##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2024-11-24 r87369)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.13.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ...Warning: program compiled against libxml 212 using older 211
 OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       39.780  0.391  40.248
FSmethod      37.468  0.331  37.873
corr_plot     37.417  0.247  37.726
pred_ensembel 18.467  0.547  17.817
enrichfindP    0.520  0.020  21.235
getFASTA       0.134  0.020   5.513
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/home/biocbuild/R/R-4.5.0-devel_2024-11-24/site-library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2024-11-24 r87369) -- "Unsuffered Consequences"
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 104.934288 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.477843 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.730001 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.895040 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.698230 
iter  10 value 93.328261
iter  10 value 93.328261
iter  10 value 93.328261
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.967276 
iter  10 value 93.198556
iter  20 value 92.959535
final  value 92.959524 
converged
Fitting Repeat 2 

# weights:  305
initial  value 121.035461 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.497698 
iter  10 value 93.328264
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.779080 
iter  10 value 93.329237
iter  20 value 93.328307
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.713692 
iter  10 value 87.520139
iter  20 value 87.287312
final  value 87.285265 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.525804 
iter  10 value 93.482768
final  value 93.482759 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.055697 
iter  10 value 85.042580
iter  20 value 83.481119
iter  30 value 81.490210
iter  40 value 81.027357
iter  50 value 80.916368
iter  60 value 80.915666
final  value 80.915599 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.067806 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.824123 
iter  10 value 93.354249
final  value 93.187808 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.882446 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.494624 
iter  10 value 94.057798
iter  20 value 90.435908
iter  30 value 87.560345
iter  40 value 84.897373
iter  50 value 83.979092
iter  60 value 83.964152
iter  70 value 83.960527
final  value 83.960245 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.697445 
iter  10 value 94.027023
iter  20 value 93.279886
iter  30 value 92.414395
iter  40 value 89.675818
iter  50 value 89.317121
iter  60 value 87.989089
iter  70 value 87.683542
iter  80 value 86.145708
iter  90 value 85.353307
iter 100 value 84.666346
final  value 84.666346 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.459315 
iter  10 value 93.947302
iter  20 value 91.372906
iter  30 value 87.977744
iter  40 value 86.918942
iter  50 value 86.661181
iter  60 value 85.633839
iter  70 value 84.017535
iter  80 value 83.964870
iter  90 value 83.960253
final  value 83.960245 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.322334 
iter  10 value 94.054880
iter  20 value 93.345674
iter  30 value 93.203952
iter  40 value 93.189113
iter  50 value 93.173384
iter  60 value 86.631928
iter  70 value 84.803636
iter  80 value 84.281030
iter  90 value 84.076563
iter 100 value 83.974385
final  value 83.974385 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.877933 
iter  10 value 93.964768
iter  20 value 92.035580
iter  30 value 91.110111
iter  40 value 91.002692
iter  50 value 90.999241
iter  60 value 90.997654
final  value 90.996877 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.238082 
iter  10 value 93.489987
iter  20 value 91.712147
iter  30 value 87.644437
iter  40 value 84.579687
iter  50 value 83.755112
iter  60 value 82.856132
iter  70 value 82.281907
iter  80 value 81.851023
iter  90 value 81.450853
iter 100 value 80.953376
final  value 80.953376 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.268355 
iter  10 value 94.081543
iter  20 value 93.422074
iter  30 value 90.858792
iter  40 value 87.716046
iter  50 value 86.404376
iter  60 value 86.119762
iter  70 value 84.749598
iter  80 value 84.227987
iter  90 value 84.117238
iter 100 value 83.775349
final  value 83.775349 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.206800 
iter  10 value 93.322753
iter  20 value 89.332758
iter  30 value 87.716285
iter  40 value 84.863164
iter  50 value 83.941642
iter  60 value 83.172035
iter  70 value 82.864751
iter  80 value 82.689921
iter  90 value 82.491990
iter 100 value 82.320929
final  value 82.320929 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.351781 
iter  10 value 93.991177
iter  20 value 93.233525
iter  30 value 93.060566
iter  40 value 93.036813
iter  50 value 92.888751
iter  60 value 87.196052
iter  70 value 85.527521
iter  80 value 85.062909
iter  90 value 84.208545
iter 100 value 83.718806
final  value 83.718806 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.054350 
iter  10 value 94.023724
iter  20 value 86.182623
iter  30 value 84.746897
iter  40 value 83.240678
iter  50 value 81.535656
iter  60 value 81.241938
iter  70 value 81.145812
iter  80 value 81.082089
iter  90 value 80.771964
iter 100 value 80.593245
final  value 80.593245 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.100849 
iter  10 value 89.013499
iter  20 value 84.815050
iter  30 value 84.535036
iter  40 value 83.774463
iter  50 value 83.144674
iter  60 value 81.790640
iter  70 value 81.426328
iter  80 value 81.049891
iter  90 value 80.776672
iter 100 value 80.555961
final  value 80.555961 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.506911 
iter  10 value 93.553882
iter  20 value 85.776006
iter  30 value 84.015296
iter  40 value 83.322251
iter  50 value 82.075597
iter  60 value 81.613963
iter  70 value 80.968806
iter  80 value 80.862185
iter  90 value 80.693571
iter 100 value 80.414840
final  value 80.414840 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.522677 
