| Back to Build/check report for BioC 3.17 |
|
This page was generated on 2023-01-29 16:33:53 -0000 (Sun, 29 Jan 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| kunpeng1 | Linux (Ubuntu 22.04.1 LTS) | aarch64 | R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences" | 4021 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
|
To the developers/maintainers of the HPiP package: - Please allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 913/2162 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.5.0 (landing page) Matineh Rahmatbakhsh
| kunpeng1 | Linux (Ubuntu 22.04.1 LTS) / aarch64 | OK | OK | WARNINGS | |||||||||
| Package: HPiP |
| Version: 1.5.0 |
| Command: /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/library --timings HPiP_1.5.0.tar.gz |
| StartedAt: 2023-01-29 00:58:47 -0000 (Sun, 29 Jan 2023) |
| EndedAt: 2023-01-29 01:13:44 -0000 (Sun, 29 Jan 2023) |
| EllapsedTime: 896.3 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: HPiP.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/library --timings HPiP_1.5.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2023-01-14 r83615)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
* running under: Ubuntu 22.04.1 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.5.0’
* 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 package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... WARNING
Error in library(HPiP, lib.loc = "/home/biocbuild/bbs-3.17-bioc/R/library") :
there is no package called ‘HPiP’
Execution halted
It looks like this package has a loading problem when not on .libPaths:
see the messages for details.
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... SKIPPED
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘runTests.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK
NONE
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 1 NOTE
See
‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.17-bioc/R/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)
HPiP.Rcheck/tests/runTests.Rout
R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 98.171410
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 108.896662
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 94.634728
iter 10 value 90.713958
iter 20 value 84.727326
iter 30 value 84.721023
final value 84.720834
converged
Fitting Repeat 4
# weights: 103
initial value 97.870674
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.674077
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 113.280599
final value 94.466823
converged
Fitting Repeat 2
# weights: 305
initial value 105.319541
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 111.451643
iter 10 value 94.406499
final value 94.354286
converged
Fitting Repeat 4
# weights: 305
initial value 97.667369
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 96.398730
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 124.666506
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 95.576470
final value 94.354286
converged
Fitting Repeat 3
# weights: 507
initial value 112.400731
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 99.015452
iter 10 value 93.811885
iter 20 value 92.785416
iter 30 value 92.770472
final value 92.770439
converged
Fitting Repeat 5
# weights: 507
initial value 100.882161
final value 94.330952
converged
Fitting Repeat 1
# weights: 103
initial value 103.645851
iter 10 value 94.487388
iter 20 value 94.413899
iter 30 value 90.576080
iter 40 value 88.746224
iter 50 value 88.654741
iter 60 value 88.649272
iter 70 value 88.112215
iter 80 value 86.400309
iter 90 value 84.856875
iter 100 value 84.561463
final value 84.561463
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 103.600676
iter 10 value 94.479784
iter 20 value 91.652481
iter 30 value 90.758758
iter 40 value 89.055724
iter 50 value 88.560880
iter 60 value 84.511261
iter 70 value 83.992821
iter 80 value 83.966301
iter 90 value 83.781187
iter 100 value 82.814871
final value 82.814871
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 98.460641
iter 10 value 94.402423
iter 20 value 89.675699
iter 30 value 86.466307
iter 40 value 83.792363
iter 50 value 83.495974
iter 60 value 83.429530
final value 83.429496
converged
Fitting Repeat 4
# weights: 103
initial value 107.700655
iter 10 value 92.354568
iter 20 value 89.113206
iter 30 value 85.310003
iter 40 value 83.603829
iter 50 value 83.561590
iter 60 value 83.416509
iter 70 value 83.352274
final value 83.352178
converged
Fitting Repeat 5
# weights: 103
initial value 100.032055
iter 10 value 95.372470
iter 20 value 94.485980
iter 30 value 94.012868
iter 40 value 89.938626
iter 50 value 86.376689
iter 60 value 84.761574
iter 70 value 83.663011
iter 80 value 82.973347
iter 90 value 82.737088
final value 82.736613
converged
Fitting Repeat 1
# weights: 305
initial value 103.254624
iter 10 value 94.551297
iter 20 value 90.230121
iter 30 value 85.481021
iter 40 value 84.059718
iter 50 value 83.545459
iter 60 value 82.818504
iter 70 value 82.402357
iter 80 value 82.117719
iter 90 value 81.991263
iter 100 value 81.966382
final value 81.966382
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.981515
iter 10 value 94.496651
iter 20 value 89.012667
iter 30 value 87.967905
iter 40 value 86.972058
iter 50 value 86.223041
iter 60 value 85.271004
iter 70 value 84.296087
iter 80 value 83.121797
iter 90 value 82.875945
iter 100 value 82.714146
final value 82.714146
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.495390
iter 10 value 94.472348
iter 20 value 87.638034
iter 30 value 85.770040
iter 40 value 85.121160
iter 50 value 81.918428
iter 60 value 81.090466
iter 70 value 80.887909
iter 80 value 80.669006
iter 90 value 80.528721
iter 100 value 80.466837
final value 80.466837
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 116.904695
iter 10 value 94.603494
iter 20 value 88.338172
iter 30 value 86.352952
iter 40 value 84.785898
iter 50 value 83.777939
iter 60 value 83.722205
iter 70 value 83.658708
iter 80 value 83.631707
iter 90 value 83.539500
iter 100 value 82.936796
final value 82.936796
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.292788
iter 10 value 93.987763
iter 20 value 87.700662
iter 30 value 85.686308
iter 40 value 85.468251
iter 50 value 84.042356
iter 60 value 83.142092
iter 70 value 82.641747
iter 80 value 82.235132
iter 90 value 82.041807
iter 100 value 82.017411
final value 82.017411
