Matineh Rahmatbakhsh
| Snapshot Date: 2023-04-10 14:00:05 -0400 (Mon, 10 Apr 2023) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_16 |
| git_last_commit: 3ed3d60 |
| git_last_commit_date: 2023-04-04 18:50:04 -0400 (Tue, 04 Apr 2023) |
| Back to Multiple platform build/check report for BioC 3.16: simplified long |
|
This page was generated on 2023-04-12 11:05:36 -0400 (Wed, 12 Apr 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) | x86_64 | 4.2.3 (2023-03-15) -- "Shortstop Beagle" | 4502 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" | 4282 |
| lconway | macOS 12.5.1 Monterey | x86_64 | 4.2.3 (2023-03-15) -- "Shortstop Beagle" | 4310 |
| 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 926/2183 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.4.3 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.5.1 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| Package: HPiP |
| Version: 1.4.3 |
| Command: F:\biocbuild\bbs-3.16-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.16-bioc\R\library --no-vignettes --timings HPiP_1.4.3.tar.gz |
| StartedAt: 2023-04-11 02:23:20 -0400 (Tue, 11 Apr 2023) |
| EndedAt: 2023-04-11 02:29:09 -0400 (Tue, 11 Apr 2023) |
| EllapsedTime: 349.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.16-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.16-bioc\R\library --no-vignettes --timings HPiP_1.4.3.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.16-bioc/meat/HPiP.Rcheck'
* using R version 4.2.3 (2023-03-15 ucrt)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.4.3'
* 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 whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 29.50 1.14 30.64
FSmethod 29.17 1.45 30.70
corr_plot 29.59 0.83 30.43
pred_ensembel 12.39 0.59 9.81
enrichfindP 0.44 0.09 51.33
* 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 ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
'F:/biocbuild/bbs-3.16-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.16-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.16-bioc/R/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 version 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (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 94.573266
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 104.314352
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 94.700093
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.672109
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 99.550949
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 94.640305
iter 10 value 93.900038
final value 93.900034
converged
Fitting Repeat 2
# weights: 305
initial value 111.250324
iter 10 value 93.938221
final value 93.938175
converged
Fitting Repeat 3
# weights: 305
initial value 97.888603
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 105.247399
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 99.481199
final value 94.443243
converged
Fitting Repeat 1
# weights: 507
initial value 110.358085
iter 10 value 92.738052
iter 20 value 85.562989
final value 85.562956
converged
Fitting Repeat 2
# weights: 507
initial value 109.602117
iter 10 value 83.310067
iter 20 value 83.033315
iter 30 value 82.898112
final value 82.897269
converged
Fitting Repeat 3
# weights: 507
initial value 100.245691
final value 94.400000
converged
Fitting Repeat 4
# weights: 507
initial value 104.922172
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 99.093454
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 98.267501
iter 10 value 94.512716
iter 20 value 94.321262
iter 30 value 84.136900
iter 40 value 83.560599
iter 50 value 82.402469
iter 60 value 81.763738
iter 70 value 81.707387
iter 80 value 81.695418
final value 81.693948
converged
Fitting Repeat 2
# weights: 103
initial value 115.632077
iter 10 value 94.486957
iter 20 value 94.136369
iter 30 value 87.259913
iter 40 value 83.144080
iter 50 value 82.908664
iter 60 value 81.275057
iter 70 value 80.859387
iter 80 value 80.830255
iter 90 value 80.418068
final value 80.394299
converged
Fitting Repeat 3
# weights: 103
initial value 109.265757
iter 10 value 94.485646
iter 20 value 94.427599
iter 30 value 92.950444
iter 40 value 92.198802
iter 50 value 91.376942
iter 60 value 84.312774
iter 70 value 82.405703
iter 80 value 82.144769
iter 90 value 82.128511
iter 100 value 81.056693
final value 81.056693
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 107.228711
iter 10 value 94.630700
iter 20 value 94.272626
iter 30 value 91.643214
iter 40 value 89.803156
iter 50 value 89.722167
iter 60 value 88.169438
iter 70 value 86.480102
iter 80 value 85.897845
iter 90 value 82.440443
iter 100 value 81.741021
final value 81.741021
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 96.463336
iter 10 value 94.451873
iter 20 value 91.308768
iter 30 value 86.070867
iter 40 value 84.823246
iter 50 value 84.097365
iter 60 value 83.629561
iter 70 value 83.148118
iter 80 value 82.310388
iter 90 value 82.172370
iter 100 value 82.132595
final value 82.132595
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.868132
iter 10 value 93.332680
iter 20 value 84.023468
iter 30 value 83.443295
iter 40 value 82.437652
iter 50 value 81.911985
iter 60 value 81.668187
iter 70 value 81.105936
iter 80 value 79.855881
iter 90 value 78.960941
iter 100 value 78.693379
final value 78.693379
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.883744
iter 10 value 94.503006
iter 20 value 87.343563
iter 30 value 84.374426
iter 40 value 82.675909
iter 50 value 80.853901
iter 60 value 79.987760
iter 70 value 79.438789
iter 80 value 79.256027
iter 90 value 79.033356
iter 100 value 78.835109
final value 78.835109
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.529917
iter 10 value 95.220857
iter 20 value 91.995426
iter 30 value 86.429077
iter 40 value 84.361251
iter 50 value 83.118586
iter 60 value 82.989164
iter 70 value 82.904908
iter 80 value 82.152071
iter 90 value 81.848838
iter 100 value 81.797695
final value 81.797695
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.793892
iter 10 value 100.904393
iter 20 value 94.462104
iter 30 value 93.786871
iter 40 value 86.522497
iter 50 value 83.758470
iter 60 value 82.352946
iter 70 value 80.382430
iter 80 value 79.257276
iter 90 value 79.104403
iter 100 value 78.781373
final value 78.781373
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.259369
iter 10 value 94.821399