iter  10 value 94.053686
iter  20 value 93.287839
iter  30 value 85.721970
iter  40 value 82.858300
iter  50 value 81.904711
iter  60 value 80.928451
iter  70 value 80.722980
iter  80 value 80.567786
iter  90 value 80.297045
iter 100 value 80.240474
final  value 80.240474 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.043008 
iter  10 value 93.076971
iter  20 value 89.015621
iter  30 value 83.569081
iter  40 value 83.048730
iter  50 value 82.461991
iter  60 value 82.180521
iter  70 value 81.902684
iter  80 value 81.146041
iter  90 value 80.787210
iter 100 value 80.668374
final  value 80.668374 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 140.463047 
iter  10 value 93.873381
iter  20 value 93.363399
iter  30 value 86.864999
iter  40 value 86.242654
iter  50 value 86.002340
iter  60 value 83.757892
iter  70 value 82.979426
iter  80 value 81.546211
iter  90 value 80.579964
iter 100 value 80.293759
final  value 80.293759 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.273969 
iter  10 value 93.330396
final  value 93.330323 
converged
Fitting Repeat 2 

# weights:  103
initial  value 123.680490 
iter  10 value 93.330582
iter  20 value 93.330322
iter  30 value 93.217580
final  value 93.217376 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.128312 
final  value 94.054710 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.729867 
final  value 94.054365 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.910674 
final  value 94.054577 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.790467 
iter  10 value 93.119774
iter  20 value 93.092053
iter  30 value 93.087514
iter  40 value 90.803994
iter  50 value 86.020539
final  value 86.009475 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.802421 
iter  10 value 94.057880
iter  20 value 94.052928
iter  30 value 93.290184
final  value 93.226321 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.277645 
iter  10 value 93.333764
iter  20 value 93.330455
iter  30 value 93.216943
iter  40 value 93.216560
iter  50 value 93.216539
final  value 93.216524 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.508638 
iter  10 value 94.058424
iter  20 value 94.053538
iter  30 value 93.651299
iter  40 value 89.898943
iter  50 value 85.052994
iter  60 value 84.638073
iter  70 value 84.558597
iter  80 value 84.061154
iter  90 value 83.453061
iter 100 value 83.425100
final  value 83.425100 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.952312 
iter  10 value 94.057755
final  value 94.053084 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.312123 
iter  10 value 93.343954
iter  20 value 93.336111
iter  30 value 93.330504
iter  40 value 93.323608
iter  50 value 93.131987
iter  60 value 92.159181
iter  70 value 90.478403
final  value 90.475621 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.076341 
iter  10 value 93.970315
iter  20 value 93.752488
iter  30 value 93.519846
iter  40 value 86.569757
iter  50 value 86.539037
iter  60 value 85.642035
iter  70 value 82.377817
iter  80 value 81.201851
iter  90 value 79.774862
iter 100 value 79.108064
final  value 79.108064 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.102664 
iter  10 value 93.379517
iter  20 value 89.908929
iter  30 value 85.084065
iter  40 value 84.552311
iter  50 value 84.538800
iter  60 value 84.533603
iter  70 value 84.531050
iter  80 value 84.530970
final  value 84.530952 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.747105 
iter  10 value 94.054342
iter  20 value 93.708350
iter  30 value 92.252144
iter  40 value 91.866489
final  value 91.565101 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.447639 
iter  10 value 93.337045
iter  20 value 93.334696
iter  30 value 93.053158
iter  40 value 91.763948
iter  50 value 87.434635
iter  60 value 87.075784
iter  70 value 84.973692
iter  80 value 83.387026
iter  90 value 82.907916
iter 100 value 82.907527
final  value 82.907527 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.049166 
final  value 94.476471 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.740274 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.484287 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.406718 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.473302 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.810460 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.922563 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.564125 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.792012 
iter  10 value 93.796861
iter  20 value 93.783163
final  value 93.783150 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.712754 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.778590 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.685972 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.653469 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.953206 
iter  10 value 92.832893
iter  20 value 92.525855
final  value 92.525851 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.267937 
final  value 94.484216 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.805769 
iter  10 value 94.487678
iter  20 value 93.571460
iter  30 value 91.821416
iter  40 value 91.389687
iter  50 value 84.634572
iter  60 value 84.344013
iter  70 value 83.287275
iter  80 value 83.178294
iter  90 value 83.005942
iter 100 value 82.539160
final  value 82.539160 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.754941 
iter  10 value 94.305937
iter  20 value 89.845743
iter  30 value 87.327415
iter  40 value 87.037857
iter  50 value 86.292208
iter  60 value 80.557961
iter  70 value 80.249957
iter  80 value 80.060675
iter  90 value 80.023269
iter 100 value 79.950460
final  value 79.950460 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.902052 
iter  10 value 94.491669
iter  20 value 94.488570
iter  30 value 94.294686
iter  40 value 87.471823
iter  50 value 86.359871
iter  60 value 86.102279
iter  70 value 83.056306
iter  80 value 82.871342
iter  90 value 82.517841
iter 100 value 82.444897