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 117.507057
iter 10 value 94.601784
iter 20 value 85.360055
iter 30 value 84.847974
iter 40 value 84.769072
iter 50 value 84.154486
iter 60 value 83.255832
iter 70 value 82.773711
iter 80 value 82.519089
iter 90 value 81.023362
iter 100 value 80.901514
final value 80.901514
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 123.686203
iter 10 value 94.249454
iter 20 value 89.534558
iter 30 value 86.894810
iter 40 value 84.740938
iter 50 value 84.531757
iter 60 value 84.492985
iter 70 value 84.389685
iter 80 value 84.185919
iter 90 value 83.729761
iter 100 value 83.424197
final value 83.424197
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.552888
iter 10 value 95.042102
iter 20 value 91.558019
iter 30 value 88.980536
iter 40 value 85.095185
iter 50 value 83.812326
iter 60 value 82.339551
iter 70 value 81.018156
iter 80 value 80.635539
iter 90 value 80.384471
iter 100 value 80.154891
final value 80.154891
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 127.278652
iter 10 value 94.957908
iter 20 value 91.822432
iter 30 value 86.587748
iter 40 value 85.613054
iter 50 value 84.169719
iter 60 value 83.979573
iter 70 value 83.644809
iter 80 value 82.415206
iter 90 value 80.944435
iter 100 value 80.764512
final value 80.764512
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 136.838071
iter 10 value 98.029777
iter 20 value 87.248669
iter 30 value 86.087996
iter 40 value 83.716673
iter 50 value 82.354630
iter 60 value 82.080499
iter 70 value 81.685159
iter 80 value 81.326167
iter 90 value 81.154945
iter 100 value 81.027985
final value 81.027985
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 106.103806
final value 94.485800
converged
Fitting Repeat 2
# weights: 103
initial value 98.595895
final value 94.468316
converged
Fitting Repeat 3
# weights: 103
initial value 103.929187
final value 94.486020
converged
Fitting Repeat 4
# weights: 103
initial value 100.097320
iter 10 value 93.885144
iter 20 value 91.787245
iter 30 value 87.718896
iter 40 value 87.691351
iter 50 value 87.690531
iter 60 value 87.688960
final value 87.688464
converged
Fitting Repeat 5
# weights: 103
initial value 99.835735
iter 10 value 94.114957
iter 20 value 94.113997
iter 30 value 94.091325
iter 40 value 94.086483
final value 94.085851
converged
Fitting Repeat 1
# weights: 305
initial value 103.305614
iter 10 value 94.489386
iter 20 value 94.479805
iter 30 value 94.332597
final value 94.331396
converged
Fitting Repeat 2
# weights: 305
initial value 99.642035
iter 10 value 93.893773
iter 20 value 93.700051
iter 30 value 93.648237
iter 40 value 93.578874
iter 50 value 91.447533
iter 60 value 85.013679
iter 70 value 83.171465
iter 80 value 82.907332
iter 90 value 82.471992
iter 100 value 82.442326
final value 82.442326
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 97.509614
iter 10 value 94.489413
iter 20 value 94.484234
iter 30 value 93.447410
iter 40 value 85.672293
iter 50 value 83.794672
iter 60 value 83.704544
iter 70 value 83.282597
iter 80 value 83.153578
iter 90 value 83.149938
iter 100 value 83.086887
final value 83.086887
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 118.170430
iter 10 value 94.343575
iter 20 value 94.339691
iter 30 value 94.111354
iter 40 value 93.375938
iter 50 value 87.904641
iter 60 value 87.759398
iter 70 value 85.360265
iter 80 value 85.357229
iter 90 value 85.356549
iter 100 value 85.355672
final value 85.355672
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 96.822093
iter 10 value 94.488152
iter 20 value 84.549729
iter 30 value 83.886699
iter 40 value 83.857946
iter 50 value 83.857697
iter 60 value 83.067831
iter 70 value 82.883980
iter 80 value 79.722178
iter 90 value 79.224925
iter 100 value 79.099388
final value 79.099388
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 100.054334
iter 10 value 94.492273
iter 20 value 94.484311
iter 30 value 94.346590
iter 40 value 92.212853
iter 50 value 91.400996
iter 60 value 90.256828
iter 70 value 90.019054
iter 80 value 89.842709
iter 90 value 89.838692
iter 100 value 89.838094
final value 89.838094
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.762370
iter 10 value 94.475241
iter 20 value 94.473280
iter 30 value 94.472312
iter 40 value 94.364840
iter 50 value 93.729038
iter 60 value 84.020953
final value 83.929533
converged
Fitting Repeat 3
# weights: 507
initial value 97.422060
iter 10 value 94.492865
iter 20 value 94.488013
iter 30 value 94.480930
iter 40 value 94.114898
final value 94.112889
converged
Fitting Repeat 4
# weights: 507
initial value 111.896203
iter 10 value 94.474982
iter 20 value 94.337866
iter 30 value 90.928099
iter 40 value 90.919255
iter 50 value 90.581323
iter 60 value 85.985027
iter 70 value 83.655588
iter 80 value 83.516697
iter 90 value 82.959228
iter 100 value 80.361023
final value 80.361023
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.588639
iter 10 value 94.492684
iter 20 value 94.448707
iter 30 value 87.154134
iter 40 value 84.750336
iter 50 value 84.747208
iter 60 value 84.738690
iter 70 value 84.733095
iter 80 value 83.831150
iter 90 value 83.100722
iter 100 value 83.100111
final value 83.100111
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.527926
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.885317
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.928289
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.634479
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 104.344429
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 99.666336
final value 94.275362
converged
Fitting Repeat 2
# weights: 305
initial value 103.377674
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 101.387093
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 105.717217
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 95.901080
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 114.561776
iter 10 value 92.303448
iter 10 value 92.303448
iter 10 value 92.303448
final value 92.303448
converged
Fitting Repeat 2
# weights: 507
initial value 113.834850
iter 10 value 93.177560
final value 93.177238
converged
Fitting Repeat 3
# weights: 507
initial value 101.580425
iter 10 value 87.764832
iter 20 value 83.273669
iter 30 value 82.810357
iter 40 value 82.615338
iter 50 value 82.608129
final value 82.607893
converged
Fitting Repeat 4
# weights: 507
initial value 95.252858
iter 10 value 87.375350