iter 20 value 94.780834
iter 30 value 88.977119
iter 40 value 83.511461
iter 50 value 83.067275
iter 60 value 81.756002
iter 70 value 81.700151
iter 80 value 81.649264
iter 90 value 81.202112
iter 100 value 80.816228
final value 80.816228
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 123.306775
iter 10 value 94.566719
iter 20 value 86.821386
iter 30 value 82.584438
iter 40 value 79.293732
iter 50 value 79.015337
iter 60 value 78.769164
iter 70 value 78.725879
iter 80 value 78.673701
iter 90 value 78.495880
iter 100 value 78.395735
final value 78.395735
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 121.369896
iter 10 value 94.409015
iter 20 value 85.901995
iter 30 value 82.430415
iter 40 value 81.810507
iter 50 value 80.561580
iter 60 value 79.702507
iter 70 value 79.289191
iter 80 value 79.122897
iter 90 value 78.904732
iter 100 value 78.706597
final value 78.706597
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.077761
iter 10 value 94.420536
iter 20 value 85.449939
iter 30 value 84.229048
iter 40 value 84.091701
iter 50 value 82.992111
iter 60 value 82.526778
iter 70 value 82.449128
iter 80 value 82.175241
iter 90 value 81.674385
iter 100 value 81.003208
final value 81.003208
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.299476
iter 10 value 94.666767
iter 20 value 94.355213
iter 30 value 90.436457
iter 40 value 88.298558
iter 50 value 83.043452
iter 60 value 82.397013
iter 70 value 81.950416
iter 80 value 81.822288
iter 90 value 81.757926
iter 100 value 81.025988
final value 81.025988
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.133670
iter 10 value 91.832534
iter 20 value 85.140676
iter 30 value 83.709518
iter 40 value 82.745104
iter 50 value 82.023197
iter 60 value 81.498343
iter 70 value 80.664940
iter 80 value 80.609759
iter 90 value 80.358578
iter 100 value 79.598452
final value 79.598452
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.252183
final value 94.485647
converged
Fitting Repeat 2
# weights: 103
initial value 95.318978
iter 10 value 94.485910
iter 20 value 94.484254
final value 94.484214
converged
Fitting Repeat 3
# weights: 103
initial value 99.658927
iter 10 value 94.485928
final value 94.484215
converged
Fitting Repeat 4
# weights: 103
initial value 98.704556
final value 94.487276
converged
Fitting Repeat 5
# weights: 103
initial value 95.499313
final value 94.485569
converged
Fitting Repeat 1
# weights: 305
initial value 100.630188
iter 10 value 94.489364
iter 20 value 94.473992
iter 30 value 92.710221
iter 40 value 89.875020
iter 50 value 89.874148
iter 60 value 89.872419
iter 70 value 89.867539
iter 80 value 89.865709
iter 90 value 89.865091
iter 100 value 89.860831
final value 89.860831
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 96.559661
iter 10 value 93.241990
iter 20 value 85.343989
iter 30 value 85.169518
iter 40 value 85.164264
iter 50 value 85.161373
iter 60 value 85.149749
iter 70 value 84.468720
iter 80 value 81.526669
iter 90 value 80.377382
iter 100 value 80.347092
final value 80.347092
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 96.778349
iter 10 value 91.783057
iter 20 value 91.344335
iter 30 value 91.302022
iter 40 value 91.040745
iter 50 value 90.770156
iter 60 value 90.756752
final value 90.730340
converged
Fitting Repeat 4
# weights: 305
initial value 97.029988
iter 10 value 94.489203
iter 20 value 94.378950
iter 30 value 91.518679
iter 40 value 87.985892
iter 50 value 85.883212
iter 60 value 85.849698
final value 85.849357
converged
Fitting Repeat 5
# weights: 305
initial value 102.444487
iter 10 value 94.489290
final value 94.484569
converged
Fitting Repeat 1
# weights: 507
initial value 97.153449
iter 10 value 92.959780
iter 20 value 92.250754
iter 30 value 92.249930
iter 40 value 92.244431
final value 92.244409
converged
Fitting Repeat 2
# weights: 507
initial value 98.031210
iter 10 value 94.492064
iter 20 value 94.482188
iter 30 value 84.829282
iter 40 value 82.899392
iter 50 value 82.868254
iter 60 value 81.647607
final value 81.645660
converged
Fitting Repeat 3
# weights: 507
initial value 108.806608
iter 10 value 94.373750
iter 20 value 94.369778
iter 30 value 94.357379
iter 30 value 94.357378
iter 30 value 94.357378
final value 94.357378
converged
Fitting Repeat 4
# weights: 507
initial value 98.303397
iter 10 value 94.417226
iter 20 value 93.704083
iter 30 value 90.598311
iter 40 value 90.549974
iter 50 value 90.541881
iter 60 value 90.531683
iter 70 value 90.424325
iter 80 value 90.392542
iter 90 value 90.388615
iter 100 value 81.814645
final value 81.814645
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.025055
iter 10 value 94.451821
iter 20 value 94.419513
iter 30 value 86.544415
iter 40 value 84.596326
iter 50 value 82.713758
iter 60 value 81.075229
iter 70 value 80.646510
iter 80 value 80.247589
iter 90 value 80.098692
iter 100 value 80.089028
final value 80.089028
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 108.838356
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 100.118099
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 99.028983
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 97.539046
iter 10 value 88.559556
iter 20 value 83.558327
iter 30 value 83.535476
final value 83.535122
converged
Fitting Repeat 5
# weights: 103
initial value 101.635571
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 102.527409
final value 94.032967
converged
Fitting Repeat 2
# weights: 305
initial value 99.306909
iter 10 value 93.410246
iter 10 value 93.410246
iter 10 value 93.410246
final value 93.410246
converged
Fitting Repeat 3
# weights: 305
initial value 103.010898
final value 94.032967
converged
Fitting Repeat 4
# weights: 305
initial value 97.261173
iter 10 value 93.372145
final value 93.371808
converged
Fitting Repeat 5
# weights: 305
initial value 96.147429
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 99.744032
iter 10 value 94.052911
iter 10 value 94.052910
iter 10 value 94.052910
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 105.966369
iter 10 value 92.127716
iter 20 value 85.460812
iter 30 value 83.139597
iter 40 value 81.105170
iter 50 value 81.061261
iter 60 value 80.989106
final value 80.989094
converged
Fitting Repeat 3
# weights: 507
initial value 96.127132
final value 94.052911
converged
Fitting Repeat 4
# weights: 507
initial value 122.579830
iter 10 value 93.893856
final value 93.893849
