##############################################################################
##############################################################################
###
### 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_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    gcc (GCC) 12.2.1 20220819 (openEuler 12.2.1-14)
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
FSmethod      38.230  0.683  39.047
var_imp       37.618  0.703  38.398
corr_plot     37.931  0.271  38.285
pred_ensembel 19.082  1.012  16.924
enrichfindP    0.514  0.053  21.100
getFASTA       0.083  0.005   5.501
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

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


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

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

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

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

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

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

# weights:  103
initial  value 97.478620 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.828160 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.335800 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.970494 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.159495 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.228575 
iter  10 value 90.185757
iter  20 value 89.290927
final  value 89.234725 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.901551 
final  value 94.052435 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.453440 
iter  10 value 93.285860
iter  20 value 93.283340
final  value 93.283334 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.796558 
iter  10 value 92.873173
iter  20 value 82.075624
iter  30 value 81.280900
iter  40 value 81.279022
final  value 81.279018 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.459371 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.517735 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.006991 
iter  10 value 94.162315
iter  20 value 94.144499
final  value 94.144481 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.027589 
iter  10 value 93.272729
iter  20 value 93.148416
iter  30 value 92.950677
final  value 92.949136 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.522571 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.694005 
iter  10 value 92.647746
final  value 92.613874 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.934856 
iter  10 value 94.484105
iter  20 value 84.106651
iter  30 value 82.552791
iter  40 value 81.324651
iter  50 value 80.895658
iter  60 value 80.638708
iter  70 value 80.570483
iter  80 value 80.565330
final  value 80.565327 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.814922 
iter  10 value 93.775560
iter  20 value 85.861603
iter  30 value 85.469663
iter  40 value 85.018065
iter  50 value 82.205758
iter  60 value 81.565095
iter  70 value 81.034828
iter  80 value 80.748243
iter  90 value 80.608416
iter 100 value 80.565334
final  value 80.565334 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.046030 
iter  10 value 94.490109
iter  20 value 93.925465
iter  30 value 83.937603
iter  40 value 83.249921
iter  50 value 82.672230
iter  60 value 82.633618
final  value 82.633609 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.116450 
iter  10 value 94.590218
iter  20 value 94.139053
iter  30 value 92.942194
iter  40 value 83.406240
iter  50 value 82.676735
iter  60 value 82.642774
iter  70 value 82.628393
iter  70 value 82.628392
iter  70 value 82.628392
final  value 82.628392 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.375720 
iter  10 value 93.338579
iter  20 value 88.031008
iter  30 value 87.257428
iter  40 value 83.335738
iter  50 value 83.299485
iter  60 value 82.894790
iter  70 value 81.437972
iter  80 value 80.405188
iter  90 value 80.373404
iter 100 value 80.348606
final  value 80.348606 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 133.200634 
iter  10 value 94.484634
iter  20 value 93.732724
iter  30 value 91.212846
iter  40 value 83.870027
iter  50 value 83.676184
iter  60 value 83.000252
iter  70 value 81.873839
iter  80 value 81.690333
iter  90 value 81.350988
iter 100 value 81.257308
final  value 81.257308 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.297486 
iter  10 value 94.507362
iter  20 value 84.191372
iter  30 value 82.422613
iter  40 value 80.575913
iter  50 value 80.378492
iter  60 value 80.342684
iter  70 value 80.274301
iter  80 value 80.096081
iter  90 value 79.859994
iter 100 value 79.581546
final  value 79.581546 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.086496 
iter  10 value 94.983256
iter  20 value 94.026474
iter  30 value 87.232592
iter  40 value 85.464601
iter  50 value 84.927634
iter  60 value 82.802255
iter  70 value 81.874199
iter  80 value 81.796926
iter  90 value 81.605410
iter 100 value 80.553651
final  value 80.553651 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.275916 
iter  10 value 94.429207
iter  20 value 92.182819
iter  30 value 84.781075
iter  40 value 83.398386
iter  50 value 83.360721
iter  60 value 82.303145
iter  70 value 81.079429
iter  80 value 80.596533
iter  90 value 79.939479
iter 100 value 79.623906
final  value 79.623906 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.033918 
iter  10 value 93.410324
iter  20 value 86.520249
iter  30 value 82.915254
iter  40 value 82.822643
iter  50 value 82.366411
iter  60 value 81.218406
iter  70 value 80.493121
iter  80 value 80.453024
iter  90 value 80.441205
iter 100 value 80.422678
final  value 80.422678 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.742904 
iter  10 value 94.570352
iter  20 value 83.600288
iter  30 value 82.600980
iter  40 value 81.432479
iter  50 value 80.760241
iter  60 value 79.868571
iter  70 value 79.639267
iter  80 value 79.495957
iter  90 value 79.408237
iter 100 value 79.365879
final  value 79.365879 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.240019 
iter  10 value 84.951577
iter  20 value 82.328778
iter  30 value 81.627143
iter  40 value 80.387102
iter  50 value 80.094645
iter  60 value 79.976843