final  value 82.444897 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 108.513645 
iter  10 value 92.387237
iter  20 value 85.179568
iter  30 value 84.763319
iter  40 value 83.883257
iter  50 value 82.316867
iter  60 value 81.716052
iter  70 value 81.701975
iter  80 value 81.701549
iter  90 value 81.696833
iter 100 value 81.694907
final  value 81.694907 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.472490 
iter  10 value 94.486831
iter  20 value 93.573064
iter  30 value 90.427089
iter  40 value 87.280320
iter  50 value 86.502367
iter  60 value 86.237857
iter  70 value 82.479375
iter  80 value 81.483473
iter  90 value 81.361071
iter 100 value 81.338503
final  value 81.338503 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 115.784661 
iter  10 value 94.625424
iter  20 value 91.350943
iter  30 value 86.572684
iter  40 value 83.464307
iter  50 value 82.565250
iter  60 value 82.111081
iter  70 value 82.071822
iter  80 value 81.310606
iter  90 value 80.236275
iter 100 value 79.912808
final  value 79.912808 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.951673 
iter  10 value 94.822995
iter  20 value 93.144891
iter  30 value 86.604343
iter  40 value 82.437963
iter  50 value 82.188833
iter  60 value 82.156288
iter  70 value 82.013689
iter  80 value 81.230439
iter  90 value 79.566741
iter 100 value 78.979850
final  value 78.979850 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.426333 
iter  10 value 94.407297
iter  20 value 85.058352
iter  30 value 82.335468
iter  40 value 81.099422
iter  50 value 80.758098
iter  60 value 80.184193
iter  70 value 79.646795
iter  80 value 79.554040
iter  90 value 79.318174
iter 100 value 79.129728
final  value 79.129728 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.538082 
iter  10 value 94.477960
iter  20 value 85.666286
iter  30 value 84.753365
iter  40 value 83.433972
iter  50 value 82.088629
iter  60 value 81.977911
iter  70 value 81.882427
iter  80 value 81.591532
iter  90 value 81.342906
iter 100 value 79.905019
final  value 79.905019 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.273881 
iter  10 value 88.941080
iter  20 value 83.884246
iter  30 value 82.926663
iter  40 value 81.743485
iter  50 value 81.580853
iter  60 value 80.383666
iter  70 value 80.040061
iter  80 value 80.027845
iter  90 value 79.906894
iter 100 value 79.645709
final  value 79.645709 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.371575 
iter  10 value 93.117988
iter  20 value 86.272076
iter  30 value 83.903066
iter  40 value 82.381092
iter  50 value 81.161182
iter  60 value 80.375271
iter  70 value 79.757422
iter  80 value 79.269089
iter  90 value 79.023180
iter 100 value 78.936095
final  value 78.936095 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.889578 
iter  10 value 94.519469
iter  20 value 92.471555
iter  30 value 88.884879
iter  40 value 84.032200
iter  50 value 80.968748
iter  60 value 80.503526
iter  70 value 79.858476
iter  80 value 79.496553
iter  90 value 79.130013
iter 100 value 78.982255
final  value 78.982255 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.367558 
iter  10 value 94.519081
iter  20 value 94.317141
iter  30 value 84.738899
iter  40 value 84.062693
iter  50 value 83.899009
iter  60 value 81.560590
iter  70 value 79.673550
iter  80 value 79.394253
iter  90 value 78.877417
iter 100 value 78.685945
final  value 78.685945 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.103811 
iter  10 value 94.696632
iter  20 value 93.369317
iter  30 value 85.990211
iter  40 value 84.796646
iter  50 value 82.656771
iter  60 value 81.972613
iter  70 value 81.797257
iter  80 value 81.767222
iter  90 value 81.584653
iter 100 value 80.707313
final  value 80.707313 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.017135 
iter  10 value 94.444462
iter  20 value 90.623084
iter  30 value 83.440593
iter  40 value 83.118695
iter  50 value 82.305647
iter  60 value 80.360902
iter  70 value 79.788879
iter  80 value 79.516583
iter  90 value 79.449237
iter 100 value 79.117558
final  value 79.117558 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.656968 
final  value 94.486033 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.032211 
final  value 94.485642 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.567034 
final  value 94.485856 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.389228 
final  value 94.486113 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.129839 
final  value 94.485789 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.658188 
iter  10 value 94.484784
final  value 94.484741 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.811358 
iter  10 value 94.484710
final  value 94.484360 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.791245 
iter  10 value 94.359363
iter  20 value 92.806863
iter  30 value 91.548214
iter  40 value 87.802254
iter  50 value 87.644811
iter  60 value 87.639916
final  value 87.639867 
converged
Fitting Repeat 4 

# weights:  305
initial  value 121.420927 
iter  10 value 94.359326
iter  20 value 94.354657
iter  30 value 94.028067
iter  40 value 84.422684
iter  50 value 84.313688
iter  60 value 84.022030
final  value 84.020993 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.043516 
iter  10 value 81.845961
iter  20 value 81.066263
iter  30 value 81.019029
iter  40 value 81.015952
iter  50 value 80.972187
iter  60 value 80.526074
iter  70 value 80.137486
iter  80 value 80.135844
final  value 80.135842 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.191822 
iter  10 value 93.949060
iter  20 value 92.111231
iter  30 value 92.067579
iter  40 value 91.997850
iter  50 value 91.960713
iter  60 value 91.960020
iter  70 value 88.470914
iter  80 value 87.530622
iter  90 value 84.644640
iter 100 value 84.168743
final  value 84.168743 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.150203 
iter  10 value 90.815732
iter  20 value 90.556568
iter  30 value 89.950100
iter  40 value 83.276211
iter  50 value 83.265721
iter  60 value 83.184424
iter  70 value 83.050902
final  value 83.048893 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.835503 