converged
Fitting Repeat 5
# weights: 507
initial value 103.859682
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 100.063317
iter 10 value 94.063770
iter 20 value 93.631642
iter 30 value 92.659836
iter 40 value 92.015902
iter 50 value 89.707637
iter 60 value 85.590524
iter 70 value 84.739954
iter 80 value 84.523030
iter 90 value 84.515078
iter 90 value 84.515077
iter 90 value 84.515077
final value 84.515077
converged
Fitting Repeat 2
# weights: 103
initial value 101.907378
iter 10 value 93.995661
iter 20 value 93.486109
iter 30 value 93.467770
iter 40 value 89.480369
iter 50 value 84.909579
iter 60 value 83.716800
iter 70 value 83.558014
final value 83.536732
converged
Fitting Repeat 3
# weights: 103
initial value 98.944182
iter 10 value 94.056504
iter 20 value 93.807400
iter 30 value 93.605351
iter 40 value 92.633835
iter 50 value 87.516668
iter 60 value 87.250240
iter 70 value 86.695944
iter 80 value 85.452157
iter 90 value 84.445532
iter 100 value 84.059731
final value 84.059731
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 107.280429
iter 10 value 94.066744
iter 20 value 91.454692
iter 30 value 90.880962
iter 40 value 90.873340
final value 90.873339
converged
Fitting Repeat 5
# weights: 103
initial value 100.950877
iter 10 value 94.054884
iter 20 value 88.010321
iter 30 value 84.841591
iter 40 value 84.529899
iter 50 value 84.515148
final value 84.515078
converged
Fitting Repeat 1
# weights: 305
initial value 118.664782
iter 10 value 93.743341
iter 20 value 87.238745
iter 30 value 83.142031
iter 40 value 81.182915
iter 50 value 80.601253
iter 60 value 80.369198
iter 70 value 79.507185
iter 80 value 79.423131
iter 90 value 79.299318
iter 100 value 79.283184
final value 79.283184
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 117.774267
iter 10 value 93.949627
iter 20 value 86.436954
iter 30 value 83.211095
iter 40 value 81.163336
iter 50 value 80.224565
iter 60 value 78.415649
iter 70 value 78.127889
iter 80 value 78.025950
iter 90 value 78.006305
iter 100 value 77.986674
final value 77.986674
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 110.115295
iter 10 value 94.013345
iter 20 value 92.429403
iter 30 value 90.945165
iter 40 value 89.882888
iter 50 value 89.726641
iter 60 value 85.589213
iter 70 value 82.280037
iter 80 value 80.560513
iter 90 value 79.795159
iter 100 value 79.537955
final value 79.537955
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.792747
iter 10 value 93.917371
iter 20 value 91.157857
iter 30 value 90.394668
iter 40 value 86.512139
iter 50 value 85.152084
iter 60 value 84.223725
iter 70 value 84.056243
iter 80 value 83.937169
iter 90 value 83.826316
iter 100 value 82.352223
final value 82.352223
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 115.866415
iter 10 value 94.437323
iter 20 value 92.862502
iter 30 value 87.861519
iter 40 value 86.773149
iter 50 value 82.717860
iter 60 value 81.422917
iter 70 value 81.123393
iter 80 value 80.822861
iter 90 value 80.095991
iter 100 value 79.734925
final value 79.734925
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 118.713718
iter 10 value 93.204596
iter 20 value 84.354903
iter 30 value 83.529497
iter 40 value 81.277683
iter 50 value 80.117364
iter 60 value 79.690702
iter 70 value 79.362013
iter 80 value 79.088419
iter 90 value 79.039381
iter 100 value 78.959640
final value 78.959640
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.129619
iter 10 value 91.435446
iter 20 value 86.227465
iter 30 value 84.473532
iter 40 value 83.879628
iter 50 value 83.513365
iter 60 value 83.022811
iter 70 value 80.417469
iter 80 value 79.834045
iter 90 value 79.421178
iter 100 value 78.946435
final value 78.946435
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.175943
iter 10 value 94.180965
iter 20 value 91.706198
iter 30 value 85.936804
iter 40 value 82.545248
iter 50 value 82.021013
iter 60 value 81.706014
iter 70 value 81.536507
iter 80 value 81.319796
iter 90 value 81.004631
iter 100 value 80.732706
final value 80.732706
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.027523
iter 10 value 94.651760
iter 20 value 86.500599
iter 30 value 85.321688
iter 40 value 83.902636
iter 50 value 83.552728
iter 60 value 82.970167
iter 70 value 79.890877
iter 80 value 78.894889
iter 90 value 78.282441
iter 100 value 78.168404
final value 78.168404
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.535059
iter 10 value 90.157021
iter 20 value 87.714845
iter 30 value 86.081537
iter 40 value 83.690767
iter 50 value 83.533641
iter 60 value 83.470467
iter 70 value 83.055653
iter 80 value 80.652089
iter 90 value 79.689989
iter 100 value 79.263625
final value 79.263625
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.656362
iter 10 value 93.308474
iter 20 value 93.307507
iter 30 value 92.979649
iter 40 value 92.890789
iter 50 value 92.890547
iter 60 value 92.890005
iter 70 value 91.637152
iter 80 value 91.078919
iter 90 value 91.072263
final value 91.072256
converged
Fitting Repeat 2
# weights: 103
initial value 111.469414
final value 94.034391
converged
Fitting Repeat 3
# weights: 103
initial value 94.727991
final value 94.054599
converged
Fitting Repeat 4
# weights: 103
initial value 99.837809
final value 94.054524
converged
Fitting Repeat 5
# weights: 103
initial value 96.347013
final value 94.054531
converged
Fitting Repeat 1
# weights: 305
initial value 97.818745
iter 10 value 94.054541
iter 20 value 90.857411
iter 30 value 81.900186
iter 40 value 81.686862
iter 50 value 80.842541
iter 60 value 77.443942
iter 70 value 77.349691
iter 80 value 77.337456
iter 90 value 77.336191
iter 100 value 77.335160
final value 77.335160
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.577657
iter 10 value 93.719077
iter 20 value 93.418798
iter 30 value 85.368819
iter 40 value 84.188605
iter 50 value 81.026667
iter 60 value 80.758524
iter 70 value 80.586887
iter 80 value 80.583652
iter 90 value 80.581478
final value 80.575845
converged
Fitting Repeat 3
# weights: 305
initial value 129.397510
iter 10 value 94.039460
iter 20 value 94.033770
iter 30 value 93.410568
iter 40 value 91.395674
iter 50 value 90.410701
final value 90.410456
converged
Fitting Repeat 4
# weights: 305
initial value 110.087641
iter 10 value 94.057419
iter 20 value 93.518185
iter 30 value 84.800193
iter 40 value 83.790984
iter 50 value 83.568480
final value 83.567657
converged
Fitting Repeat 5