iter  70 value 79.701988
iter  80 value 79.607488
iter  90 value 79.400479
iter 100 value 79.248698
final  value 79.248698 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.525654 
iter  10 value 94.415554
iter  20 value 92.193973
iter  30 value 91.783565
iter  40 value 91.387151
iter  50 value 90.288395
iter  60 value 89.957861
iter  70 value 84.009874
iter  80 value 81.976046
iter  90 value 80.933422
iter 100 value 80.652265
final  value 80.652265 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.386434 
iter  10 value 95.090425
iter  20 value 94.019051
iter  30 value 92.620454
iter  40 value 88.810019
iter  50 value 86.850186
iter  60 value 84.201527
iter  70 value 82.473046
iter  80 value 81.027523
iter  90 value 80.627401
iter 100 value 80.125874
final  value 80.125874 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.378800 
iter  10 value 95.160854
iter  20 value 87.736038
iter  30 value 85.181152
iter  40 value 81.471254
iter  50 value 80.999311
iter  60 value 80.894795
iter  70 value 80.052446
iter  80 value 79.366372
iter  90 value 78.864870
iter 100 value 78.717339
final  value 78.717339 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.281098 
final  value 94.485804 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.097700 
iter  10 value 94.486160
iter  20 value 93.679910
iter  30 value 93.661273
iter  40 value 93.659598
iter  50 value 93.658698
iter  60 value 90.245588
iter  70 value 84.416946
iter  80 value 84.403042
iter  90 value 84.402927
iter  90 value 84.402927
iter 100 value 84.402851
final  value 84.402851 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.618924 
final  value 94.054274 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.896721 
final  value 94.486009 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.880622 
final  value 94.485907 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.024483 
iter  10 value 89.996810
iter  20 value 89.993560
iter  30 value 89.988378
iter  40 value 89.985687
iter  50 value 89.979667
iter  60 value 89.092482
iter  70 value 88.577216
iter  80 value 88.567377
final  value 88.567371 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.586258 
iter  10 value 94.488805
iter  20 value 94.481975
iter  30 value 84.223167
iter  40 value 79.864082
iter  50 value 79.860958
iter  60 value 79.835349
iter  70 value 79.319103
iter  80 value 79.230889
iter  90 value 79.230233
iter 100 value 79.230006
final  value 79.230006 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.923356 
iter  10 value 94.486524
iter  20 value 83.718605
iter  30 value 82.561883
iter  40 value 82.556252
iter  50 value 82.500492
iter  60 value 81.223574
final  value 81.223363 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.071274 
iter  10 value 94.488063
iter  20 value 94.473200
iter  30 value 85.205143
iter  40 value 85.171564
iter  50 value 85.169933
iter  60 value 85.037576
iter  70 value 85.021794
iter  80 value 85.021316
iter  90 value 84.771240
iter 100 value 84.693139
final  value 84.693139 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.600098 
iter  10 value 94.280454
iter  20 value 94.276375
iter  30 value 93.774349
iter  40 value 87.186341
iter  50 value 85.801035
iter  60 value 81.479646
iter  70 value 80.074339
iter  80 value 79.427025
iter  90 value 79.420627
iter 100 value 79.287464
final  value 79.287464 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.088119 
iter  10 value 88.594419
iter  20 value 83.382714
iter  30 value 81.839599
iter  40 value 81.614601
iter  50 value 81.482607
iter  60 value 81.473091
iter  70 value 79.256392
iter  80 value 78.733113
iter  90 value 78.731211
iter 100 value 78.729594
final  value 78.729594 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.317707 
iter  10 value 93.920315
iter  20 value 93.895585
iter  30 value 93.650701
iter  40 value 93.641103
iter  50 value 93.640992
iter  60 value 93.640809
final  value 93.640794 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.478818 
iter  10 value 94.491282
iter  20 value 94.317573
iter  30 value 91.337379
iter  40 value 90.790833
iter  50 value 90.790045
iter  60 value 90.786510
iter  70 value 90.786435
final  value 90.786393 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.090448 
iter  10 value 93.011869
iter  20 value 88.237628
iter  30 value 86.130394
iter  40 value 86.098155
iter  50 value 84.764127
iter  60 value 84.750564
iter  70 value 84.750120
iter  80 value 84.748610
final  value 84.748580 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.637396 
iter  10 value 94.492102
iter  20 value 94.355694
final  value 94.355686 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.864808 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.607866 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.439873 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.874699 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.469395 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.869845 
iter  10 value 89.605303
iter  20 value 88.845203
final  value 88.315362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.434339 
final  value 94.476471 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.079522 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.912608 
final  value 94.323810 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.495910 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.572691 
final  value 94.365462 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.333209 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.488599 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.578151 
iter  10 value 94.467400
final  value 94.467392 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.542343 
final  value 94.399733 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.324865 
iter  10 value 94.455455
iter  20 value 90.522847
iter  30 value 88.592038
iter  40 value 86.113686
iter  50 value 85.435102
iter  60 value 85.336542
final  value 85.336537 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.066356 
iter  10 value 94.488997
iter  20 value 93.368687
iter  30 value 89.086866
iter  40 value 88.302971
iter  50 value 87.752919
iter  60 value 86.279265