iter 20 value 87.245616
iter 30 value 87.045711
iter 40 value 86.113061
iter 50 value 85.400382
iter 60 value 85.248407
iter 70 value 85.223177
iter 80 value 85.222632
final value 85.222587
converged
Fitting Repeat 5
# weights: 507
initial value 138.983663
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 104.301308
iter 10 value 94.107086
iter 20 value 88.917998
iter 30 value 88.065678
iter 40 value 81.452127
iter 50 value 80.931645
iter 60 value 80.687053
iter 70 value 80.381292
iter 80 value 80.310873
iter 90 value 80.272879
iter 100 value 80.271457
final value 80.271457
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.720861
iter 10 value 94.488276
iter 20 value 94.296296
iter 30 value 85.223501
iter 40 value 84.327846
iter 50 value 84.167735
iter 60 value 84.062922
iter 70 value 83.821977
iter 80 value 83.810966
final value 83.810868
converged
Fitting Repeat 3
# weights: 103
initial value 104.210307
iter 10 value 94.753154
iter 20 value 94.472184
iter 30 value 94.122702
iter 40 value 93.882280
iter 50 value 93.398207
iter 60 value 92.898369
iter 70 value 87.575079
iter 80 value 84.036999
iter 90 value 83.743761
iter 100 value 83.540124
final value 83.540124
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 97.530421
iter 10 value 94.492443
iter 20 value 94.486589
iter 30 value 93.851027
iter 40 value 89.106309
iter 50 value 86.909398
iter 60 value 84.605231
iter 70 value 83.865694
iter 80 value 83.816684
iter 90 value 83.811145
iter 100 value 83.810866
final value 83.810866
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.935948
iter 10 value 94.450176
iter 20 value 89.215716
iter 30 value 85.359467
iter 40 value 84.150689
iter 50 value 83.953622
iter 60 value 82.197613
iter 70 value 80.761076
iter 80 value 80.407284
iter 90 value 80.271918
final value 80.271249
converged
Fitting Repeat 1
# weights: 305
initial value 100.438070
iter 10 value 93.959973
iter 20 value 93.305436
iter 30 value 92.715466
iter 40 value 88.925018
iter 50 value 87.301068
iter 60 value 86.942789
iter 70 value 86.217546
iter 80 value 83.725508
iter 90 value 82.347146
iter 100 value 80.702165
final value 80.702165
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 110.579847
iter 10 value 94.767203
iter 20 value 94.207068
iter 30 value 93.430542
iter 40 value 89.290759
iter 50 value 86.878425
iter 60 value 84.547933
iter 70 value 83.077580
iter 80 value 81.416040
iter 90 value 81.264814
iter 100 value 81.195076
final value 81.195076
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.644633
iter 10 value 94.997139
iter 20 value 93.290249
iter 30 value 93.116940
iter 40 value 86.054798
iter 50 value 83.092182
iter 60 value 80.397490
iter 70 value 79.445264
iter 80 value 79.295073
iter 90 value 79.205015
iter 100 value 79.195231
final value 79.195231
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 111.823385
iter 10 value 95.224521
iter 20 value 93.179634
iter 30 value 90.724922
iter 40 value 90.376608
iter 50 value 89.508463
iter 60 value 82.800368
iter 70 value 80.345069
iter 80 value 79.869955
iter 90 value 79.684162
iter 100 value 79.529002
final value 79.529002
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 111.338919
iter 10 value 93.622787
iter 20 value 93.362933
iter 30 value 92.570683
iter 40 value 91.457112
iter 50 value 90.428600
iter 60 value 89.375388
iter 70 value 88.875086
iter 80 value 87.943223
iter 90 value 84.006844
iter 100 value 80.492123
final value 80.492123
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.575208
iter 10 value 88.928392
iter 20 value 86.071232
iter 30 value 85.123314
iter 40 value 82.457778
iter 50 value 81.395294
iter 60 value 81.109314
iter 70 value 80.951609
iter 80 value 80.885135
iter 90 value 80.860108
iter 100 value 80.795329
final value 80.795329
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 124.585613
iter 10 value 93.915951
iter 20 value 90.955760
iter 30 value 84.142236
iter 40 value 83.902808
iter 50 value 81.817229
iter 60 value 81.466398
iter 70 value 81.135279
iter 80 value 81.014897
iter 90 value 80.774665
iter 100 value 80.753312
final value 80.753312
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.300486
iter 10 value 94.613643
iter 20 value 93.354424
iter 30 value 90.919628
iter 40 value 86.284424
iter 50 value 84.411170
iter 60 value 83.808790
iter 70 value 83.589922
iter 80 value 83.004107
iter 90 value 81.704762
iter 100 value 80.899080
final value 80.899080
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 133.073404
iter 10 value 94.486689
iter 20 value 93.445600
iter 30 value 88.910694
iter 40 value 84.947267
iter 50 value 82.146250
iter 60 value 80.566385
iter 70 value 80.161974
iter 80 value 79.422255
iter 90 value 79.215275
iter 100 value 79.001646
final value 79.001646
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.560771
iter 10 value 99.442807
iter 20 value 93.907521
iter 30 value 85.138520
iter 40 value 83.540040
iter 50 value 83.407183
iter 60 value 83.159831
iter 70 value 82.085515
iter 80 value 80.034790
iter 90 value 79.452459
iter 100 value 79.389031
final value 79.389031
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.527506
iter 10 value 93.397385
iter 20 value 93.396977
iter 30 value 92.675660
iter 40 value 92.211543
iter 50 value 89.193909
iter 60 value 80.688417
iter 70 value 80.448894
iter 80 value 79.656974
iter 90 value 78.794710
iter 100 value 78.694101
final value 78.694101
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.732291
final value 94.486030
converged
Fitting Repeat 3
# weights: 103
initial value 101.979833
final value 94.485649
converged
Fitting Repeat 4
# weights: 103
initial value 99.220633
iter 10 value 93.397619
iter 20 value 93.397308
iter 30 value 93.395940
iter 30 value 93.395939
iter 30 value 93.395939
final value 93.395939
converged
Fitting Repeat 5
# weights: 103
initial value 98.773670
final value 94.485855
converged
Fitting Repeat 1
# weights: 305
initial value 110.816758
iter 10 value 94.488476
iter 20 value 89.682374
iter 30 value 86.873468
iter 40 value 86.872577
iter 50 value 85.726756
iter 60 value 85.282200
iter 70 value 85.097749
iter 80 value 84.955174
iter 90 value 84.892649
iter 100 value 84.790019
final value 84.790019
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.405852
iter 10 value 94.489007
iter 20 value 94.484222
iter 30 value 94.077355
iter 40 value 85.692687
iter 50 value 85.679987
iter 60 value 85.003211