# weights: 305
initial value 106.886647
iter 10 value 94.058546
iter 20 value 94.053053
iter 30 value 90.834850
iter 40 value 82.066017
iter 50 value 81.897517
iter 60 value 81.896344
iter 70 value 81.734701
iter 80 value 80.811818
iter 90 value 80.805796
iter 100 value 80.805685
final value 80.805685
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.822595
iter 10 value 92.304732
iter 20 value 85.319805
iter 30 value 85.249080
iter 40 value 85.248525
iter 50 value 85.169536
iter 60 value 85.151217
iter 70 value 84.988446
iter 80 value 84.467723
iter 90 value 83.187616
iter 100 value 82.230634
final value 82.230634
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.438513
iter 10 value 93.722513
iter 20 value 93.418341
iter 30 value 93.417347
iter 40 value 93.414908
iter 50 value 90.196547
iter 60 value 90.105840
iter 70 value 90.104981
iter 80 value 90.102521
iter 90 value 90.057769
iter 100 value 90.051862
final value 90.051862
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 94.667940
iter 10 value 94.041839
iter 20 value 93.707255
iter 30 value 82.510048
iter 40 value 82.253031
iter 50 value 82.252630
iter 60 value 80.016713
iter 70 value 77.386386
iter 80 value 77.080670
iter 90 value 76.740467
iter 100 value 76.673382
final value 76.673382
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 100.360600
iter 10 value 94.061581
iter 20 value 85.976328
iter 30 value 81.892358
iter 40 value 81.869751
iter 50 value 81.869325
iter 60 value 81.685963
iter 70 value 80.475026
iter 80 value 79.720888
iter 90 value 77.573640
iter 100 value 76.814106
final value 76.814106
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 96.663349
iter 10 value 93.721839
iter 20 value 93.674219
iter 30 value 93.398729
iter 40 value 89.946415
iter 50 value 89.852312
final value 89.851892
converged
Fitting Repeat 1
# weights: 103
initial value 101.372750
final value 94.144481
converged
Fitting Repeat 2
# weights: 103
initial value 96.606872
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 94.994664
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.093793
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 101.507151
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 110.554973
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 96.954906
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 100.052472
final value 94.484209
converged
Fitting Repeat 4
# weights: 305
initial value 115.854621
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 103.908626
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 105.721294
iter 10 value 94.183362
iter 20 value 92.397087
iter 30 value 89.406554
iter 40 value 84.483613
iter 50 value 84.181446
iter 60 value 84.012916
iter 70 value 83.957922
iter 80 value 83.478859
iter 90 value 83.475835
final value 83.475819
converged
Fitting Repeat 2
# weights: 507
initial value 114.899368
iter 10 value 94.470068
final value 94.470000
converged
Fitting Repeat 3
# weights: 507
initial value 102.196202
iter 10 value 94.483825
final value 94.483812
converged
Fitting Repeat 4
# weights: 507
initial value 98.403644
iter 10 value 93.868520
final value 93.783647
converged
Fitting Repeat 5
# weights: 507
initial value 95.457126
iter 10 value 93.834997
iter 20 value 92.922272
final value 92.919320
converged
Fitting Repeat 1
# weights: 103
initial value 105.082958
iter 10 value 94.481296
iter 20 value 93.872548
iter 30 value 84.848995
iter 40 value 84.557640
iter 50 value 84.425985
iter 60 value 83.953585
iter 70 value 82.530402
iter 80 value 81.928212
iter 90 value 81.756631
iter 100 value 81.441239
final value 81.441239
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.007040
iter 10 value 94.474755
iter 20 value 93.876312
iter 30 value 92.418161
iter 40 value 92.358842
iter 50 value 87.739198
iter 60 value 84.923161
iter 70 value 84.280200
iter 80 value 83.045906
iter 90 value 81.985082
iter 100 value 81.638946
final value 81.638946
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.180514
iter 10 value 94.488788
iter 20 value 94.388214
iter 30 value 92.152679
iter 40 value 83.998353
iter 50 value 83.067055
iter 60 value 82.124183
iter 70 value 81.631878
iter 80 value 81.422673
iter 90 value 81.297264
iter 100 value 81.265268
final value 81.265268
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 106.196991
iter 10 value 93.518660
iter 20 value 84.854046
iter 30 value 84.635976
iter 40 value 84.002016
iter 50 value 83.697868
iter 60 value 83.580622
final value 83.580428
converged
Fitting Repeat 5
# weights: 103
initial value 96.718542
iter 10 value 88.235643
iter 20 value 86.377586
iter 30 value 85.062634
iter 40 value 84.271717
iter 50 value 83.341634
iter 60 value 83.162820
iter 70 value 83.110345
final value 83.110327
converged
Fitting Repeat 1
# weights: 305
initial value 119.308793
iter 10 value 94.524074
iter 20 value 94.221546
iter 30 value 91.468896
iter 40 value 88.304921
iter 50 value 86.311466
iter 60 value 84.696859
iter 70 value 82.240867
iter 80 value 81.934263
iter 90 value 81.556616
iter 100 value 81.051710
final value 81.051710
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.837766
iter 10 value 94.480423
iter 20 value 86.017928
iter 30 value 84.275391
iter 40 value 82.939460
iter 50 value 82.479622
iter 60 value 82.064096
iter 70 value 81.762895
iter 80 value 81.515415
iter 90 value 81.459990
iter 100 value 81.405321
final value 81.405321
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.400196
iter 10 value 94.497651
iter 20 value 88.087114
iter 30 value 85.383760
iter 40 value 84.163032
iter 50 value 82.349481
iter 60 value 82.034145
iter 70 value 81.863361
iter 80 value 81.769473
iter 90 value 81.547001
iter 100 value 81.116373
final value 81.116373
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 119.910561
iter 10 value 94.530758
iter 20 value 94.485647
iter 30 value 94.292235
iter 40 value 87.692797
iter 50 value 85.516168
iter 60 value 84.359206
iter 70 value 83.431653
iter 80 value 83.194742
iter 90 value 83.132856
iter 100 value 82.988815
final value 82.988815
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.402951
iter 10 value 94.363357
iter 20 value 88.446919
iter 30 value 84.842557
iter 40 value 84.445530
iter 50 value 83.978199
iter 60 value 81.653665
iter 70 value 80.798357
iter 80 value 80.428619
iter 90 value 80.210786
iter 100 value 80.150358
final value 80.150358