iter  70 value 85.317722
iter  80 value 84.449003
iter  90 value 84.388163
final  value 84.381490 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.893853 
iter  10 value 90.069438
iter  20 value 87.477344
iter  30 value 87.043609
iter  40 value 86.442289
iter  50 value 86.088042
iter  60 value 85.858517
iter  70 value 85.633333
iter  80 value 83.438024
iter  90 value 82.862075
iter 100 value 82.564730
final  value 82.564730 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.265356 
iter  10 value 94.489893
iter  20 value 93.706165
iter  30 value 86.751453
iter  40 value 85.043734
iter  50 value 84.623863
iter  60 value 84.594775
final  value 84.592027 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.518616 
iter  10 value 94.510061
iter  20 value 94.482227
iter  30 value 92.637322
iter  40 value 88.379523
iter  50 value 87.191121
iter  60 value 85.482428
iter  70 value 84.528645
iter  80 value 83.528662
iter  90 value 83.436965
final  value 83.436633 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.571601 
iter  10 value 94.652708
iter  20 value 90.392149
iter  30 value 86.189103
iter  40 value 84.238873
iter  50 value 83.958945
iter  60 value 83.934921
iter  70 value 83.858512
iter  80 value 83.253451
iter  90 value 82.729346
iter 100 value 82.297245
final  value 82.297245 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.908949 
iter  10 value 94.980408
iter  20 value 92.002467
iter  30 value 89.478422
iter  40 value 85.663669
iter  50 value 84.960669
iter  60 value 84.341301
iter  70 value 84.219834
iter  80 value 84.166525
iter  90 value 84.120404
iter 100 value 83.433858
final  value 83.433858 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.874842 
iter  10 value 94.414326
iter  20 value 91.265601
iter  30 value 86.910466
iter  40 value 84.390084
iter  50 value 83.453009
iter  60 value 82.192094
iter  70 value 81.903784
iter  80 value 81.666316
iter  90 value 81.279981
iter 100 value 81.003765
final  value 81.003765 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 126.611058 
iter  10 value 93.383167
iter  20 value 88.574100
iter  30 value 88.347766
iter  40 value 88.308259
iter  50 value 88.153388
iter  60 value 84.588353
iter  70 value 84.349004
iter  80 value 84.033075
iter  90 value 83.195451
iter 100 value 82.882387
final  value 82.882387 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.680979 
iter  10 value 94.315291
iter  20 value 92.388981
iter  30 value 91.865825
iter  40 value 87.524648
iter  50 value 83.938791
iter  60 value 82.082984
iter  70 value 81.072393
iter  80 value 80.961766
iter  90 value 80.918712
iter 100 value 80.860794
final  value 80.860794 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.982844 
iter  10 value 94.519288
iter  20 value 88.157701
iter  30 value 87.615871
iter  40 value 84.639287
iter  50 value 83.486266
iter  60 value 82.733319
iter  70 value 82.034131
iter  80 value 81.478714
iter  90 value 81.098962
iter 100 value 80.936118
final  value 80.936118 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.602524 
iter  10 value 94.492522
iter  20 value 89.487255
iter  30 value 86.883595
iter  40 value 85.839516
iter  50 value 84.807871
iter  60 value 84.353813
iter  70 value 84.014134
iter  80 value 82.612287
iter  90 value 81.741583
iter 100 value 81.317218
final  value 81.317218 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 137.287620 
iter  10 value 94.165349
iter  20 value 86.459643
iter  30 value 84.963156
iter  40 value 82.598478
iter  50 value 81.595151
iter  60 value 81.450363
iter  70 value 81.357660
iter  80 value 81.285052
iter  90 value 81.259728
iter 100 value 81.238629
final  value 81.238629 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.572455 
iter  10 value 94.489320
iter  20 value 93.529466
iter  30 value 92.561704
iter  40 value 92.260873
iter  50 value 89.860443
iter  60 value 87.355920
iter  70 value 83.924973
iter  80 value 81.910923
iter  90 value 81.649367
iter 100 value 81.310684
final  value 81.310684 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 137.264521 
iter  10 value 94.900058
iter  20 value 93.493899
iter  30 value 89.412588
iter  40 value 87.388966
iter  50 value 86.417023
iter  60 value 83.906302
iter  70 value 82.702697
iter  80 value 82.119007
iter  90 value 81.943800
iter 100 value 81.622122
final  value 81.622122 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.576025 
final  value 94.485906 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.189866 
final  value 94.485766 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.993422 
final  value 94.485881 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.458416 
final  value 94.485670 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.619591 
final  value 94.485843 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.084184 
iter  10 value 94.404884
iter  20 value 94.336259
iter  30 value 87.092232
iter  40 value 87.003761
iter  50 value 86.469151
iter  60 value 86.342220
iter  70 value 86.331409
iter  80 value 86.331216
iter  90 value 86.330264
final  value 86.329871 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.752591 
iter  10 value 94.488904
iter  20 value 94.337454
iter  30 value 91.396379
iter  40 value 88.284927
iter  50 value 88.212704
iter  60 value 87.561157
iter  70 value 86.273461
iter  80 value 86.227949
iter  90 value 86.157274
iter 100 value 85.960967
final  value 85.960967 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.525135 
iter  10 value 94.478874
iter  20 value 89.189168
iter  30 value 88.929257
iter  40 value 88.249671
iter  50 value 87.537420
iter  60 value 86.738022
iter  70 value 84.760390
iter  80 value 84.284450
iter  90 value 84.241098
iter 100 value 81.954934
final  value 81.954934 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.386929 
iter  10 value 94.491597
iter  20 value 94.486309
iter  30 value 94.428501
iter  40 value 87.307175
iter  50 value 87.169041
final  value 87.137128 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.123504 
iter  10 value 94.488754
iter  20 value 94.484248
iter  30 value 94.469627
iter  40 value 92.360939
iter  50 value 92.006494
iter  60 value 91.912266
iter  70 value 91.910734