iter 70 value 80.170987
iter 80 value 79.894663
iter 90 value 79.869710
iter 100 value 79.863907
final value 79.863907
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.867440
iter 10 value 94.489003
iter 20 value 91.329166
iter 30 value 91.307555
iter 40 value 91.268752
iter 50 value 91.265234
iter 60 value 91.264951
iter 60 value 91.264950
final value 91.264950
converged
Fitting Repeat 4
# weights: 305
initial value 100.445867
iter 10 value 94.489300
iter 20 value 94.484398
iter 20 value 94.484398
iter 20 value 94.484398
final value 94.484398
converged
Fitting Repeat 5
# weights: 305
initial value 96.131879
iter 10 value 94.488872
iter 20 value 94.061151
iter 30 value 87.465396
iter 40 value 82.633791
iter 50 value 81.996519
iter 60 value 81.996175
iter 70 value 81.995188
iter 80 value 81.949057
iter 90 value 81.858716
iter 100 value 79.214608
final value 79.214608
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.749385
iter 10 value 93.185133
iter 20 value 92.919745
iter 30 value 92.915518
iter 40 value 91.444583
iter 50 value 86.172736
iter 60 value 83.598497
iter 70 value 79.752111
iter 80 value 79.021348
iter 90 value 78.878895
final value 78.878700
converged
Fitting Repeat 2
# weights: 507
initial value 107.861107
iter 10 value 93.524486
iter 20 value 85.728210
iter 30 value 85.228673
iter 40 value 82.995361
iter 50 value 82.972620
iter 60 value 82.971976
final value 82.967267
converged
Fitting Repeat 3
# weights: 507
initial value 120.010875
iter 10 value 94.492739
iter 20 value 94.375877
final value 93.395671
converged
Fitting Repeat 4
# weights: 507
initial value 94.185148
iter 10 value 86.543884
iter 20 value 86.512897
iter 30 value 84.961165
iter 40 value 84.959968
iter 50 value 84.328237
iter 60 value 84.192397
iter 70 value 84.179906
iter 80 value 84.162972
iter 90 value 84.153641
iter 100 value 83.738839
final value 83.738839
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 94.603184
iter 10 value 93.127381
iter 20 value 93.084422
iter 30 value 92.922879
final value 92.912025
converged
Fitting Repeat 1
# weights: 103
initial value 99.344721
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 97.806292
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.477109
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 99.754639
final value 93.893849
converged
Fitting Repeat 5
# weights: 103
initial value 96.653304
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 127.833146
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 119.615596
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 106.209093
final value 94.038251
converged
Fitting Repeat 4
# weights: 305
initial value 104.887298
final value 94.038251
converged
Fitting Repeat 5
# weights: 305
initial value 110.715489
final value 94.038251
converged
Fitting Repeat 1
# weights: 507
initial value 99.357587
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 110.220893
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 112.645605
final value 94.038251
converged
Fitting Repeat 4
# weights: 507
initial value 129.942829
final value 93.800211
converged
Fitting Repeat 5
# weights: 507
initial value 106.826902
final value 94.038251
converged
Fitting Repeat 1
# weights: 103
initial value 98.580814
iter 10 value 93.961955
iter 20 value 85.503988
iter 30 value 83.256281
iter 40 value 82.825245
iter 50 value 82.781383
iter 60 value 82.651804
iter 70 value 79.584986
iter 80 value 79.571837
iter 90 value 79.562435
iter 100 value 79.551039
final value 79.551039
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.285391
iter 10 value 89.585100
iter 20 value 84.046840
iter 30 value 83.636068
iter 40 value 80.257230
iter 50 value 79.621923
iter 60 value 79.553005
final value 79.550904
converged
Fitting Repeat 3
# weights: 103
initial value 102.510293
iter 10 value 93.938772
iter 20 value 92.810670
iter 30 value 91.053999
iter 40 value 81.625485
iter 50 value 81.387316
iter 60 value 81.269103
iter 70 value 80.679749
iter 80 value 80.656198
final value 80.656192
converged
Fitting Repeat 4
# weights: 103
initial value 100.070037
iter 10 value 94.051620
iter 20 value 80.549323
iter 30 value 80.314305
iter 40 value 80.157326
iter 50 value 79.546851
iter 60 value 79.249726
iter 70 value 79.016045
iter 80 value 79.013323
final value 79.013038
converged
Fitting Repeat 5
# weights: 103
initial value 96.148242
iter 10 value 94.006789
iter 20 value 92.594025
iter 30 value 86.317958
iter 40 value 82.811266
iter 50 value 81.644153
iter 60 value 80.783655
iter 70 value 80.256141
iter 80 value 80.131534
final value 80.130299
converged
Fitting Repeat 1
# weights: 305
initial value 103.297259
iter 10 value 94.214043
iter 20 value 94.040532
iter 30 value 82.474788
iter 40 value 79.085835
iter 50 value 76.688618
iter 60 value 76.303668
iter 70 value 75.486092
iter 80 value 75.156005
iter 90 value 74.935145
iter 100 value 74.905080
final value 74.905080
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 115.921055
iter 10 value 94.048464
iter 20 value 92.584010
iter 30 value 89.593079
iter 40 value 89.012390
iter 50 value 87.333515
iter 60 value 79.619294
iter 70 value 78.374505
iter 80 value 77.908341
iter 90 value 77.499499
iter 100 value 76.864226
final value 76.864226
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.845873
iter 10 value 94.067422
iter 20 value 92.176445
iter 30 value 84.722844
iter 40 value 81.791253
iter 50 value 81.216719
iter 60 value 81.069053
iter 70 value 80.583963
iter 80 value 79.616050
iter 90 value 77.597999
iter 100 value 76.534617
final value 76.534617
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.872933
iter 10 value 94.071898
iter 20 value 93.770835
iter 30 value 85.816009
iter 40 value 84.889412
iter 50 value 80.911489
iter 60 value 79.036315
iter 70 value 76.063050
iter 80 value 75.966683
iter 90 value 75.947590
iter 100 value 75.934865
final value 75.934865
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.890521
iter 10 value 92.204599
iter 20 value 87.759912
iter 30 value 79.760720
iter 40 value 78.383744
iter 50 value 77.519211
iter 60 value 77.024872
iter 70 value 76.578019
iter 80 value 76.461318
iter 90 value 76.442346
iter 100 value 76.433782
final value 76.433782
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.399817
iter 10 value 95.263021
iter 20 value 87.983083
iter 30 value 80.412402
iter 40 value 78.464491
iter 50 value 77.610870
iter 60 value 76.810579