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 133.543542
iter 10 value 100.408038
iter 20 value 88.956998
iter 30 value 87.083582
iter 40 value 86.851159
iter 50 value 86.640666
iter 60 value 83.591071
iter 70 value 83.014722
iter 80 value 82.610313
iter 90 value 82.077333
iter 100 value 81.747370
final value 81.747370
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 124.173542
iter 10 value 101.090978
iter 20 value 99.511515
iter 30 value 90.665019
iter 40 value 83.398430
iter 50 value 81.128944
iter 60 value 80.557177
iter 70 value 80.111168
iter 80 value 79.840125
iter 90 value 79.745553
iter 100 value 79.698482
final value 79.698482
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.656203
iter 10 value 95.585425
iter 20 value 94.604151
iter 30 value 91.034329
iter 40 value 88.759047
iter 50 value 84.614614
iter 60 value 84.168962
iter 70 value 83.892599
iter 80 value 83.797799
iter 90 value 83.431584
iter 100 value 82.775433
final value 82.775433
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.616811
iter 10 value 92.090071
iter 20 value 86.231904
iter 30 value 85.253956
iter 40 value 85.020401
iter 50 value 83.495041
iter 60 value 82.295245
iter 70 value 81.011718
iter 80 value 80.592003
iter 90 value 80.412949
iter 100 value 80.143735
final value 80.143735
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.756988
iter 10 value 96.450325
iter 20 value 87.273542
iter 30 value 86.150819
iter 40 value 85.712539
iter 50 value 84.480526
iter 60 value 83.948348
iter 70 value 83.680243
iter 80 value 83.600111
iter 90 value 83.069261
iter 100 value 81.944336
final value 81.944336
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 104.596915
final value 94.485849
converged
Fitting Repeat 2
# weights: 103
initial value 101.521805
final value 94.485852
converged
Fitting Repeat 3
# weights: 103
initial value 100.574014
final value 94.485809
converged
Fitting Repeat 4
# weights: 103
initial value 97.419093
final value 94.486111
converged
Fitting Repeat 5
# weights: 103
initial value 94.831242
final value 94.486054
converged
Fitting Repeat 1
# weights: 305
initial value 101.778197
iter 10 value 94.489190
iter 20 value 94.087257
iter 30 value 86.480756
iter 40 value 86.451662
final value 86.451617
converged
Fitting Repeat 2
# weights: 305
initial value 96.839673
iter 10 value 94.359243
iter 20 value 94.354629
iter 30 value 94.320622
iter 40 value 87.962362
iter 50 value 83.603940
iter 60 value 83.586605
final value 83.586536
converged
Fitting Repeat 3
# weights: 305
initial value 97.796756
iter 10 value 94.359266
iter 20 value 94.149324
final value 94.145623
converged
Fitting Repeat 4
# weights: 305
initial value 95.355244
iter 10 value 94.487795
iter 20 value 94.471941
final value 94.275641
converged
Fitting Repeat 5
# weights: 305
initial value 99.662850
iter 10 value 94.488626
iter 20 value 94.356105
iter 30 value 93.114300
iter 40 value 86.885390
iter 50 value 86.856442
iter 50 value 86.856442
iter 50 value 86.856442
final value 86.856442
converged
Fitting Repeat 1
# weights: 507
initial value 120.677645
iter 10 value 94.362309
iter 20 value 94.354631
iter 30 value 87.065518
iter 40 value 84.665401
iter 50 value 83.917797
iter 60 value 83.887676
iter 70 value 83.875608
iter 80 value 81.247783
iter 90 value 80.485751
iter 100 value 80.483857
final value 80.483857
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.269048
iter 10 value 94.152844
iter 20 value 94.151738
final value 94.151732
converged
Fitting Repeat 3
# weights: 507
initial value 102.691630
iter 10 value 94.362342
iter 20 value 94.355222
iter 30 value 94.353013
iter 40 value 91.309374
iter 50 value 83.953598
iter 60 value 80.238546
iter 70 value 79.927602
iter 80 value 79.918066
iter 90 value 79.916025
iter 100 value 79.914840
final value 79.914840
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 96.627765
iter 10 value 94.492248
iter 20 value 94.484307
iter 30 value 93.783842
iter 40 value 86.922150
iter 50 value 85.216466
iter 60 value 85.178415
final value 85.178160
converged
Fitting Repeat 5
# weights: 507
initial value 104.054359
iter 10 value 94.362886
iter 20 value 94.357262
iter 30 value 93.987679
iter 40 value 93.898081
iter 50 value 85.244332
iter 60 value 85.109992
iter 70 value 85.051557
final value 85.050454
converged
Fitting Repeat 1
# weights: 103
initial value 103.345577
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.842621
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.982551
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.728522
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.337410
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 101.377930
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 119.824510
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 107.151566
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 105.301085
iter 10 value 94.112987
final value 94.112903
converged
Fitting Repeat 5
# weights: 305
initial value 108.705272
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 95.226429
final value 94.264858
converged
Fitting Repeat 2
# weights: 507
initial value 95.399623
iter 10 value 89.757727
iter 20 value 85.680401
iter 30 value 84.041609
final value 84.001644
converged
Fitting Repeat 3
# weights: 507
initial value 96.498941
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 114.900877
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 96.619420
iter 10 value 93.938043
final value 93.926252
converged
Fitting Repeat 1
# weights: 103
initial value 102.392456
iter 10 value 94.488535
iter 20 value 94.444040
iter 30 value 94.303847
iter 40 value 87.448160
iter 50 value 84.033960
iter 60 value 83.561971
iter 70 value 83.514423
iter 80 value 83.417466
iter 90 value 82.300776
iter 100 value 82.069062
final value 82.069062
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.856104
iter 10 value 94.486970
iter 20 value 94.278477
iter 30 value 94.157426
iter 40 value 90.397624
iter 50 value 88.627890
iter 60 value 85.933271
iter 70 value 85.099407
iter 80 value 84.976319
iter 90 value 84.555058
iter 100 value 84.445490
final value 84.445490
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.926839
iter 10 value 94.553339
iter 20 value 91.691995
iter 30 value 84.976308
iter 40 value 84.859212
iter 50 value 84.463907
iter 60 value 84.441676
final value 84.441670
converged
Fitting Repeat 4
# weights: 103
initial value 98.435526