final  value 91.909489 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.684563 
iter  10 value 93.330516
iter  20 value 88.793035
iter  30 value 87.753735
iter  40 value 86.737391
iter  50 value 86.722808
iter  60 value 86.719465
iter  70 value 86.715843
iter  80 value 86.159161
iter  90 value 82.159049
iter 100 value 81.269216
final  value 81.269216 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.695383 
iter  10 value 94.492250
iter  20 value 94.472571
iter  30 value 89.172547
iter  40 value 83.698195
iter  50 value 82.958915
iter  60 value 82.871433
iter  70 value 82.855116
final  value 82.854896 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.911236 
iter  10 value 94.491964
iter  20 value 94.447670
iter  30 value 86.333165
iter  40 value 86.328138
iter  50 value 86.326985
final  value 86.326830 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.917104 
iter  10 value 94.492320
iter  20 value 94.484291
iter  30 value 92.137440
iter  40 value 83.854643
iter  50 value 82.294919
iter  60 value 82.116164
iter  70 value 82.100705
iter  80 value 82.099357
iter  90 value 81.944617
iter 100 value 81.647366
final  value 81.647366 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.321671 
iter  10 value 94.491846
iter  20 value 94.484074
iter  30 value 94.063147
iter  40 value 88.592477
iter  50 value 88.569452
iter  60 value 88.568112
iter  70 value 88.549427
iter  80 value 88.445720
iter  90 value 88.040278
iter 100 value 86.763047
final  value 86.763047 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 117.276292 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.079959 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.145496 
final  value 93.482758 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.180231 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.173330 
final  value 93.371808 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.612700 
iter  10 value 91.556094
final  value 91.374293 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.002330 
final  value 93.810010 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.133749 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.556814 
iter  10 value 93.672981
final  value 93.672973 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.936143 
iter  10 value 92.603369
iter  20 value 92.310479
iter  20 value 92.310478
iter  20 value 92.310478
final  value 92.310478 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.507237 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.306593 
final  value 93.810010 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.815406 
iter  10 value 93.701870
final  value 93.622234 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.800572 
iter  10 value 93.673026
final  value 93.672973 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.346831 
final  value 93.672973 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.265871 
iter  10 value 93.950214
iter  20 value 88.101093
iter  30 value 86.571712
iter  40 value 85.092265
iter  50 value 84.560295
iter  60 value 84.362243
final  value 84.360551 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.537475 
iter  10 value 94.026860
iter  20 value 93.566211
iter  30 value 93.535985
final  value 93.535957 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.860667 
iter  10 value 94.057318
iter  20 value 92.237413
iter  30 value 86.830682
iter  40 value 84.685793
iter  50 value 84.370312
iter  60 value 84.299502
iter  70 value 84.293328
iter  70 value 84.293328
iter  70 value 84.293328
final  value 84.293328 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.712856 
iter  10 value 94.028563
iter  20 value 85.691809
iter  30 value 84.568697
iter  40 value 84.105178
iter  50 value 82.140251
iter  60 value 81.780529
iter  70 value 81.464326
iter  80 value 81.385718
iter  90 value 81.343788
final  value 81.343769 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.794217 
iter  10 value 94.056375
iter  20 value 93.823376
iter  30 value 93.788787
iter  40 value 93.547046
iter  50 value 93.169607
iter  60 value 93.156320
iter  70 value 93.156014
iter  80 value 93.155859
final  value 93.155779 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.451462 
iter  10 value 93.350461
iter  20 value 88.961987
iter  30 value 88.189191
iter  40 value 87.763397
iter  50 value 85.966856
iter  60 value 85.272955
iter  70 value 83.131898
iter  80 value 81.526784
iter  90 value 80.966263
iter 100 value 79.531355
final  value 79.531355 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.949522 
iter  10 value 94.032796
iter  20 value 88.645683
iter  30 value 87.738224
iter  40 value 85.287127
iter  50 value 84.837422
iter  60 value 83.527502
iter  70 value 82.346836
iter  80 value 82.131811
iter  90 value 81.812240
iter 100 value 81.588906
final  value 81.588906 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.833110 
iter  10 value 94.008999
iter  20 value 93.484134
iter  30 value 93.394101
iter  40 value 89.755451
iter  50 value 88.007515
iter  60 value 85.565569
iter  70 value 83.373320
iter  80 value 82.898791
iter  90 value 80.176035
iter 100 value 79.636604
final  value 79.636604 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.222564 
iter  10 value 94.098894
iter  20 value 93.484658
iter  30 value 92.026782
iter  40 value 90.172842
iter  50 value 88.282332
iter  60 value 85.233922
iter  70 value 83.417488
iter  80 value 80.617193
iter  90 value 79.976418
iter 100 value 79.572182
final  value 79.572182 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.104583 
iter  10 value 88.005178
iter  20 value 86.829146
iter  30 value 86.459418
iter  40 value 86.341962
iter  50 value 86.323615
iter  60 value 86.099505
iter  70 value 84.585935
iter  80 value 82.576539
iter  90 value 80.802380
iter 100 value 80.207765
final  value 80.207765 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 130.638029 
iter  10 value 95.435328
iter  20 value 94.243332
iter  30 value 93.934315
iter  40 value 90.608658
iter  50 value 87.834179
iter  60 value 86.724739
iter  70 value 85.980926
iter  80 value 83.025515
iter  90 value 80.323734
iter 100 value 79.123027