iter  10 value 94.362691
iter  20 value 94.356142
iter  30 value 94.164739
iter  40 value 92.859799
iter  50 value 85.823256
iter  60 value 82.474050
iter  70 value 80.401687
iter  80 value 79.378568
iter  90 value 78.812841
iter 100 value 78.521138
final  value 78.521138 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.145879 
iter  10 value 94.489573
iter  20 value 94.113050
iter  30 value 90.966672
iter  40 value 90.397959
iter  50 value 82.581795
iter  60 value 81.606461
iter  70 value 81.063520
iter  80 value 81.021960
iter  90 value 81.016777
final  value 81.013983 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.628190 
iter  10 value 92.535354
iter  20 value 92.531951
iter  30 value 92.495649
iter  40 value 92.033231
iter  50 value 91.939532
iter  60 value 91.938850
iter  70 value 91.927513
iter  80 value 91.864038
final  value 91.855877 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.523197 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.412948 
iter  10 value 94.210184
iter  20 value 94.209545
iter  20 value 94.209544
iter  20 value 94.209544
final  value 94.209544 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.934909 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.024865 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.457825 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.224416 
iter  10 value 94.430450
iter  20 value 94.354286
iter  20 value 94.354286
iter  20 value 94.354286
final  value 94.354286 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.830106 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.933636 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.647793 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.335135 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.687064 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.490647 
iter  10 value 94.508520
iter  20 value 92.414500
iter  30 value 92.311345
iter  40 value 92.303760
iter  50 value 92.303658
iter  60 value 89.419830
final  value 89.330621 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.181087 
final  value 92.608648 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.131651 
final  value 94.330952 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.141846 
iter  10 value 94.408013
final  value 94.405644 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.029651 
iter  10 value 93.339686
iter  20 value 87.567865
iter  30 value 86.861839
iter  40 value 84.979971
iter  50 value 84.801642
iter  60 value 83.903605
iter  70 value 83.825140
iter  80 value 83.817708
final  value 83.817587 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.709955 
iter  10 value 94.433000
iter  20 value 94.267262
iter  30 value 91.644935
iter  40 value 87.641213
iter  50 value 85.497722
iter  60 value 84.830566
iter  70 value 84.323730
iter  80 value 84.190227
final  value 84.177696 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.615241 
iter  10 value 94.447705
iter  20 value 93.608713
iter  30 value 93.274375
iter  40 value 93.223650
iter  50 value 91.522684
iter  60 value 91.475876
final  value 91.467530 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.589858 
iter  10 value 94.456751
iter  20 value 93.888590
iter  30 value 90.272942
iter  40 value 88.629178
iter  50 value 87.711621
iter  60 value 87.657500
iter  70 value 87.543439
iter  80 value 87.512104
iter  90 value 87.507733
final  value 87.507493 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.144374 
iter  10 value 94.047610
iter  20 value 87.416971
iter  30 value 87.001103
iter  40 value 85.791884
iter  50 value 84.764658
iter  60 value 84.180147
iter  70 value 83.857735
iter  80 value 83.817589
final  value 83.817587 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.513322 
iter  10 value 93.822151
iter  20 value 90.195690
iter  30 value 89.339117
iter  40 value 87.092991
iter  50 value 84.665338
iter  60 value 84.483536
iter  70 value 84.357386
iter  80 value 84.303559
iter  90 value 83.934458
iter 100 value 83.754437
final  value 83.754437 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.824566 
iter  10 value 93.939890
iter  20 value 89.878472
iter  30 value 88.464828
iter  40 value 87.329276
iter  50 value 85.227459
iter  60 value 84.243542
iter  70 value 83.631512
iter  80 value 83.390115
iter  90 value 83.318075
iter 100 value 83.224041
final  value 83.224041 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.214077 
iter  10 value 94.491154
iter  20 value 94.199659
iter  30 value 93.850357
iter  40 value 90.716957
iter  50 value 85.469993
iter  60 value 84.127708
iter  70 value 83.665471
iter  80 value 83.460385
iter  90 value 83.220162
iter 100 value 83.117589
final  value 83.117589 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.234269 
iter  10 value 94.521404
iter  20 value 91.147964
iter  30 value 88.444268
iter  40 value 88.134774
iter  50 value 86.493442
iter  60 value 85.993289
iter  70 value 85.331156
iter  80 value 85.133900
iter  90 value 84.876464
iter 100 value 84.578080
final  value 84.578080 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.120136 
iter  10 value 89.008232
iter  20 value 86.433304
iter  30 value 84.957195
iter  40 value 84.189694
iter  50 value 83.775047
iter  60 value 83.739520
iter  70 value 83.454069
iter  80 value 83.335884
iter  90 value 83.132733
iter 100 value 83.082246
final  value 83.082246 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.095538 
iter  10 value 94.448376
iter  20 value 93.082724
iter  30 value 91.622204
iter  40 value 88.186787
iter  50 value 87.390945
iter  60 value 84.732655
iter  70 value 83.755165
iter  80 value 83.165522
iter  90 value 83.055588
iter 100 value 83.010060
final  value 83.010060 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.471985 
iter  10 value 95.072784
iter  20 value 93.594750
iter  30 value 91.525479
iter  40 value 88.826091
iter  50 value 87.400600
iter  60 value 86.429936
iter  70 value 86.328918
iter  80 value 86.197056
iter  90 value 86.092487
iter 100 value 85.378218