iter 10 value 94.489410
iter 20 value 87.039884
iter 30 value 85.768310
iter 40 value 85.529509
iter 50 value 84.607224
iter 60 value 84.442108
final value 84.441669
converged
Fitting Repeat 5
# weights: 103
initial value 96.582157
iter 10 value 94.488312
iter 20 value 94.486547
iter 30 value 86.554038
iter 40 value 84.125988
iter 50 value 83.493898
iter 60 value 83.317367
iter 70 value 82.754465
iter 80 value 82.173529
iter 90 value 82.060326
iter 100 value 82.032105
final value 82.032105
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 103.676474
iter 10 value 94.446079
iter 20 value 87.531385
iter 30 value 83.863469
iter 40 value 82.344402
iter 50 value 81.882070
iter 60 value 81.720260
iter 70 value 81.626900
iter 80 value 81.452650
iter 90 value 81.307393
iter 100 value 81.289498
final value 81.289498
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.971870
iter 10 value 94.701941
iter 20 value 87.388270
iter 30 value 85.929504
iter 40 value 84.717927
iter 50 value 83.232298
iter 60 value 81.566329
iter 70 value 81.487517
iter 80 value 81.405103
iter 90 value 81.259183
iter 100 value 81.172525
final value 81.172525
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 114.147919
iter 10 value 94.387706
iter 20 value 93.910307
iter 30 value 85.932938
iter 40 value 83.052449
iter 50 value 82.516468
iter 60 value 81.904630
iter 70 value 81.628975
iter 80 value 81.372251
iter 90 value 81.224813
iter 100 value 81.201921
final value 81.201921
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 113.008937
iter 10 value 88.975949
iter 20 value 85.115174
iter 30 value 84.978006
iter 40 value 84.450116
iter 50 value 84.100973
iter 60 value 84.028284
iter 70 value 83.817509
iter 80 value 82.622312
iter 90 value 81.592541
iter 100 value 81.475023
final value 81.475023
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.653892
iter 10 value 94.455837
iter 20 value 88.882316
iter 30 value 85.015304
iter 40 value 83.980955
iter 50 value 82.924343
iter 60 value 82.009977
iter 70 value 81.370990
iter 80 value 81.091390
iter 90 value 81.033541
iter 100 value 80.970946
final value 80.970946
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.618617
iter 10 value 93.448647
iter 20 value 87.810666
iter 30 value 84.286306
iter 40 value 83.265826
iter 50 value 82.356048
iter 60 value 81.548830
iter 70 value 81.310167
iter 80 value 81.079411
iter 90 value 80.958283
iter 100 value 80.917242
final value 80.917242
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 118.235368
iter 10 value 93.433088
iter 20 value 86.276629
iter 30 value 85.236448
iter 40 value 82.981152
iter 50 value 81.760775
iter 60 value 81.455074
iter 70 value 80.789151
iter 80 value 80.573903
iter 90 value 80.474106
iter 100 value 80.424088
final value 80.424088
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.152486
iter 10 value 94.099854
iter 20 value 87.937258
iter 30 value 85.256632
iter 40 value 84.278888
iter 50 value 83.532248
iter 60 value 82.970368
iter 70 value 82.543932
iter 80 value 82.298198
iter 90 value 82.154903
iter 100 value 82.078181
final value 82.078181
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.010064
iter 10 value 94.441348
iter 20 value 89.391445
iter 30 value 84.519772
iter 40 value 82.369459
iter 50 value 81.356838
iter 60 value 80.708761
iter 70 value 80.541840
iter 80 value 80.400767
iter 90 value 80.194590
iter 100 value 80.083339
final value 80.083339
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.264038
iter 10 value 91.217530
iter 20 value 87.154501
iter 30 value 84.266187
iter 40 value 82.756126
iter 50 value 82.222700
iter 60 value 81.958142
iter 70 value 81.805349
iter 80 value 81.459398
iter 90 value 80.911796
iter 100 value 80.601946
final value 80.601946
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.623334
final value 94.485791
converged
Fitting Repeat 2
# weights: 103
initial value 100.982172
final value 94.486044
converged
Fitting Repeat 3
# weights: 103
initial value 97.923962
final value 94.485768
converged
Fitting Repeat 4
# weights: 103
initial value 95.628117
iter 10 value 94.114821
iter 20 value 93.439848
iter 30 value 93.425700
iter 40 value 93.228828
final value 93.210254
converged
Fitting Repeat 5
# weights: 103
initial value 98.446431
iter 10 value 94.048616
iter 20 value 92.346607
iter 30 value 90.687369
iter 40 value 90.599556
iter 50 value 90.579847
iter 60 value 90.414609
iter 70 value 90.400542
final value 90.399160
converged
Fitting Repeat 1
# weights: 305
initial value 99.481408
iter 10 value 94.488195
iter 20 value 94.448626
iter 30 value 84.060219
iter 40 value 84.054312
iter 50 value 84.023905
iter 50 value 84.023905
iter 50 value 84.023905
final value 84.023905
converged
Fitting Repeat 2
# weights: 305
initial value 103.482601
iter 10 value 94.117790
iter 20 value 94.115702
iter 30 value 91.754554
iter 40 value 84.212517
iter 50 value 83.363984
iter 60 value 83.241976
iter 70 value 83.136729
iter 80 value 82.732861
iter 90 value 82.718095
iter 100 value 82.717535
final value 82.717535
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.492160
iter 10 value 91.537094
iter 20 value 91.531255
iter 30 value 91.528657
iter 40 value 91.528176
iter 50 value 91.528109
iter 60 value 87.252283
iter 70 value 86.169593
iter 80 value 85.986507
final value 85.985930
converged
Fitting Repeat 4
# weights: 305
initial value 96.473505
iter 10 value 94.118121
iter 20 value 94.070410
iter 30 value 84.723963
iter 40 value 84.002028
iter 50 value 83.938802
iter 60 value 83.475190
iter 70 value 82.329856
iter 80 value 81.495534
iter 90 value 81.457992
iter 100 value 81.457757
final value 81.457757
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.972755
iter 10 value 94.489220
iter 20 value 94.484245
iter 30 value 92.246640
iter 40 value 91.399345
iter 50 value 91.237921
iter 60 value 91.220306
iter 70 value 90.997465
iter 80 value 82.838002
iter 90 value 82.373743
iter 100 value 82.368833
final value 82.368833
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 111.812608
iter 10 value 94.492289
iter 20 value 94.380345
iter 30 value 87.601304
iter 40 value 83.973249
iter 50 value 83.615173
iter 60 value 83.598569
iter 70 value 83.598480
iter 80 value 83.598305
final value 83.598256
converged
Fitting Repeat 2
# weights: 507
initial value 96.877292
iter 10 value 94.121499
iter 20 value 94.115521
iter 30 value 94.061873