iter 70 value 75.641256
iter 80 value 74.849478
iter 90 value 74.586083
iter 100 value 74.575700
final value 74.575700
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 129.762473
iter 10 value 93.159907
iter 20 value 81.189053
iter 30 value 80.354486
iter 40 value 77.721537
iter 50 value 76.660546
iter 60 value 75.401575
iter 70 value 74.887740
iter 80 value 74.669876
iter 90 value 74.588195
iter 100 value 74.512937
final value 74.512937
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 129.539815
iter 10 value 93.904524
iter 20 value 82.678742
iter 30 value 80.723682
iter 40 value 78.635875
iter 50 value 77.507135
iter 60 value 75.899336
iter 70 value 75.115021
iter 80 value 74.939555
iter 90 value 74.836122
iter 100 value 74.768798
final value 74.768798
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.020846
iter 10 value 94.414606
iter 20 value 89.269925
iter 30 value 84.096166
iter 40 value 81.609531
iter 50 value 80.472396
iter 60 value 78.763800
iter 70 value 77.851871
iter 80 value 77.432154
iter 90 value 76.517279
iter 100 value 75.870983
final value 75.870983
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.387370
iter 10 value 94.289620
iter 20 value 93.624100
iter 30 value 81.587742
iter 40 value 80.177145
iter 50 value 79.694943
iter 60 value 77.692881
iter 70 value 77.042331
iter 80 value 76.282420
iter 90 value 75.844234
iter 100 value 75.339640
final value 75.339640
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.383949
final value 94.054640
converged
Fitting Repeat 2
# weights: 103
initial value 97.181188
final value 94.054574
converged
Fitting Repeat 3
# weights: 103
initial value 110.907780
iter 10 value 94.054417
iter 20 value 90.633699
iter 30 value 78.109401
iter 40 value 78.018052
iter 50 value 78.017697
final value 78.017659
converged
Fitting Repeat 4
# weights: 103
initial value 101.238601
final value 94.054576
converged
Fitting Repeat 5
# weights: 103
initial value 95.713946
final value 94.054499
converged
Fitting Repeat 1
# weights: 305
initial value 100.630651
iter 10 value 93.676502
iter 20 value 93.671581
iter 30 value 86.428850
iter 40 value 82.380667
iter 50 value 82.002675
iter 60 value 81.329243
iter 70 value 76.316446
iter 80 value 75.510249
iter 90 value 75.366810
iter 100 value 75.085448
final value 75.085448
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 95.369153
iter 10 value 94.057679
iter 20 value 94.034711
iter 30 value 92.599126
iter 40 value 90.793521
iter 50 value 90.784495
iter 60 value 90.772217
iter 70 value 90.768690
final value 90.768480
converged
Fitting Repeat 3
# weights: 305
initial value 95.928049
iter 10 value 90.852383
iter 20 value 90.659813
iter 30 value 90.657791
iter 40 value 89.217421
iter 50 value 89.208810
iter 60 value 88.492444
iter 70 value 88.488658
final value 88.488618
converged
Fitting Repeat 4
# weights: 305
initial value 100.870002
iter 10 value 92.236253
iter 20 value 91.278368
iter 30 value 91.264611
iter 40 value 90.885713
iter 50 value 90.854531
iter 60 value 90.852773
iter 70 value 90.851957
iter 80 value 90.677618
final value 90.671818
converged
Fitting Repeat 5
# weights: 305
initial value 100.382711
iter 10 value 94.043328
iter 20 value 94.040996
iter 30 value 94.039904
iter 40 value 94.038877
iter 50 value 93.976961
iter 60 value 92.807016
iter 70 value 92.802428
iter 80 value 91.260961
iter 80 value 91.260961
iter 80 value 91.260961
final value 91.260961
converged
Fitting Repeat 1
# weights: 507
initial value 118.810291
iter 10 value 94.046580
iter 20 value 94.017930
iter 30 value 90.470139
iter 40 value 80.954114
iter 50 value 80.874514
iter 60 value 80.541625
iter 70 value 80.498888
iter 80 value 80.445051
iter 90 value 77.376813
iter 100 value 77.092883
final value 77.092883
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.280284
iter 10 value 94.061185
iter 20 value 90.133198
iter 30 value 89.271030
iter 40 value 89.256033
iter 50 value 77.736190
iter 60 value 77.386007
iter 60 value 77.386007
final value 77.386007
converged
Fitting Repeat 3
# weights: 507
initial value 126.520733
iter 10 value 93.657636
iter 20 value 92.125532
iter 30 value 91.994529
final value 91.994222
converged
Fitting Repeat 4
# weights: 507
initial value 98.067474
iter 10 value 90.744288
iter 20 value 89.696568
iter 30 value 89.127143
iter 40 value 89.125219
iter 50 value 88.324647
iter 60 value 88.319690
iter 70 value 87.390974
iter 80 value 75.812380
iter 90 value 75.533910
iter 100 value 75.516189
final value 75.516189
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 99.513085
iter 10 value 94.017178
iter 20 value 94.009410
iter 30 value 94.009257
final value 94.009187
converged
Fitting Repeat 1
# weights: 103
initial value 96.246087
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 104.280891
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 98.813795
iter 10 value 86.811731
iter 20 value 85.045132
iter 30 value 85.012463
final value 85.012407
converged
Fitting Repeat 4
# weights: 103
initial value 95.987232
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 98.109060
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 95.196742
final value 93.307576
converged
Fitting Repeat 2
# weights: 305
initial value 102.581638
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 99.131403
iter 10 value 87.290282
iter 20 value 86.200291
final value 86.200000
converged
Fitting Repeat 4
# weights: 305
initial value 101.858601
iter 10 value 92.525607
iter 20 value 92.475600
final value 92.475526
converged
Fitting Repeat 5
# weights: 305
initial value 101.045644
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 96.566067
iter 10 value 90.930759
iter 20 value 90.653659
iter 30 value 90.583435
iter 40 value 90.582489
iter 50 value 90.579566
final value 90.579322
converged
Fitting Repeat 2
# weights: 507
initial value 105.793923
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 109.172107
final value 94.008696
converged
Fitting Repeat 4
# weights: 507
initial value 104.967057
final value 94.008696
converged
Fitting Repeat 5
# weights: 507
initial value 112.765605
final value 93.551913
converged
Fitting Repeat 1
# weights: 103
initial value 95.919831
iter 10 value 93.985147
iter 20 value 84.577025
iter 30 value 84.209289
iter 40 value 83.921331
iter 50 value 83.533480
iter 60 value 83.343973
iter 70 value 83.128496
iter 80 value 83.067156
iter 90 value 83.012663
iter 100 value 82.927557