final  value 85.378218 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.002086 
iter  10 value 94.468346
iter  20 value 94.221789
iter  30 value 93.588441
iter  40 value 89.371370
iter  50 value 88.283311
iter  60 value 87.783235
iter  70 value 85.124257
iter  80 value 84.319743
iter  90 value 84.032979
iter 100 value 83.955066
final  value 83.955066 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.656368 
iter  10 value 93.345878
iter  20 value 91.207809
iter  30 value 87.106527
iter  40 value 85.585204
iter  50 value 85.256305
iter  60 value 84.994204
iter  70 value 84.791990
iter  80 value 84.174130
iter  90 value 83.471139
iter 100 value 82.796744
final  value 82.796744 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.019982 
iter  10 value 94.943810
iter  20 value 91.112656
iter  30 value 86.535518
iter  40 value 84.221836
iter  50 value 83.013514
iter  60 value 82.966764
iter  70 value 82.870532
iter  80 value 82.827382
iter  90 value 82.710728
iter 100 value 82.416118
final  value 82.416118 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.957814 
final  value 94.468443 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.476843 
final  value 94.485664 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.226905 
final  value 94.485893 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.348549 
final  value 94.485864 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.190572 
final  value 94.485690 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.561983 
iter  10 value 94.471585
iter  20 value 90.808045
iter  30 value 89.858053
iter  40 value 89.418882
iter  50 value 89.412082
iter  60 value 89.389322
iter  70 value 87.971198
final  value 87.919707 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.478187 
iter  10 value 94.489689
iter  20 value 94.421883
iter  30 value 89.423510
iter  40 value 87.650007
iter  50 value 87.587848
iter  60 value 87.582409
final  value 87.581908 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.939583 
iter  10 value 94.471856
iter  20 value 93.638983
iter  30 value 89.412860
iter  30 value 89.412859
iter  30 value 89.412859
final  value 89.412859 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.107198 
iter  10 value 94.471352
iter  20 value 94.391159
iter  30 value 87.301477
iter  40 value 86.506665
iter  50 value 86.331526
iter  60 value 86.180836
final  value 86.180829 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.808200 
iter  10 value 94.488080
final  value 94.484740 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.472077 
iter  10 value 94.491503
iter  20 value 94.419617
iter  30 value 93.854935
iter  40 value 93.826485
final  value 93.826282 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.839796 
iter  10 value 94.491797
iter  20 value 94.479977
iter  30 value 91.080647
iter  40 value 90.064153
iter  50 value 87.654192
iter  60 value 87.646113
iter  70 value 87.598450
iter  80 value 86.894183
iter  90 value 83.918297
iter 100 value 83.340460
final  value 83.340460 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.930532 
iter  10 value 94.491399
iter  20 value 94.484225
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.665546 
iter  10 value 93.928928
iter  20 value 92.011900
iter  30 value 91.833123
iter  40 value 91.783871
iter  50 value 91.447441
iter  60 value 91.402413
iter  70 value 91.400988
iter  80 value 91.218127
iter  90 value 86.254677
iter 100 value 86.170578
final  value 86.170578 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 159.458070 
iter  10 value 94.480591
iter  20 value 93.225249
iter  30 value 88.892109
iter  40 value 88.695823
iter  50 value 88.650567
iter  60 value 88.626467
iter  70 value 88.605859
iter  80 value 88.604688
iter  90 value 88.604320
iter 100 value 88.603604
final  value 88.603604 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.106649 
iter  10 value 90.088387
iter  20 value 85.391983
final  value 85.357733 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.730545 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.273197 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.755868 
final  value 94.423529 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.987886 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.680663 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.701180 
iter  10 value 94.597763
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 131.496158 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.362766 
iter  10 value 94.425347
iter  20 value 94.423553
iter  20 value 94.423553
final  value 94.423549 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.809500 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.333787 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 126.395435 
iter  10 value 94.584468
iter  20 value 94.469881
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.554623 
iter  10 value 86.934443
iter  20 value 86.886962
final  value 86.886850 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.404889 
iter  10 value 91.920796
iter  20 value 85.991496
iter  30 value 85.919344
iter  40 value 85.911266
final  value 85.911215 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.820781 
iter  10 value 94.423984
iter  20 value 94.423532
final  value 94.423530 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.831448 
iter  10 value 94.629457
iter  20 value 94.488585
iter  30 value 88.640955
iter  40 value 84.345222
iter  50 value 83.550377
iter  60 value 83.135998
iter  70 value 82.303359
iter  80 value 80.963239
iter  90 value 80.397584
iter 100 value 80.393734
final  value 80.393734 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.956127 
iter  10 value 94.486979
iter  20 value 94.175230
iter  30 value 85.200494
iter  40 value 84.005868
iter  50 value 83.513760
iter  60 value 83.406245
iter  70 value 83.081979
iter  80 value 82.962968
iter  90 value 82.366300
iter 100 value 81.794678
final  value 81.794678 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.290939 
iter  10 value 94.443454
iter  20 value 91.651708