iter 40 value 86.777704
iter 50 value 83.345158
iter 60 value 82.898098
iter 70 value 82.886599
final value 82.886342
converged
Fitting Repeat 3
# weights: 507
initial value 118.478783
iter 10 value 94.120722
iter 20 value 94.115761
iter 30 value 91.176112
iter 40 value 86.560777
iter 50 value 86.462826
iter 60 value 86.276653
iter 70 value 83.999013
iter 80 value 80.964875
iter 90 value 79.514944
iter 100 value 79.169884
final value 79.169884
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.819350
iter 10 value 94.489792
iter 20 value 94.485829
iter 30 value 94.481995
iter 40 value 94.478719
final value 94.478676
converged
Fitting Repeat 5
# weights: 507
initial value 102.642907
iter 10 value 93.707945
iter 20 value 93.704977
iter 30 value 86.768302
iter 40 value 86.756831
iter 50 value 86.754531
iter 60 value 86.249202
iter 70 value 85.670662
iter 80 value 84.657568
iter 90 value 82.031077
iter 100 value 81.688060
final value 81.688060
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.131058
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 100.361564
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 94.937518
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 95.462295
iter 10 value 93.705049
iter 20 value 89.927487
iter 30 value 89.037743
iter 40 value 88.983549
iter 40 value 88.983548
iter 40 value 88.983548
final value 88.983548
converged
Fitting Repeat 5
# weights: 103
initial value 95.746444
final value 93.921212
converged
Fitting Repeat 1
# weights: 305
initial value 102.301199
iter 10 value 90.053578
iter 20 value 85.027179
iter 30 value 84.992192
iter 40 value 84.985129
iter 50 value 84.985087
final value 84.985079
converged
Fitting Repeat 2
# weights: 305
initial value 103.715018
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.986831
final value 93.915746
converged
Fitting Repeat 4
# weights: 305
initial value 105.591654
final value 93.915746
converged
Fitting Repeat 5
# weights: 305
initial value 105.380384
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 106.829997
iter 10 value 93.915746
iter 10 value 93.915746
iter 10 value 93.915746
final value 93.915746
converged
Fitting Repeat 2
# weights: 507
initial value 104.624647
iter 10 value 93.603957
iter 20 value 88.341731
iter 30 value 87.950189
final value 87.950034
converged
Fitting Repeat 3
# weights: 507
initial value 101.985078
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 108.573241
iter 10 value 93.672974
iter 10 value 93.672974
iter 10 value 93.672973
final value 93.672973
converged
Fitting Repeat 5
# weights: 507
initial value 103.065859
final value 93.915746
converged
Fitting Repeat 1
# weights: 103
initial value 107.246054
iter 10 value 94.055233
iter 20 value 93.872721
iter 30 value 93.697206
iter 40 value 93.655867
iter 50 value 93.369946
iter 60 value 91.328817
iter 70 value 90.520636
iter 80 value 89.291957
iter 90 value 87.953444
iter 100 value 87.032261
final value 87.032261
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 103.963859
iter 10 value 93.938988
iter 20 value 91.694450
iter 30 value 87.614232
iter 40 value 87.151295
iter 50 value 86.580639
iter 60 value 86.576640
final value 86.576637
converged
Fitting Repeat 3
# weights: 103
initial value 97.056953
iter 10 value 94.060444
iter 20 value 92.245178
iter 30 value 88.147823
iter 40 value 87.295158
iter 50 value 86.650991
iter 60 value 85.372716
iter 70 value 84.949695
iter 80 value 84.650052
iter 90 value 84.635820
final value 84.635062
converged
Fitting Repeat 4
# weights: 103
initial value 106.286624
iter 10 value 94.015773
iter 20 value 93.705088
iter 30 value 89.078079
iter 40 value 88.390353
iter 50 value 86.948227
iter 60 value 85.725692
iter 70 value 85.040830
iter 80 value 84.957870
final value 84.955604
converged
Fitting Repeat 5
# weights: 103
initial value 97.984902
iter 10 value 93.975406
iter 20 value 93.212342
iter 30 value 91.540530
iter 40 value 89.756619
iter 50 value 87.042950
iter 60 value 86.378240
iter 70 value 85.280721
iter 80 value 84.978612
iter 90 value 84.955786
final value 84.955604
converged
Fitting Repeat 1
# weights: 305
initial value 103.213477
iter 10 value 94.022021
iter 20 value 88.134594
iter 30 value 87.519503
iter 40 value 86.841002
iter 50 value 86.553793
iter 60 value 86.401749
iter 70 value 85.643281
iter 80 value 85.363649
iter 90 value 85.240896
iter 100 value 84.866929
final value 84.866929
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.214936
iter 10 value 94.059021
iter 20 value 93.708417
iter 30 value 93.634476
iter 40 value 92.385451
iter 50 value 88.718888
iter 60 value 85.086073
iter 70 value 83.915689
iter 80 value 83.494526
iter 90 value 83.383934
iter 100 value 83.364053
final value 83.364053
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 111.118547
iter 10 value 94.054267
iter 20 value 88.201745
iter 30 value 86.131124
iter 40 value 84.681264
iter 50 value 84.296598
iter 60 value 84.161053
iter 70 value 83.860759
iter 80 value 83.653800
iter 90 value 83.614956
iter 100 value 83.543429
final value 83.543429
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.270541
iter 10 value 94.089503
iter 20 value 89.331588
iter 30 value 88.312528
iter 40 value 86.957934
iter 50 value 86.461437
iter 60 value 86.427506
iter 70 value 86.234288
iter 80 value 85.854022
iter 90 value 85.675956
iter 100 value 85.657155
final value 85.657155
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.585130
iter 10 value 94.074936
iter 20 value 93.391122
iter 30 value 89.382556
iter 40 value 87.613384
iter 50 value 87.089638
iter 60 value 86.720631
iter 70 value 85.935472
iter 80 value 84.774414
iter 90 value 84.353233
iter 100 value 84.113722
final value 84.113722
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.890877
iter 10 value 94.366133
iter 20 value 89.658196
iter 30 value 88.321393
iter 40 value 85.936420
iter 50 value 85.299109
iter 60 value 84.095952
iter 70 value 83.725230
iter 80 value 83.471898
iter 90 value 83.343822
iter 100 value 83.185759
final value 83.185759
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.718862
iter 10 value 94.082134
iter 20 value 91.426846
iter 30 value 88.318693
iter 40 value 87.978345
iter 50 value 86.815922
iter 60 value 85.896945
iter 70 value 85.407565
iter 80 value 85.019029
iter 90 value 84.883676
iter 100 value 84.528475
final value 84.528475
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.939182