final value 82.927557
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 102.400058
iter 10 value 93.796422
iter 20 value 84.522237
iter 30 value 83.971493
iter 40 value 83.717792
iter 50 value 83.423881
iter 60 value 83.206568
iter 70 value 83.181838
iter 80 value 83.164321
final value 83.164320
converged
Fitting Repeat 3
# weights: 103
initial value 97.519656
iter 10 value 94.643050
iter 20 value 94.056902
iter 30 value 93.326931
iter 40 value 91.796090
iter 50 value 91.627443
iter 60 value 91.620496
final value 91.620494
converged
Fitting Repeat 4
# weights: 103
initial value 104.110946
iter 10 value 88.841602
iter 20 value 84.230446
iter 30 value 83.345706
iter 40 value 83.062539
iter 50 value 82.911600
iter 60 value 82.822927
iter 70 value 82.662909
iter 80 value 82.588154
final value 82.547661
converged
Fitting Repeat 5
# weights: 103
initial value 107.059477
iter 10 value 93.932432
iter 20 value 85.837907
iter 30 value 85.419997
iter 40 value 85.085448
iter 50 value 85.039902
final value 85.036132
converged
Fitting Repeat 1
# weights: 305
initial value 105.094198
iter 10 value 94.064671
iter 20 value 89.320718
iter 30 value 87.433414
iter 40 value 86.187225
iter 50 value 83.877606
iter 60 value 83.324753
iter 70 value 82.875668
iter 80 value 82.576709
iter 90 value 82.159374
iter 100 value 81.939623
final value 81.939623
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.290081
iter 10 value 89.018936
iter 20 value 83.513656
iter 30 value 82.759248
iter 40 value 82.209956
iter 50 value 81.988034
iter 60 value 81.718542
iter 70 value 81.546505
iter 80 value 81.441652
iter 90 value 81.325546
iter 100 value 81.271774
final value 81.271774
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 112.596797
iter 10 value 93.885067
iter 20 value 89.280570
iter 30 value 87.012194
iter 40 value 83.431053
iter 50 value 82.592470
iter 60 value 82.173779
iter 70 value 82.150117
iter 80 value 82.113413
iter 90 value 81.973119
iter 100 value 81.335515
final value 81.335515
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.071789
iter 10 value 91.894232
iter 20 value 86.251003
iter 30 value 84.416000
iter 40 value 84.029961
iter 50 value 84.009661
iter 60 value 83.978951
iter 70 value 83.390970
iter 80 value 82.794889
iter 90 value 82.238161
iter 100 value 82.154271
final value 82.154271
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.064390
iter 10 value 87.201394
iter 20 value 86.008760
iter 30 value 85.270077
iter 40 value 84.036448
iter 50 value 83.458806
iter 60 value 83.315864
iter 70 value 83.082036
iter 80 value 83.019631
iter 90 value 82.839585
iter 100 value 82.317116
final value 82.317116
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 111.915302
iter 10 value 97.415517
iter 20 value 92.635318
iter 30 value 91.358842
iter 40 value 89.147302
iter 50 value 83.943066
iter 60 value 83.275863
iter 70 value 82.122479
iter 80 value 81.997950
iter 90 value 81.909331
iter 100 value 81.889433
final value 81.889433
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.770262
iter 10 value 94.158577
iter 20 value 84.393135
iter 30 value 84.112779
iter 40 value 83.771620
iter 50 value 83.735631
iter 60 value 83.537723
iter 70 value 82.211489
iter 80 value 82.065230
iter 90 value 81.763724
iter 100 value 81.510279
final value 81.510279
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.859726
iter 10 value 94.314083
iter 20 value 92.064086
iter 30 value 86.379525
iter 40 value 85.544603
iter 50 value 83.949478
iter 60 value 83.461565
iter 70 value 83.240497
iter 80 value 82.987740
iter 90 value 82.037379
iter 100 value 81.412920
final value 81.412920
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.722736
iter 10 value 93.275427
iter 20 value 85.356669
iter 30 value 84.011658
iter 40 value 83.022797
iter 50 value 81.690535
iter 60 value 81.534857
iter 70 value 81.285588
iter 80 value 81.056641
iter 90 value 80.943764
iter 100 value 80.928022
final value 80.928022
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 120.565855
iter 10 value 93.769653
iter 20 value 87.934635
iter 30 value 86.087600
iter 40 value 85.268574
iter 50 value 84.621659
iter 60 value 83.892746
iter 70 value 83.242119
iter 80 value 81.882810
iter 90 value 81.378149
iter 100 value 81.189470
final value 81.189470
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.057884
iter 10 value 94.054465
iter 20 value 93.220109
iter 30 value 91.434704
iter 40 value 91.434365
iter 50 value 91.433903
iter 60 value 91.433736
iter 70 value 91.432564
final value 91.432535
converged
Fitting Repeat 2
# weights: 103
initial value 100.325595
final value 93.553567
converged
Fitting Repeat 3
# weights: 103
initial value 105.341025
iter 10 value 94.014807
final value 94.010236
converged
Fitting Repeat 4
# weights: 103
initial value 106.869417
final value 94.054362
converged
Fitting Repeat 5
# weights: 103
initial value 107.097725
iter 10 value 94.054520
iter 20 value 94.052931
iter 30 value 92.392248
iter 40 value 86.480407
iter 50 value 86.466319
iter 60 value 86.386692
iter 70 value 84.870679
iter 80 value 84.532472
iter 90 value 84.529024
iter 100 value 84.528501
final value 84.528501
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 103.776140
iter 10 value 94.057521
iter 20 value 93.117224
iter 30 value 92.478599
iter 40 value 91.928600
iter 50 value 91.926770
iter 50 value 91.926769
final value 91.926765
converged
Fitting Repeat 2
# weights: 305
initial value 94.977582
iter 10 value 94.057546
iter 20 value 94.029395
iter 30 value 85.486363
iter 40 value 83.908980
iter 50 value 83.473162
iter 60 value 83.132104
iter 70 value 82.915896
iter 80 value 82.868055
iter 90 value 82.866592
iter 100 value 82.865938
final value 82.865938
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.044124
iter 10 value 94.013402
iter 20 value 93.958303
iter 30 value 85.898054
iter 40 value 85.881816
iter 50 value 84.823398
iter 60 value 83.122302
iter 70 value 82.140493
iter 80 value 82.124178
iter 90 value 82.123607
iter 100 value 82.122490
final value 82.122490
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 110.827600
iter 10 value 94.057022
iter 20 value 94.006465
iter 30 value 89.980786
iter 40 value 89.919741
iter 50 value 89.919422
final value 89.919419
converged
Fitting Repeat 5
# weights: 305
initial value 99.557257
iter 10 value 94.057853
final value 94.053420
converged
Fitting Repeat 1
# weights: 507
initial value 120.736304