final  value 79.123027 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.257298 
iter  10 value 98.024395
iter  20 value 96.502077
iter  30 value 94.991292
iter  40 value 87.565981
iter  50 value 84.081708
iter  60 value 82.452429
iter  70 value 81.979154
iter  80 value 81.069211
iter  90 value 80.319669
iter 100 value 80.102482
final  value 80.102482 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.556623 
iter  10 value 93.898091
iter  20 value 92.145488
iter  30 value 84.976307
iter  40 value 83.772621
iter  50 value 82.564474
iter  60 value 80.896043
iter  70 value 80.304419
iter  80 value 80.067771
iter  90 value 79.718825
iter 100 value 79.617504
final  value 79.617504 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.893926 
iter  10 value 93.745298
iter  20 value 88.463416
iter  30 value 86.646401
iter  40 value 86.218394
iter  50 value 85.478182
iter  60 value 83.917123
iter  70 value 82.450703
iter  80 value 80.505202
iter  90 value 79.062588
iter 100 value 78.391617
final  value 78.391617 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.494202 
iter  10 value 93.961172
iter  20 value 93.800427
iter  30 value 93.526404
iter  40 value 85.853037
iter  50 value 84.789848
iter  60 value 84.600035
iter  70 value 84.195635
iter  80 value 82.535375
iter  90 value 80.177877
iter 100 value 79.626990
final  value 79.626990 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.555842 
iter  10 value 94.054416
iter  20 value 94.050932
final  value 93.673225 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.270837 
iter  10 value 93.513346
final  value 93.484367 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.362820 
final  value 94.054658 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.488950 
final  value 93.811613 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.259448 
final  value 93.484394 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.372694 
iter  10 value 93.033525
iter  20 value 93.032988
iter  30 value 91.688785
iter  40 value 84.776363
iter  50 value 83.162598
iter  60 value 82.814759
iter  70 value 82.743192
iter  80 value 82.731076
iter  90 value 79.989980
iter 100 value 78.943003
final  value 78.943003 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.581022 
iter  10 value 93.035827
iter  20 value 93.022259
iter  30 value 93.020374
iter  40 value 93.019925
iter  50 value 93.018893
iter  60 value 93.017415
iter  70 value 92.688439
final  value 92.683480 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.953655 
iter  10 value 93.678594
iter  20 value 93.677234
iter  30 value 93.455783
iter  40 value 92.860859
iter  50 value 87.465337
iter  60 value 84.873986
iter  70 value 84.864244
iter  80 value 84.812663
iter  90 value 84.810156
final  value 84.806473 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.298107 
iter  10 value 93.678083
iter  20 value 93.675110
iter  30 value 86.879431
iter  40 value 86.788219
iter  50 value 86.787925
iter  60 value 86.787865
iter  70 value 86.787190
iter  80 value 86.302040
iter  90 value 85.173977
iter 100 value 81.808185
final  value 81.808185 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.988449 
iter  10 value 92.107234
iter  20 value 84.119661
iter  30 value 84.116880
iter  40 value 84.115046
iter  50 value 84.114949
iter  60 value 84.059833
final  value 84.059267 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.674832 
iter  10 value 94.060689
iter  20 value 93.905497
iter  30 value 87.013903
iter  40 value 86.361610
iter  50 value 85.894047
iter  60 value 85.886058
iter  70 value 83.374599
iter  80 value 82.613347
iter  90 value 82.609998
final  value 82.609001 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.998269 
iter  10 value 93.540894
iter  20 value 93.489924
iter  30 value 93.488779
iter  40 value 93.485805
iter  50 value 93.483874
iter  60 value 93.483677
iter  70 value 93.483134
final  value 93.483116 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.184987 
iter  10 value 93.681123
iter  20 value 93.677157
iter  30 value 93.408635
iter  40 value 93.408297
iter  50 value 93.407733
final  value 93.407628 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.632651 
iter  10 value 94.060638
iter  20 value 94.053200
iter  30 value 94.035837
iter  40 value 84.599453
iter  50 value 84.163482
iter  60 value 84.128521
iter  70 value 84.068541
iter  80 value 84.062690
iter  90 value 84.061499
iter 100 value 83.982966
final  value 83.982966 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.429867 
iter  10 value 90.543915
iter  20 value 90.411830
iter  30 value 90.397500
iter  40 value 86.854883
iter  50 value 86.828274
iter  60 value 86.656138
iter  70 value 85.772417
iter  80 value 85.405030
iter  90 value 85.300413
final  value 85.300078 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.551184 
iter  10 value 92.106136
final  value 92.030026 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.011411 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.748270 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.462529 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.292431 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.798951 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 129.235196 
iter  10 value 88.591544
iter  20 value 86.876778
iter  30 value 86.864376
final  value 86.864309 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.821673 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.055355 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.796538 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.026688 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.539406 
iter  10 value 93.207161
iter  20 value 93.205835
final  value 93.205815 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.708601 
iter  10 value 93.638947
final  value 93.621187 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.516333 
iter  10 value 94.325970
final  value 94.325945 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.586897 
iter  10 value 93.281932
iter  20 value 92.933488
final  value 92.933431 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.179456 
iter  10 value 94.376819
iter  20 value 86.637093
iter  30 value 86.413972