iter 10 value 94.417320
iter 20 value 90.854098
iter 30 value 88.020479
iter 40 value 86.890943
iter 50 value 85.394287
iter 60 value 84.761807
iter 70 value 83.838310
iter 80 value 83.523183
iter 90 value 83.188074
iter 100 value 83.060910
final value 83.060910
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.879282
iter 10 value 94.065017
iter 20 value 93.487397
iter 30 value 89.727134
iter 40 value 86.647694
iter 50 value 85.327711
iter 60 value 84.134150
iter 70 value 83.903018
iter 80 value 83.847263
iter 90 value 83.815302
iter 100 value 83.769877
final value 83.769877
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.494959
iter 10 value 94.108729
iter 20 value 93.965420
iter 30 value 91.439739
iter 40 value 88.797631
iter 50 value 86.445543
iter 60 value 85.310728
iter 70 value 85.104863
iter 80 value 84.652669
iter 90 value 83.793121
iter 100 value 83.240218
final value 83.240218
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.285878
final value 94.054573
converged
Fitting Repeat 2
# weights: 103
initial value 101.284344
final value 94.054404
converged
Fitting Repeat 3
# weights: 103
initial value 95.988043
final value 94.054871
converged
Fitting Repeat 4
# weights: 103
initial value 101.632271
final value 94.054388
converged
Fitting Repeat 5
# weights: 103
initial value 97.223221
iter 10 value 94.054471
iter 20 value 94.052968
final value 94.052913
converged
Fitting Repeat 1
# weights: 305
initial value 94.968102
iter 10 value 94.057770
iter 20 value 94.049223
iter 30 value 93.542617
iter 40 value 92.830260
final value 92.830211
converged
Fitting Repeat 2
# weights: 305
initial value 95.342869
iter 10 value 93.930452
iter 20 value 93.919643
iter 30 value 93.912277
iter 40 value 92.150425
iter 50 value 90.373566
iter 60 value 89.919499
iter 70 value 89.902779
iter 80 value 87.878431
iter 90 value 85.954428
iter 100 value 83.935941
final value 83.935941
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 98.758367
iter 10 value 93.920644
iter 20 value 93.916962
iter 30 value 93.915981
iter 30 value 93.915981
final value 93.915981
converged
Fitting Repeat 4
# weights: 305
initial value 98.091696
iter 10 value 93.920550
iter 20 value 93.869549
iter 30 value 93.607126
iter 40 value 93.604941
final value 93.604886
converged
Fitting Repeat 5
# weights: 305
initial value 98.659688
iter 10 value 93.920656
iter 20 value 93.915972
iter 30 value 89.514732
iter 40 value 89.482185
final value 89.482145
converged
Fitting Repeat 1
# weights: 507
initial value 104.258642
iter 10 value 94.060097
iter 20 value 94.052890
iter 30 value 91.287060
iter 40 value 87.532841
final value 87.532818
converged
Fitting Repeat 2
# weights: 507
initial value 99.748253
iter 10 value 88.713021
iter 20 value 87.568783
iter 30 value 87.521965
iter 40 value 87.426044
iter 50 value 87.421572
iter 60 value 87.419092
iter 70 value 87.418219
iter 80 value 87.417444
iter 90 value 87.415008
iter 100 value 87.413017
final value 87.413017
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.900930
iter 10 value 93.923582
iter 20 value 93.759836
iter 30 value 93.606621
final value 93.604748
converged
Fitting Repeat 4
# weights: 507
initial value 100.618313
iter 10 value 94.061330
iter 20 value 94.053167
final value 94.052935
converged
Fitting Repeat 5
# weights: 507
initial value 100.190778
iter 10 value 94.053684
iter 20 value 94.053142
iter 30 value 93.669212
iter 40 value 90.744243
iter 50 value 88.894156
iter 60 value 88.880289
iter 70 value 88.879392
iter 70 value 88.879392
final value 88.879392
converged
Fitting Repeat 1
# weights: 507
initial value 140.607660
iter 10 value 118.210134
iter 20 value 117.786028
iter 30 value 117.472341
iter 40 value 111.922382
iter 50 value 109.334922
iter 60 value 105.625818
iter 70 value 102.652996
iter 80 value 101.795688
iter 90 value 101.339356
iter 100 value 100.678881
final value 100.678881
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 155.078731
iter 10 value 119.313158
iter 20 value 117.732471
iter 30 value 115.714194
iter 40 value 106.923311
iter 50 value 104.281894
iter 60 value 103.764592
iter 70 value 103.313442
iter 80 value 102.856795
iter 90 value 102.541994
iter 100 value 102.359773
final value 102.359773
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 148.934111
iter 10 value 120.889764
iter 20 value 118.702381
iter 30 value 114.946195
iter 40 value 106.473457
iter 50 value 103.745547
iter 60 value 102.436609
iter 70 value 101.705807
iter 80 value 100.798887
iter 90 value 100.494877
iter 100 value 100.419169
final value 100.419169
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 140.006047
iter 10 value 117.925160
iter 20 value 111.653875
iter 30 value 108.443495
iter 40 value 107.153048
iter 50 value 105.258391
iter 60 value 103.925885
iter 70 value 103.049299
iter 80 value 101.749713
iter 90 value 101.312280
iter 100 value 101.124726
final value 101.124726
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 129.484670
iter 10 value 115.605488
iter 20 value 108.115537
iter 30 value 105.133350
iter 40 value 102.154535
iter 50 value 101.836569
iter 60 value 101.517386
iter 70 value 101.206160
iter 80 value 101.052128
iter 90 value 100.972597
iter 100 value 100.694059
final value 100.694059
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Tue Apr 11 02:28:58 2023
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
41.18 1.42 83.29
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 29.17 | 1.45 | 30.70 | |
| FreqInteractors | 0.32 | 0.00 | 0.35 | |
| calculateAAC | 0.03 | 0.02 | 0.05 | |
| calculateAutocor | 0.35 | 0.07 | 0.47 | |
| calculateCTDC | 0.08 | 0.00 | 0.08 | |
| calculateCTDD | 0.71 | 0.08 | 0.81 | |
| calculateCTDT | 0.24 | 0.01 | 0.25 | |
| calculateCTriad | 0.39 | 0.05 | 0.44 | |
| calculateDC | 0.08 | 0.00 | 0.08 | |
| calculateF | 0.38 | 0.00 | 0.37 | |
| calculateKSAAP | 0.11 | 0.00 | 0.11 | |
| calculateQD_Sm | 1.58 | 0.12 | 1.70 | |
| calculateTC | 1.67 | 0.07 | 1.74 | |
| calculateTC_Sm | 0.31 | 0.01 | 0.33 | |
| corr_plot | 29.59 | 0.83 | 30.43 | |
| enrichfindP | 0.44 | 0.09 | 51.33 | |
| enrichfind_hp | 0.03 | 0.02 | 3.03 | |
| enrichplot | 0.3 | 0.0 | 0.3 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.03 | 0.02 | 2.41 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.08 | 0.00 | 0.13 | |
| pred_ensembel | 12.39 | 0.59 | 9.81 | |
| var_imp | 29.50 | 1.14 | 30.64 | |