iter 10 value 94.069713
iter 20 value 94.060702
iter 30 value 91.955238
iter 40 value 91.617888
iter 50 value 90.095229
iter 60 value 82.903294
iter 70 value 80.878125
iter 80 value 80.030400
iter 90 value 79.991806
iter 100 value 79.990965
final value 79.990965
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 96.451822
iter 10 value 92.798686
iter 20 value 88.921359
iter 30 value 88.792262
iter 40 value 88.777578
iter 50 value 84.697809
iter 60 value 82.573358
iter 70 value 81.938405
iter 80 value 81.254991
iter 90 value 80.912426
iter 100 value 80.888502
final value 80.888502
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.667728
iter 10 value 93.279314
iter 20 value 93.272671
iter 30 value 93.248238
iter 40 value 85.879058
iter 50 value 84.928208
iter 60 value 84.337315
iter 70 value 84.293368
iter 80 value 84.284655
iter 90 value 84.265725
iter 100 value 84.265627
final value 84.265627
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 97.149288
iter 10 value 94.060379
iter 20 value 92.191496
iter 30 value 86.822266
iter 40 value 86.494111
iter 50 value 85.240365
iter 60 value 82.593601
iter 70 value 82.255840
iter 80 value 82.252260
final value 82.252060
converged
Fitting Repeat 5
# weights: 507
initial value 104.869061
iter 10 value 94.060828
iter 20 value 94.023476
iter 30 value 87.641923
iter 40 value 87.164836
iter 50 value 85.826418
final value 85.534863
converged
Fitting Repeat 1
# weights: 103
initial value 96.807880
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 101.911390
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.174322
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.123270
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 99.993834
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 123.360471
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 106.934980
iter 10 value 94.360048
final value 94.354396
converged
Fitting Repeat 3
# weights: 305
initial value 98.702431
final value 94.354396
converged
Fitting Repeat 4
# weights: 305
initial value 108.646752
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 109.632165
iter 10 value 94.448052
iter 10 value 94.448052
iter 10 value 94.448052
final value 94.448052
converged
Fitting Repeat 1
# weights: 507
initial value 99.927794
iter 10 value 91.526569
iter 20 value 91.472587
iter 30 value 87.900565
iter 40 value 82.653953
iter 50 value 82.639859
iter 60 value 82.636518
final value 82.636510
converged
Fitting Repeat 2
# weights: 507
initial value 107.029625
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 100.155068
final value 94.354396
converged
Fitting Repeat 4
# weights: 507
initial value 116.042789
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 109.507772
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 96.880678
iter 10 value 94.484408
iter 20 value 94.248217
iter 30 value 88.475483
iter 40 value 88.236379
iter 50 value 84.994045
iter 60 value 84.379382
iter 70 value 84.323637
iter 80 value 84.318805
iter 90 value 84.295809
iter 100 value 84.284852
final value 84.284852
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.563736
iter 10 value 94.174237
iter 20 value 92.756991
iter 30 value 88.614721
iter 40 value 88.127600
iter 50 value 87.258146
iter 60 value 87.084967
iter 70 value 87.076344
iter 80 value 84.620879
iter 90 value 84.444100
iter 100 value 84.435616
final value 84.435616
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 98.969491
iter 10 value 93.664836
iter 20 value 89.390375
iter 30 value 88.101304
iter 40 value 86.083129
iter 50 value 85.851795
iter 60 value 85.796969
final value 85.792440
converged
Fitting Repeat 4
# weights: 103
initial value 100.779774
iter 10 value 94.466389
iter 20 value 94.386964
iter 30 value 94.170745
iter 40 value 93.468657
iter 50 value 88.464454
iter 60 value 86.934647
iter 70 value 86.692511
iter 80 value 86.676544
iter 90 value 86.277999
iter 100 value 86.105579
final value 86.105579
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.025201
iter 10 value 94.443689
iter 20 value 88.579229
iter 30 value 85.099693
iter 40 value 83.561564
iter 50 value 83.442749
iter 60 value 83.385164
iter 70 value 82.431921
iter 80 value 81.702092
iter 90 value 81.643469
iter 100 value 81.641504
final value 81.641504
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.169184
iter 10 value 94.545667
iter 20 value 94.142274
iter 30 value 94.022915
iter 40 value 93.981041
iter 50 value 91.364226
iter 60 value 84.637227
iter 70 value 84.065653
iter 80 value 82.908971
iter 90 value 82.488786
iter 100 value 81.829632
final value 81.829632
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 107.409182
iter 10 value 94.428914
iter 20 value 87.176394
iter 30 value 85.807794
iter 40 value 85.068932
iter 50 value 84.774452
iter 60 value 84.214727
iter 70 value 84.094406
iter 80 value 83.556780
iter 90 value 82.258817
iter 100 value 81.285401
final value 81.285401
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.031781
iter 10 value 94.573493
iter 20 value 94.468781
iter 30 value 91.327720
iter 40 value 86.774038
iter 50 value 84.781399
iter 60 value 82.439322
iter 70 value 81.567131
iter 80 value 81.428712
iter 90 value 81.099538
iter 100 value 80.836403
final value 80.836403
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.992832
iter 10 value 89.398025
iter 20 value 84.806322
iter 30 value 84.019088
iter 40 value 83.880589
iter 50 value 83.854378
iter 60 value 83.679933
iter 70 value 82.665784
iter 80 value 82.072604
iter 90 value 81.082702
iter 100 value 80.675684
final value 80.675684
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 113.350175
iter 10 value 94.430748
iter 20 value 91.586309
iter 30 value 89.035430
iter 40 value 86.750801
iter 50 value 85.135961
iter 60 value 83.519736
iter 70 value 82.185547
iter 80 value 81.552137
iter 90 value 81.286037
iter 100 value 80.698727
final value 80.698727
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.353211
iter 10 value 95.226380
iter 20 value 94.467339
iter 30 value 91.384650
iter 40 value 86.546494
iter 50 value 85.326094
iter 60 value 83.601136
iter 70 value 82.005346
iter 80 value 81.462472
iter 90 value 81.215388
iter 100 value 81.186568
final value 81.186568
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.800894
iter 10 value 89.786833
iter 20 value 87.989106
iter 30 value 85.061324
iter 40 value 84.742657
iter 50 value 83.904794