iter  40 value 84.736728
iter  50 value 84.371750
iter  60 value 83.746186
iter  70 value 83.577894
final  value 83.577693 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.826156 
iter  10 value 94.483216
iter  20 value 90.634433
iter  30 value 90.027798
iter  40 value 87.800116
iter  50 value 86.071148
iter  60 value 82.626595
iter  70 value 80.984170
iter  80 value 80.659506
iter  90 value 80.336647
iter 100 value 80.328048
final  value 80.328048 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.363740 
iter  10 value 94.496526
iter  20 value 89.237533
iter  30 value 85.410354
iter  40 value 85.080077
iter  50 value 84.568277
iter  60 value 82.187024
iter  70 value 81.713285
iter  80 value 81.679664
final  value 81.679114 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.918474 
iter  10 value 92.857612
iter  20 value 91.847013
iter  30 value 91.826238
iter  40 value 91.825035
iter  50 value 91.396102
iter  60 value 86.144127
iter  70 value 84.875849
iter  80 value 84.373657
iter  90 value 84.085947
iter 100 value 83.629428
final  value 83.629428 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.313809 
iter  10 value 94.060708
iter  20 value 91.144438
iter  30 value 84.345323
iter  40 value 83.658814
iter  50 value 81.657411
iter  60 value 80.613260
iter  70 value 80.514937
iter  80 value 80.446046
iter  90 value 80.376800
iter 100 value 80.328053
final  value 80.328053 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.627047 
iter  10 value 94.875214
iter  20 value 94.494232
iter  30 value 94.282246
iter  40 value 86.796890
iter  50 value 85.875420
iter  60 value 83.112717
iter  70 value 79.967648
iter  80 value 79.603356
iter  90 value 79.508637
iter 100 value 79.331222
final  value 79.331222 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.404949 
iter  10 value 94.989625
iter  20 value 92.389922
iter  30 value 85.640647
iter  40 value 82.699839
iter  50 value 81.741850
iter  60 value 80.983106
iter  70 value 80.314912
iter  80 value 79.820566
iter  90 value 79.512010
iter 100 value 79.492012
final  value 79.492012 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.815251 
iter  10 value 94.490060
iter  20 value 93.741723
iter  30 value 89.856517
iter  40 value 86.405151
iter  50 value 84.885183
iter  60 value 83.949943
iter  70 value 83.917332
iter  80 value 83.681872
iter  90 value 81.093548
iter 100 value 79.778158
final  value 79.778158 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.425530 
iter  10 value 94.692101
iter  20 value 94.504967
iter  30 value 91.535005
iter  40 value 86.389050
iter  50 value 86.113682
iter  60 value 85.714011
iter  70 value 84.015242
iter  80 value 83.556122
iter  90 value 83.287146
iter 100 value 82.824822
final  value 82.824822 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.476049 
iter  10 value 94.522061
iter  20 value 90.884813
iter  30 value 85.422556
iter  40 value 82.836120
iter  50 value 82.554565
iter  60 value 81.641398
iter  70 value 80.463460
iter  80 value 80.316269
iter  90 value 79.785128
iter 100 value 79.644048
final  value 79.644048 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.141080 
iter  10 value 94.738793
iter  20 value 91.483163
iter  30 value 84.954532
iter  40 value 83.982246
iter  50 value 82.654812
iter  60 value 80.977542
iter  70 value 80.650872
iter  80 value 80.032579
iter  90 value 79.586852
iter 100 value 79.404103
final  value 79.404103 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.239654 
iter  10 value 94.387240
iter  20 value 90.576627
iter  30 value 87.291139
iter  40 value 85.163359
iter  50 value 84.794643
iter  60 value 84.040807
iter  70 value 83.674219
iter  80 value 83.494062
iter  90 value 82.596171
iter 100 value 81.358456
final  value 81.358456 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.858678 
iter  10 value 93.825436
iter  20 value 85.486814
iter  30 value 82.020755
iter  40 value 80.131463
iter  50 value 79.952208
iter  60 value 79.382247
iter  70 value 79.094549
iter  80 value 78.981586
iter  90 value 78.790305
iter 100 value 78.606052
final  value 78.606052 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.530994 
iter  10 value 95.742361
iter  20 value 90.433903
iter  30 value 87.233179
iter  40 value 85.098908
iter  50 value 82.373143
iter  60 value 81.067357
iter  70 value 80.408775
iter  80 value 80.010250
iter  90 value 79.685647
iter 100 value 79.373120
final  value 79.373120 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.384702 
iter  10 value 94.580336
iter  20 value 89.121703
iter  30 value 88.002702
iter  40 value 87.717876
iter  50 value 86.604192
iter  60 value 83.869597
iter  70 value 81.527792
iter  80 value 80.702060
iter  90 value 80.099633
iter 100 value 79.840209
final  value 79.840209 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.343039 
iter  10 value 94.486317
final  value 94.484638 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.954208 
final  value 94.485984 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.224456 
final  value 94.485745 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.428458 
final  value 94.485838 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.476269 
iter  10 value 94.485475
iter  20 value 89.483357
iter  30 value 88.875413
iter  40 value 88.873289
final  value 88.872854 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.851522 
iter  10 value 94.488208
iter  20 value 94.450389
iter  30 value 93.816884
iter  40 value 93.810039
final  value 93.810008 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.807514 
iter  10 value 94.489955
iter  20 value 94.484766
final  value 94.484589 
converged
Fitting Repeat 3 

# weights:  305
initial  value 128.102038 
iter  10 value 94.489019
iter  20 value 94.352795
iter  30 value 90.506908
iter  40 value 87.643215
iter  50 value 85.789920
iter  60 value 85.787230
iter  70 value 84.141803
iter  80 value 83.731980
iter  90 value 83.677589
iter 100 value 83.676641
final  value 83.676641 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.297069 
iter  10 value 93.481354
iter  20 value 92.952239
iter  30 value 91.570301
iter  40 value 90.722237
iter  50 value 90.496188