iter  30 value 86.487805
iter  40 value 83.369220
iter  50 value 83.130194
iter  60 value 82.781508
iter  70 value 82.733429
iter  80 value 82.342206
iter  90 value 82.238777
iter 100 value 80.978296
final  value 80.978296 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.446332 
iter  10 value 94.588231
iter  20 value 94.487133
iter  30 value 93.843399
iter  40 value 92.649980
iter  50 value 88.225454
iter  60 value 85.900248
iter  70 value 84.293071
iter  80 value 82.595280
iter  90 value 82.272422
iter 100 value 82.241252
final  value 82.241252 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.091143 
iter  10 value 94.488010
iter  20 value 94.472528
iter  30 value 90.453046
iter  40 value 87.099750
iter  50 value 86.638557
iter  60 value 86.497538
iter  70 value 84.748559
iter  80 value 83.135832
iter  90 value 82.772208
final  value 82.769179 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.639842 
iter  10 value 92.662767
iter  20 value 86.893445
iter  30 value 85.959647
iter  40 value 83.286530
iter  50 value 81.972285
iter  60 value 81.483283
iter  70 value 81.218466
iter  80 value 80.424646
iter  90 value 79.416337
iter 100 value 79.161308
final  value 79.161308 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.820959 
iter  10 value 94.536557
iter  20 value 85.954258
iter  30 value 84.075388
iter  40 value 81.910357
iter  50 value 80.801561
iter  60 value 80.344149
iter  70 value 79.947309
iter  80 value 79.584319
iter  90 value 79.367535
iter 100 value 79.174003
final  value 79.174003 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.121216 
iter  10 value 95.461824
iter  20 value 91.496340
iter  30 value 89.582898
iter  40 value 83.829829
iter  50 value 83.043299
iter  60 value 82.404110
iter  70 value 82.060761
iter  80 value 81.598056
iter  90 value 81.328541
iter 100 value 80.063511
final  value 80.063511 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.640791 
iter  10 value 94.518265
iter  20 value 92.904022
iter  30 value 86.289866
iter  40 value 84.148600
iter  50 value 82.058796
iter  60 value 81.117000
iter  70 value 80.817924
iter  80 value 80.633357
iter  90 value 80.442419
iter 100 value 80.206958
final  value 80.206958 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.292724 
iter  10 value 94.467049
iter  20 value 88.912726
iter  30 value 85.690976
iter  40 value 85.273282
iter  50 value 84.673198
iter  60 value 81.054063
iter  70 value 80.435888
iter  80 value 80.089652
iter  90 value 79.436704
iter 100 value 79.160858
final  value 79.160858 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.043036 
iter  10 value 93.853131
iter  20 value 90.528087
iter  30 value 83.550535
iter  40 value 82.979083
iter  50 value 81.388188
iter  60 value 80.694304
iter  70 value 80.016685
iter  80 value 79.743067
iter  90 value 79.489143
iter 100 value 79.334716
final  value 79.334716 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.428065 
iter  10 value 94.718718
iter  20 value 89.720849
iter  30 value 87.045219
iter  40 value 83.137447
iter  50 value 81.827053
iter  60 value 80.432262
iter  70 value 80.301961
iter  80 value 80.202449
iter  90 value 80.060429
iter 100 value 79.685096
final  value 79.685096 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 141.383839 
iter  10 value 94.514931
iter  20 value 92.668539
iter  30 value 86.732715
iter  40 value 85.884565
iter  50 value 84.208187
iter  60 value 81.818250
iter  70 value 79.927484
iter  80 value 79.643499
iter  90 value 79.379213
iter 100 value 79.260149
final  value 79.260149 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.639242 
iter  10 value 94.056013
iter  20 value 90.276386
iter  30 value 86.738384
iter  40 value 84.791504
iter  50 value 81.648951
iter  60 value 80.852302
iter  70 value 79.972339
iter  80 value 79.465920
iter  90 value 79.387877
iter 100 value 79.150049
final  value 79.150049 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.224044 
iter  10 value 94.740639
iter  20 value 94.555571
iter  30 value 87.213159
iter  40 value 84.106585
iter  50 value 83.416150
iter  60 value 82.694915
iter  70 value 80.034780
iter  80 value 79.730182
iter  90 value 79.490228
iter 100 value 79.446915
final  value 79.446915 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.471796 
final  value 94.485702 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.141708 
final  value 94.485977 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.828330 
final  value 94.485802 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.364298 
iter  10 value 94.486127
final  value 94.484265 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.136911 
final  value 94.485765 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.481911 
iter  10 value 94.489465
iter  20 value 94.486212
iter  30 value 87.217225
iter  40 value 86.640174
iter  50 value 86.639171
final  value 86.638830 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.674754 
iter  10 value 94.135186
iter  20 value 94.070187
iter  30 value 88.412061
iter  40 value 83.110410
iter  50 value 82.356165
iter  60 value 82.299232
iter  70 value 81.712507
iter  80 value 81.584222
iter  90 value 81.584142
iter 100 value 81.583729
final  value 81.583729 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.565101 
final  value 94.489124 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.788647 
iter  10 value 94.488872
iter  20 value 94.476167
iter  30 value 94.238655
iter  40 value 92.107493
iter  50 value 90.561981
iter  60 value 80.784591
iter  70 value 80.611881
iter  80 value 80.355220
iter  90 value 80.327232
iter 100 value 80.324985
final  value 80.324985 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.736381 
iter  10 value 94.472306
iter  20 value 94.467491
final  value 94.467414 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.322004 
iter  10 value 89.429588
iter  20 value 88.389238
iter  30 value 88.385879
iter  40 value 83.582890
iter  50 value 83.394946
iter  60 value 82.802593
iter  70 value 82.785092
iter  80 value 82.259505
iter  90 value 82.128690
iter 100 value 82.124763