iter 60 value 83.857960
iter 70 value 83.746109
iter 80 value 82.835871
iter 90 value 80.993290
iter 100 value 80.606429
final value 80.606429
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 131.415647
iter 10 value 95.306677
iter 20 value 88.671385
iter 30 value 85.420063
iter 40 value 82.742244
iter 50 value 81.434216
iter 60 value 81.225547
iter 70 value 80.836792
iter 80 value 80.635094
iter 90 value 80.601363
iter 100 value 80.557076
final value 80.557076
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.105866
iter 10 value 94.491297
iter 20 value 94.118526
iter 30 value 92.749154
iter 40 value 91.900081
iter 50 value 91.062934
iter 60 value 86.779134
iter 70 value 84.497587
iter 80 value 83.260348
iter 90 value 82.477565
iter 100 value 82.114022
final value 82.114022
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.325667
iter 10 value 94.470334
iter 20 value 90.518445
iter 30 value 88.077990
iter 40 value 83.559831
iter 50 value 82.704181
iter 60 value 81.797369
iter 70 value 81.433101
iter 80 value 81.169071
iter 90 value 80.700489
iter 100 value 80.333558
final value 80.333558
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.872531
final value 94.356026
converged
Fitting Repeat 2
# weights: 103
initial value 95.189459
iter 10 value 94.485617
iter 20 value 94.484220
iter 20 value 94.484220
iter 20 value 94.484220
final value 94.484220
converged
Fitting Repeat 3
# weights: 103
initial value 98.246447
final value 94.485860
converged
Fitting Repeat 4
# weights: 103
initial value 101.616336
final value 94.485841
converged
Fitting Repeat 5
# weights: 103
initial value 99.440592
iter 10 value 94.485843
iter 20 value 94.484218
iter 20 value 94.484217
iter 20 value 94.484217
final value 94.484217
converged
Fitting Repeat 1
# weights: 305
initial value 128.230656
iter 10 value 94.489082
iter 20 value 94.484597
iter 30 value 94.027104
iter 40 value 91.977915
iter 50 value 91.963928
iter 60 value 91.550530
iter 70 value 91.549740
iter 80 value 88.700789
iter 90 value 87.689499
iter 100 value 87.686131
final value 87.686131
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.876364
iter 10 value 94.490734
iter 20 value 94.485528
final value 94.485499
converged
Fitting Repeat 3
# weights: 305
initial value 113.200924
iter 10 value 94.489057
iter 20 value 94.407876
iter 30 value 94.105264
iter 40 value 93.995574
iter 50 value 92.997866
iter 60 value 90.112679
iter 70 value 89.967992
iter 80 value 89.966496
iter 90 value 89.961690
iter 100 value 89.925489
final value 89.925489
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.516234
iter 10 value 94.489174
iter 20 value 94.448084
iter 30 value 88.286862
iter 40 value 88.215886
iter 50 value 88.213903
iter 50 value 88.213903
iter 50 value 88.213903
final value 88.213903
converged
Fitting Repeat 5
# weights: 305
initial value 106.946361
iter 10 value 94.498240
iter 20 value 94.374756
iter 30 value 85.944597
iter 40 value 85.182321
iter 50 value 85.176093
iter 60 value 85.173978
iter 70 value 85.171700
iter 80 value 85.168873
final value 85.168852
converged
Fitting Repeat 1
# weights: 507
initial value 97.188122
iter 10 value 94.361902
iter 20 value 94.250252
iter 30 value 92.131196
iter 40 value 91.940809
iter 50 value 91.940534
final value 91.940532
converged
Fitting Repeat 2
# weights: 507
initial value 96.338510
iter 10 value 94.055165
iter 20 value 94.048496
iter 30 value 94.048310
iter 40 value 94.003354
iter 50 value 93.737488
iter 60 value 89.813249
iter 70 value 82.997367
iter 80 value 81.640107
iter 90 value 80.425366
iter 100 value 80.042061
final value 80.042061
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 102.202812
iter 10 value 94.489901
iter 20 value 93.563698
iter 30 value 85.124203
iter 40 value 85.109663
iter 50 value 85.105570
iter 60 value 85.075694
iter 70 value 84.538338
iter 80 value 83.672595
iter 90 value 83.670245
iter 100 value 83.669576
final value 83.669576
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.950160
iter 10 value 94.057619
iter 20 value 94.004081
iter 30 value 94.002992
iter 40 value 94.000563
iter 50 value 93.997024
iter 60 value 93.995493
iter 70 value 93.568199
iter 80 value 91.069288
iter 90 value 90.688439
iter 100 value 90.676289
final value 90.676289
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 96.886580
iter 10 value 94.055790
iter 20 value 94.052884
iter 30 value 93.985918
final value 93.937102
converged
Fitting Repeat 1
# weights: 305
initial value 151.596365
iter 10 value 117.896000
iter 20 value 117.891532
iter 30 value 113.385712
iter 40 value 111.879796
iter 50 value 111.879603
iter 60 value 111.877879
iter 70 value 111.866108
iter 80 value 108.917587
final value 108.915095
converged
Fitting Repeat 2
# weights: 305
initial value 123.716264
iter 10 value 117.895606
iter 20 value 117.855275
iter 30 value 117.530038
iter 40 value 116.570212
iter 50 value 114.921494
iter 60 value 114.736295
final value 114.735115
converged
Fitting Repeat 3
# weights: 305
initial value 118.715819
iter 10 value 117.842488
iter 20 value 107.004245
final value 107.004242
converged
Fitting Repeat 4
# weights: 305
initial value 137.026370
iter 10 value 117.465116
iter 20 value 117.211189
iter 30 value 117.206788
iter 40 value 110.713769
iter 50 value 110.263499
iter 60 value 110.110932
iter 70 value 107.769462
iter 80 value 107.764648
iter 90 value 107.764334
iter 100 value 106.156052
final value 106.156052
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 122.549741
iter 10 value 111.229519
iter 20 value 107.987421
iter 30 value 107.984503
iter 40 value 107.981899
iter 50 value 105.872222
iter 60 value 105.286802
iter 70 value 105.282501
iter 80 value 105.271628
final value 105.266151
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 -- Sun Jan 29 01:01:58 2023
***********************************************
Number of test functions: 8
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures
Number of test functions: 8
Number of errors: 0
Number of failures: 0
Warning messages:
1: The `.data` argument of `add_column()` must have unique names as of tibble
3.0.0.
ℹ Use `.name_repair = "minimal"`.
ℹ The deprecated feature was likely used in the tibble package.
Please report the issue at <https://github.com/tidyverse/tibble/issues>.
2: `repeats` has no meaning for this resampling method.
3: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
53.410 0.867 97.491