iter  60 value 90.495779
iter  70 value 90.494533
final  value 90.494187 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.074175 
iter  10 value 90.203230
iter  20 value 86.152233
final  value 86.149858 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.504413 
iter  10 value 94.492346
iter  20 value 94.111323
iter  30 value 85.168428
iter  40 value 85.167908
iter  50 value 85.155467
iter  60 value 82.098864
iter  70 value 81.473793
final  value 81.473039 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.120444 
iter  10 value 94.492586
iter  20 value 94.484229
iter  30 value 94.354688
iter  30 value 94.354688
iter  30 value 94.354688
final  value 94.354688 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.828883 
iter  10 value 94.498817
iter  20 value 93.591200
iter  30 value 91.571107
iter  40 value 91.470654
iter  50 value 91.470157
iter  60 value 91.466933
iter  70 value 87.273566
iter  80 value 84.068877
iter  90 value 83.926986
iter 100 value 82.500939
final  value 82.500939 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 133.204569 
iter  10 value 94.364135
iter  20 value 94.269834
iter  30 value 93.766910
final  value 93.693709 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.181161 
iter  10 value 94.296369
iter  20 value 94.219311
iter  30 value 94.206559
iter  40 value 93.748299
iter  50 value 92.921074
iter  60 value 83.740394
iter  70 value 82.855054
iter  80 value 82.834301
iter  90 value 82.834147
final  value 82.833977 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.188879 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.213890 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.744498 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.457633 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.017179 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.312219 
iter  10 value 94.042030
final  value 94.042012 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.412761 
iter  10 value 94.057646
iter  20 value 94.052913
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.422277 
iter  10 value 94.008699
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.175962 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.111931 
final  value 94.042012 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.755132 
iter  10 value 92.701660
final  value 92.701657 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.341809 
iter  10 value 94.053561
iter  20 value 93.637003
iter  30 value 93.507271
iter  40 value 93.506763
final  value 93.506755 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.163176 
iter  10 value 94.043544
final  value 94.015123 
converged
Fitting Repeat 4 

# weights:  507
initial  value 130.295312 
iter  10 value 94.054701
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.759489 
iter  10 value 93.808689
final  value 93.808679 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.855073 
iter  10 value 94.033831
iter  20 value 92.177141
iter  30 value 91.433179
iter  40 value 88.233473
iter  50 value 83.296233
iter  60 value 80.962909
iter  70 value 80.883385
iter  80 value 80.828651
iter  90 value 80.786012
iter 100 value 80.405288
final  value 80.405288 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.225159 
iter  10 value 93.182406
iter  20 value 85.608848
iter  30 value 84.797918
iter  40 value 84.672500
iter  50 value 84.562507
iter  60 value 84.352017
iter  70 value 82.741272
iter  80 value 80.874116
iter  90 value 80.615641
iter 100 value 80.139816
final  value 80.139816 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.519334 
iter  10 value 94.056682
iter  20 value 93.840341
iter  30 value 83.979772
iter  40 value 83.118394
iter  50 value 82.855278
iter  60 value 81.991113
iter  70 value 81.710432
iter  80 value 81.627175
final  value 81.627173 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.590833 
iter  10 value 94.054816
iter  20 value 90.038617
iter  30 value 88.260588
iter  40 value 81.415686
iter  50 value 80.876797
iter  60 value 80.811857
iter  70 value 80.611227
iter  80 value 80.193407
iter  90 value 80.106102
iter 100 value 80.079850
final  value 80.079850 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.523816 
iter  10 value 94.056640
iter  20 value 92.392864
iter  30 value 85.178386
iter  40 value 83.915779
iter  50 value 83.407886
iter  60 value 83.282375
iter  70 value 83.278123
iter  70 value 83.278122
iter  70 value 83.278122
final  value 83.278122 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.588059 
iter  10 value 94.121560
iter  20 value 93.953021
iter  30 value 90.346900
iter  40 value 86.231053
iter  50 value 84.803070
iter  60 value 82.323664
iter  70 value 81.778976
iter  80 value 81.634376
iter  90 value 81.538771
iter 100 value 81.436573
final  value 81.436573 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.893918 
iter  10 value 94.074342
iter  20 value 93.817779
iter  30 value 90.195021
iter  40 value 85.360166
iter  50 value 84.634437
iter  60 value 82.127742
iter  70 value 80.893121
iter  80 value 80.577368
iter  90 value 80.151755
iter 100 value 79.490034
final  value 79.490034 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.060695 
iter  10 value 94.210671
iter  20 value 87.510746
iter  30 value 85.943860
iter  40 value 83.616628
iter  50 value 82.843877
iter  60 value 82.093145
iter  70 value 81.676389
iter  80 value 80.939383
iter  90 value 80.164703
iter 100 value 79.231398
final  value 79.231398 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.957239 
iter  10 value 108.416751
iter  20 value 93.483020
iter  30 value 88.599447
iter  40 value 83.206401
iter  50 value 82.712376
iter  60 value 81.089298
iter  70 value 80.719607
iter  80 value 80.418285
iter  90 value 80.207949
iter 100 value 80.162960
final  value 80.162960 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.679585 
iter  10 value 94.657578
iter  20 value 88.770336
iter  30 value 85.095738
iter  40 value 83.880291
iter  50 value 82.073880
iter  60 value 80.540077
iter  70 value 80.012284
iter  80 value 79.677333
iter  90 value 79.099133
iter 100 value 78.758508
final  value 78.758508 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.300604 