final  value 82.124763 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.527132 
iter  10 value 94.475313
iter  20 value 90.324547
iter  30 value 89.680770
iter  40 value 87.013259
iter  50 value 86.935021
iter  60 value 85.946237
iter  70 value 83.467279
iter  80 value 83.459839
iter  90 value 83.147749
iter 100 value 83.069878
final  value 83.069878 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.678822 
iter  10 value 94.475366
iter  20 value 94.467924
iter  30 value 92.677419
iter  40 value 83.463993
iter  50 value 80.688313
iter  60 value 80.112115
iter  70 value 80.035679
iter  80 value 79.369362
iter  90 value 79.285102
iter 100 value 79.270404
final  value 79.270404 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.210768 
iter  10 value 94.492052
iter  20 value 92.701999
iter  30 value 88.469191
iter  40 value 88.468340
iter  50 value 86.842624
iter  60 value 82.483942
iter  70 value 82.482006
iter  80 value 82.477510
iter  90 value 82.474351
iter 100 value 82.472887
final  value 82.472887 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.266765 
iter  10 value 94.032431
iter  20 value 94.030723
iter  30 value 94.029935
iter  40 value 93.995727
iter  50 value 83.420400
iter  60 value 83.073410
iter  70 value 81.650103
iter  80 value 81.437426
final  value 81.436474 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.553719 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.333521 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.408878 
final  value 93.869755 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.352444 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.894390 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.282039 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.720556 
iter  10 value 93.399020
final  value 93.399016 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.468039 
iter  10 value 93.653870
iter  10 value 93.653870
iter  10 value 93.653870
final  value 93.653870 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.730564 
final  value 93.426574 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.749422 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.276251 
iter  10 value 91.824180
final  value 91.824176 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.401341 
final  value 93.836064 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.571899 
iter  10 value 93.605336
final  value 93.604520 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.656901 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.494715 
iter  10 value 87.177462
iter  20 value 85.819860
iter  30 value 85.799081
final  value 85.798885 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.121908 
iter  10 value 94.057010
iter  20 value 86.614549
iter  30 value 82.241253
iter  40 value 82.044887
iter  50 value 81.897701
final  value 81.879910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.447065 
iter  10 value 94.023700
iter  20 value 93.475450
iter  30 value 93.447420
iter  40 value 92.691272
iter  50 value 88.621648
iter  60 value 86.368297
iter  70 value 82.614783
iter  80 value 81.147084
iter  90 value 81.081651
iter 100 value 81.028292
final  value 81.028292 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 108.903920 
iter  10 value 94.054840
iter  20 value 93.488250
iter  30 value 93.453705
iter  40 value 92.522275
iter  50 value 88.085161
iter  60 value 86.252208
iter  70 value 79.717387
iter  80 value 78.792193
iter  90 value 78.479851
iter 100 value 78.427389
final  value 78.427389 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 94.595208 
iter  10 value 84.707952
iter  20 value 83.174001
iter  30 value 81.096939
iter  40 value 81.068325
iter  50 value 81.030515
iter  60 value 81.027533
final  value 81.027528 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.310713 
iter  10 value 93.937228
iter  20 value 92.692414
iter  30 value 81.648861
iter  40 value 79.801993
iter  50 value 78.887657
iter  60 value 78.605416
iter  70 value 78.135864
iter  80 value 78.078103
iter  90 value 78.054657
final  value 78.054652 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.398930 
iter  10 value 94.970202
iter  20 value 91.376341
iter  30 value 82.467847
iter  40 value 81.058692
iter  50 value 79.733376
iter  60 value 79.381885
iter  70 value 79.175550
iter  80 value 78.434430
iter  90 value 77.704122
iter 100 value 77.110287
final  value 77.110287 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.753223 
iter  10 value 93.986535
iter  20 value 87.339143
iter  30 value 86.820176
iter  40 value 85.345097
iter  50 value 81.097710
iter  60 value 80.874581
iter  70 value 80.737382
iter  80 value 80.426733
iter  90 value 80.414868
iter 100 value 80.388095
final  value 80.388095 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.028515 
iter  10 value 93.109044
iter  20 value 88.847704
iter  30 value 85.541536
iter  40 value 85.112250
iter  50 value 82.009420
iter  60 value 81.942903
iter  70 value 81.694544
iter  80 value 80.986761
iter  90 value 80.687793
iter 100 value 80.160766
final  value 80.160766 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.849649 
iter  10 value 93.937044
iter  20 value 84.168641
iter  30 value 83.672132
iter  40 value 81.861117
iter  50 value 79.934846
iter  60 value 79.262477
iter  70 value 78.222443
iter  80 value 77.431975
iter  90 value 77.364620
iter 100 value 77.326175
final  value 77.326175 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.344008 
iter  10 value 94.011355
iter  20 value 87.683533
iter  30 value 85.513622
iter  40 value 79.983231
iter  50 value 79.352426
iter  60 value 78.758738
iter  70 value 78.270828
iter  80 value 77.973446
iter  90 value 77.910851
iter 100 value 77.874934
final  value 77.874934 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.729567 
iter  10 value 93.741944
iter  20 value 85.431233
iter  30 value 84.977109
iter  40 value 83.874249
iter  50 value 83.272723
iter  60 value 83.101656
iter  70 value 82.629151
iter  80 value 82.483251
iter  90 value 81.603748
iter 100 value 79.017909
