 value 93.844197
iter  50 value 92.396560
iter  60 value 84.107362
iter  70 value 83.141015
iter  80 value 82.709905
iter  90 value 82.563423
iter 100 value 82.557717
final  value 82.557717 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.765504 
iter  10 value 94.055504
iter  20 value 85.163619
iter  30 value 82.797555
iter  40 value 81.957043
iter  50 value 81.874967
iter  60 value 81.697593
iter  70 value 81.197721
iter  80 value 80.935270
iter  90 value 80.920750
iter 100 value 80.690787
final  value 80.690787 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.568219 
iter  10 value 94.153209
iter  20 value 93.865355
iter  30 value 93.576960
iter  40 value 85.320388
iter  50 value 84.261435
iter  60 value 83.136548
iter  70 value 82.390543
iter  80 value 82.208257
iter  90 value 81.957474
iter 100 value 81.206739
final  value 81.206739 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.798636 
iter  10 value 94.080825
iter  20 value 91.598190
iter  30 value 86.407856
iter  40 value 82.702703
iter  50 value 81.556731
iter  60 value 79.813088
iter  70 value 77.999134
iter  80 value 76.852346
iter  90 value 76.750731
iter 100 value 76.651647
final  value 76.651647 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.232043 
iter  10 value 94.487406
iter  20 value 93.924321
iter  30 value 88.353670
iter  40 value 82.851425
iter  50 value 80.597950
iter  60 value 80.168320
iter  70 value 79.502641
iter  80 value 78.704344
iter  90 value 78.139501
iter 100 value 78.004205
final  value 78.004205 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.996700 
iter  10 value 93.956800
iter  20 value 91.608019
iter  30 value 90.623807
iter  40 value 85.195102
iter  50 value 84.612442
iter  60 value 81.704497
iter  70 value 79.390742
iter  80 value 78.537816
iter  90 value 77.812532
iter 100 value 77.497566
final  value 77.497566 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.841849 
iter  10 value 94.700166
iter  20 value 88.026121
iter  30 value 85.176847
iter  40 value 82.621292
iter  50 value 80.298339
iter  60 value 79.757679
iter  70 value 78.680641
iter  80 value 77.353550
iter  90 value 77.002679
iter 100 value 76.655162
final  value 76.655162 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.831214 
iter  10 value 94.077954
iter  20 value 93.555049
iter  30 value 87.237616
iter  40 value 86.085947
iter  50 value 81.793975
iter  60 value 78.907630
iter  70 value 77.743798
iter  80 value 77.263727
iter  90 value 76.948919
iter 100 value 76.752435
final  value 76.752435 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.926406 
iter  10 value 95.714817
iter  20 value 92.400619
iter  30 value 87.727968
iter  40 value 86.633174
iter  50 value 85.776621
iter  60 value 81.246511
iter  70 value 80.429789
iter  80 value 80.303616
iter  90 value 80.145335
iter 100 value 79.994846
final  value 79.994846 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.474859 
iter  10 value 93.410661
iter  20 value 88.016443
iter  30 value 83.679879
iter  40 value 83.324406
iter  50 value 81.787605
iter  60 value 78.995364
iter  70 value 78.184235
iter  80 value 77.980198
iter  90 value 77.582362
iter 100 value 77.388478
final  value 77.388478 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.965039 
iter  10 value 95.280210
iter  20 value 91.304077
iter  30 value 85.288253
iter  40 value 82.044388
iter  50 value 80.151717
iter  60 value 79.607729
iter  70 value 79.331188
iter  80 value 78.108040
iter  90 value 77.467689
iter 100 value 77.330789
final  value 77.330789 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.184596 
final  value 94.054591 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.076302 
final  value 94.054393 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.580788 
iter  10 value 91.579873
iter  20 value 84.654726
iter  30 value 82.826249
iter  40 value 81.694919
iter  50 value 81.660450
iter  60 value 81.659748
final  value 81.659670 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.666666 
final  value 94.054371 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.908228 
iter  10 value 88.554040
iter  20 value 85.272531
iter  30 value 85.271937
iter  40 value 84.570770
iter  50 value 84.454450
iter  60 value 84.164721
iter  70 value 83.943696
final  value 83.943674 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.283349 
iter  10 value 94.057317
iter  20 value 94.023828
final  value 93.725233 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.976099 
iter  10 value 94.057822
iter  20 value 93.921946
iter  30 value 84.218110
iter  40 value 83.853477
iter  50 value 83.851606
iter  60 value 83.850977
final  value 83.850917 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.048061 
iter  10 value 94.057534
iter  20 value 94.052927
final  value 94.052921 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.008564 
iter  10 value 92.861728
iter  20 value 90.491864
iter  30 value 82.658835
iter  40 value 79.325596
iter  50 value 76.206636
iter  60 value 75.470782
iter  70 value 75.427568
iter  80 value 75.301379
iter  90 value 75.289948
iter 100 value 75.289008
final  value 75.289008 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.981207 
iter  10 value 94.058057
iter  20 value 94.052450
iter  30 value 92.369004
iter  40 value 92.327140
iter  50 value 91.691405
iter  60 value 91.649603
iter  70 value 91.477250
iter  80 value 86.729346
iter  90 value 86.699921
iter 100 value 85.980994
final  value 85.980994 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.080013 
iter  10 value 93.997407
iter  20 value 93.985362
final  value 93.984954 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.052493 
iter  10 value 94.024593
iter  20 value 94.013237
iter  30 value 93.962565
iter  40 value 88.314071
iter  50 value 81.856884
iter  60 value 81.780023
iter  70 value 81.702555
iter  80 value 81.183815
iter  90 value 80.767505
iter 100 value 80.663674
final  value 80.663674 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.183093 
iter  10 value 93.799113
iter  20 value 93.796428
iter  30 value 85.200093
iter  40 value 84.132445
iter  50 value 84.069910
iter  60 value 83.928449
iter  70 value 83.834046
iter  80 value 83.833015
final  value 83.830711 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.390454 
iter  10 value 94.060806
iter  20 value 93.785668
iter  30 value 84.127298
iter  40 value 84.061573
iter  50 value 84.060576
iter  50 value 84.060575
final  value 84.060575 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.048435 
iter  10 value 85.077940
iter  20 value 80.781513
iter  30 value 78.505665
iter  40 value 78.250677
iter  50 value 78.221176
iter  60 value 78.220734
iter  70 value 78.216222
iter  80 value 78.214602
iter  90 value 76.377029
iter 100 value 76.290249
final  value 76.290249 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 138.771694 
iter  10 value 117.895243
iter  20 value 115.444518
iter  30 value 107.619779
iter  40 value 107.518124
iter  50 value 107.514769
final  value 107.514725 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.202872 
iter  10 value 108.940384
iter  20 value 108.534876
iter  30 value 108.522198
final  value 108.520777 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.239706 
iter  10 value 117.735394
iter  20 value 117.732694
iter  30 value 117.489784
iter  40 value 116.899692
iter  50 value 115.144705
iter  60 value 112.254227
iter  70 value 106.673951
iter  80 value 106.665149
iter  90 value 106.656498
iter 100 value 105.489999
final  value 105.489999 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.060562 
iter  10 value 117.881631
iter  20 value 117.735689
iter  30 value 117.221394
iter  40 value 115.259235
iter  50 value 114.915702
final  value 114.915608 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.521004 
iter  10 value 117.684518
iter  20 value 113.824166
iter  30 value 105.059555
final  value 105.055037 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Wed Oct 25 12:14:15 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 
 54.405   1.762  87.765