iter  10 value 94.145807
iter  20 value 93.895542
iter  30 value 88.969237
iter  40 value 83.122468
iter  50 value 82.035359
iter  60 value 81.168215
iter  70 value 79.224773
iter  80 value 78.352474
iter  90 value 78.213214
iter 100 value 78.192100
final  value 78.192100 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.636700 
iter  10 value 93.944577
iter  20 value 85.702580
iter  30 value 83.437608
iter  40 value 82.988712
iter  50 value 82.281983
iter  60 value 79.972290
iter  70 value 78.912793
iter  80 value 78.743840
iter  90 value 78.606302
iter 100 value 78.546278
final  value 78.546278 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.214609 
iter  10 value 94.089544
iter  20 value 93.773644
iter  30 value 88.709841
iter  40 value 84.331003
iter  50 value 83.254427
iter  60 value 82.155266
iter  70 value 81.323198
iter  80 value 80.611211
iter  90 value 80.195277
iter 100 value 79.464885
final  value 79.464885 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 139.078355 
iter  10 value 94.032405
iter  20 value 86.068470
iter  30 value 82.855054
iter  40 value 80.992177
iter  50 value 80.298411
iter  60 value 80.152489
iter  70 value 80.036004
iter  80 value 78.952364
iter  90 value 78.544470
iter 100 value 78.398335
final  value 78.398335 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.684299 
iter  10 value 93.796196
iter  20 value 85.256233
iter  30 value 82.734375
iter  40 value 82.545945
iter  50 value 82.327804
iter  60 value 81.813147
iter  70 value 80.421226
iter  80 value 79.279026
iter  90 value 78.749484
iter 100 value 78.469242
final  value 78.469242 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.101168 
final  value 94.054802 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.493372 
iter  10 value 93.837761
iter  20 value 93.836673
iter  30 value 93.786498
iter  40 value 93.786058
final  value 93.786041 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.662925 
iter  10 value 91.574666
iter  20 value 90.787081
iter  30 value 90.785657
iter  40 value 90.784939
iter  50 value 83.091564
iter  60 value 82.166526
iter  70 value 81.521465
iter  80 value 81.506112
final  value 81.492035 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.472181 
final  value 94.054680 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.311364 
final  value 94.054703 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.622054 
iter  10 value 94.057972
iter  20 value 94.053013
iter  30 value 93.926123
iter  40 value 84.661595
iter  50 value 81.560844
iter  60 value 81.553482
final  value 81.553267 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.729896 
iter  10 value 94.055253
iter  20 value 91.471406
iter  30 value 81.541436
iter  40 value 81.136579
final  value 81.136165 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.203754 
iter  10 value 91.468816
iter  20 value 84.492500
iter  30 value 84.054583
iter  40 value 83.991644
iter  50 value 83.989839
iter  60 value 82.026914
iter  70 value 80.426124
iter  80 value 78.444656
iter  90 value 78.388788
iter 100 value 78.387553
final  value 78.387553 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.602964 
iter  10 value 94.058915
iter  20 value 89.910435
iter  30 value 85.400669
iter  40 value 84.066148
iter  50 value 82.992363
iter  60 value 81.848463
iter  70 value 81.845312
iter  80 value 81.841680
iter  90 value 81.598181
iter 100 value 80.711562
final  value 80.711562 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.595858 
iter  10 value 94.058045
iter  20 value 94.053111
iter  30 value 93.950076
iter  40 value 92.955549
iter  50 value 92.954771
iter  60 value 92.927108
iter  70 value 92.313887
iter  80 value 90.156361
iter  90 value 90.156071
iter 100 value 90.147988
final  value 90.147988 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.134370 
iter  10 value 93.844694
iter  20 value 93.738999
iter  30 value 85.124319
iter  40 value 83.172138
iter  50 value 82.497893
final  value 82.495503 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.244176 
iter  10 value 93.613639
iter  20 value 93.610224
iter  30 value 93.604820
iter  40 value 87.208830
iter  50 value 84.278879
iter  60 value 84.278159
iter  70 value 84.262948
iter  80 value 84.256388
final  value 84.256074 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.067582 
iter  10 value 81.757385
iter  20 value 81.123177
iter  30 value 80.737155
iter  40 value 80.726132
iter  50 value 80.719468
iter  60 value 80.510984
iter  70 value 79.594221
iter  80 value 79.402828
iter  90 value 79.394379
final  value 79.394315 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.099073 
iter  10 value 93.844725
iter  20 value 93.836782
iter  30 value 90.813852
iter  40 value 83.014265
iter  50 value 82.894574
iter  60 value 82.893534
final  value 82.893486 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.391857 
iter  10 value 83.673048
iter  20 value 80.905886
iter  30 value 79.352688
final  value 79.342731 
converged
Fitting Repeat 1 

# weights:  305
initial  value 129.220099 
iter  10 value 117.735322
iter  20 value 117.415346
iter  30 value 105.532073
iter  40 value 105.364069
iter  50 value 105.362852
iter  60 value 105.347472
iter  70 value 105.345880
final  value 105.343681 
converged
Fitting Repeat 2 

# weights:  305
initial  value 123.026387 
iter  10 value 117.894469
iter  20 value 112.625751
iter  30 value 106.938511
iter  40 value 106.737980
iter  50 value 106.724543
iter  60 value 106.724414
final  value 106.723665 
converged
Fitting Repeat 3 

# weights:  305
initial  value 133.343116 
iter  10 value 117.763421
iter  20 value 117.737507
iter  30 value 117.728663
final  value 117.728589 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.469178 
iter  10 value 117.894652
iter  20 value 115.235998
iter  30 value 107.288329
iter  40 value 106.777879
iter  50 value 106.774416
final  value 106.773103 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.933242 
iter  10 value 117.893779
iter  20 value 117.580795
final  value 117.511456 
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 Nov 20 08:58:24 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 55.427   1.875  76.126