final  value 79.017909 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.832841 
iter  10 value 94.350497
iter  20 value 91.323255
iter  30 value 90.584163
iter  40 value 86.521222
iter  50 value 80.188753
iter  60 value 78.593967
iter  70 value 78.312453
iter  80 value 77.735573
iter  90 value 77.042625
iter 100 value 76.775127
final  value 76.775127 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.059116 
iter  10 value 94.681109
iter  20 value 92.750562
iter  30 value 83.554598
iter  40 value 81.501003
iter  50 value 80.338095
iter  60 value 79.782046
iter  70 value 78.919700
iter  80 value 78.727439
iter  90 value 78.534181
iter 100 value 78.255839
final  value 78.255839 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.815947 
iter  10 value 93.373266
iter  20 value 82.883758
iter  30 value 80.713434
iter  40 value 79.362274
iter  50 value 78.979447
iter  60 value 78.418651
iter  70 value 77.821222
iter  80 value 77.503976
iter  90 value 76.970897
iter 100 value 76.670973
final  value 76.670973 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.513705 
iter  10 value 94.139057
iter  20 value 93.573158
iter  30 value 90.622350
iter  40 value 85.600755
iter  50 value 84.163517
iter  60 value 79.903521
iter  70 value 78.963772
iter  80 value 78.442459
iter  90 value 77.514414
iter 100 value 77.164019
final  value 77.164019 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.340382 
final  value 94.054371 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.081517 
final  value 94.054325 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.153656 
iter  10 value 94.054693
iter  20 value 94.052979
iter  30 value 94.032268
final  value 93.654241 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.712396 
iter  10 value 86.064948
iter  20 value 82.154636
iter  30 value 82.152908
iter  40 value 82.012985
iter  50 value 81.962151
final  value 81.961808 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.403296 
final  value 94.054508 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.193860 
iter  10 value 94.057368
iter  20 value 94.053095
final  value 94.052921 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.629317 
iter  10 value 93.840981
iter  20 value 93.498963
iter  30 value 93.410512
iter  40 value 93.393806
iter  50 value 93.378124
iter  60 value 93.377654
iter  70 value 93.377564
iter  70 value 93.377563
iter  70 value 93.377563
final  value 93.377563 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.402194 
iter  10 value 93.690298
iter  20 value 93.637460
iter  30 value 93.631737
iter  40 value 83.401309
iter  50 value 81.359310
iter  60 value 81.230589
iter  70 value 81.109043
iter  80 value 81.048238
final  value 81.042135 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.387755 
iter  10 value 94.058272
iter  20 value 93.436549
iter  30 value 93.381333
final  value 93.378653 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.111138 
iter  10 value 94.055904
iter  20 value 93.899027
iter  30 value 86.116712
iter  40 value 84.074424
final  value 84.074420 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.666752 
iter  10 value 89.120619
iter  20 value 83.965979
iter  30 value 79.869265
iter  40 value 79.857485
iter  50 value 79.854146
iter  60 value 79.667753
iter  70 value 78.012549
iter  80 value 77.215250
iter  90 value 77.179424
iter 100 value 75.807060
final  value 75.807060 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.156126 
iter  10 value 93.588240
iter  20 value 89.671373
iter  30 value 86.637215
iter  40 value 86.634555
iter  50 value 86.630776
iter  60 value 85.910822
iter  70 value 84.948540
iter  80 value 80.164148
iter  90 value 76.725745
iter 100 value 76.645864
final  value 76.645864 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.645500 
iter  10 value 90.663775
iter  20 value 88.296831
iter  30 value 88.074388
iter  40 value 86.603834
iter  50 value 86.257977
iter  60 value 86.257387
iter  70 value 86.163887
iter  80 value 86.163385
iter  90 value 84.312855
iter 100 value 83.921298
final  value 83.921298 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 141.290961 
iter  10 value 84.774609
iter  20 value 81.545979
iter  30 value 81.470824
final  value 81.470349 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.385328 
iter  10 value 92.720827
iter  20 value 82.884866
iter  30 value 82.017346
iter  40 value 81.709609
final  value 81.706776 
converged
Fitting Repeat 1 

# weights:  305
initial  value 133.067670 
iter  10 value 114.494677
iter  20 value 114.423309
iter  30 value 114.418544
iter  40 value 114.319314
iter  50 value 114.315118
iter  60 value 113.350164
iter  70 value 113.342411
iter  80 value 113.309317
iter  90 value 110.340829
iter 100 value 108.335466
final  value 108.335466 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 135.001643 
iter  10 value 117.895125
iter  20 value 117.886626
iter  30 value 117.203734
iter  40 value 107.648190
iter  50 value 107.647137
iter  60 value 106.914970
iter  70 value 106.108558
iter  80 value 105.352635
iter  90 value 105.351738
iter 100 value 105.140092
final  value 105.140092 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.236760 
iter  10 value 115.337126
iter  20 value 115.300338
iter  30 value 114.909634
iter  40 value 114.422846
iter  50 value 114.418545
iter  60 value 114.417980
iter  60 value 114.417980
final  value 114.417980 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.537977 
iter  10 value 117.894966
iter  20 value 117.889731
iter  30 value 107.444137
final  value 107.003634 
converged
Fitting Repeat 5 

# weights:  305
initial  value 129.110092 
iter  10 value 117.554922
iter  20 value 117.552369
iter  30 value 117.356561
iter  40 value 113.756242
iter  50 value 111.708833
iter  60 value 111.659882
iter  70 value 111.659396
iter  80 value 106.126131
iter  90 value 105.775343
iter 100 value 105.773269
final  value 105.773269 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Jan 28 11:39:40 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 53.791   1.722 136.769