Matineh Rahmatbakhsh
| Snapshot Date: 2023-10-15 14:00:13 -0400 (Sun, 15 Oct 2023) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_17 |
| git_last_commit: 5d1c297 |
| git_last_commit_date: 2023-04-25 11:32:43 -0400 (Tue, 25 Apr 2023) |
| Back to Multiple platform build/check report for BioC 3.17: simplified long |
|
This page was generated on 2023-10-16 11:36:14 -0400 (Mon, 16 Oct 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.2 LTS) | x86_64 | 4.3.1 (2023-06-16) -- "Beagle Scouts" | 4626 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.3.1 (2023-06-16 ucrt) -- "Beagle Scouts" | 4379 |
| merida1 | macOS 12.6.4 Monterey | x86_64 | 4.3.1 (2023-06-16) -- "Beagle Scouts" | 4395 |
| 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 | ||||
| Package 949/2230 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.6.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 22.04.2 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.6.4 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson2 | macOS 12.6.1 Monterey / arm64 | see weekly results here | ||||||||||||
|
To the developers/maintainers of the HPiP package: - 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 Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.6.0 |
| Command: F:\biocbuild\bbs-3.17-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.17-bioc\R\library --no-vignettes --timings HPiP_1.6.0.tar.gz |
| StartedAt: 2023-10-16 03:05:36 -0400 (Mon, 16 Oct 2023) |
| EndedAt: 2023-10-16 03:09:51 -0400 (Mon, 16 Oct 2023) |
| EllapsedTime: 255.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.17-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.17-bioc\R\library --no-vignettes --timings HPiP_1.6.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck'
* using R version 4.3.1 (2023-06-16 ucrt)
* using platform: x86_64-w64-mingw32 (64-bit)
* R was compiled by
gcc.exe (GCC) 12.2.0
GNU Fortran (GCC) 12.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.6.0'
* 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 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 29.30 0.77 30.08
FSmethod 28.35 1.40 29.78
corr_plot 27.85 0.90 28.77
pred_ensembel 12.34 0.37 9.47
enrichfindP 0.59 0.05 13.42
* 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-3.17-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.17-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.17-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 4.3.1 (2023-06-16 ucrt) -- "Beagle Scouts"
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 97.012204
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 96.341855
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 100.320226
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 103.633682
final value 94.038251
converged
Fitting Repeat 5
# weights: 103
initial value 100.465221
iter 10 value 94.039103
final value 94.038252
converged
Fitting Repeat 1
# weights: 305
initial value 100.160280
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 103.886861
final value 94.038251
converged
Fitting Repeat 3
# weights: 305
initial value 97.459286
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 100.487062
final value 94.038251
converged
Fitting Repeat 5
# weights: 305
initial value 94.269815
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 96.083455
iter 10 value 93.986804
iter 20 value 93.934417
iter 30 value 93.932248
final value 93.932129
converged
Fitting Repeat 2
# weights: 507
initial value 96.217671
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 99.109879
final value 93.164740
converged
Fitting Repeat 4
# weights: 507
initial value 124.876305
final value 94.038251
converged
Fitting Repeat 5
# weights: 507
initial value 98.410552
final value 94.038252
converged
Fitting Repeat 1
# weights: 103
initial value 98.508112
iter 10 value 94.045062
iter 20 value 88.690800
iter 30 value 85.328327
iter 40 value 81.973760
iter 50 value 81.882358
iter 60 value 81.644244
iter 70 value 81.635994
final value 81.635990
converged
Fitting Repeat 2
# weights: 103
initial value 99.555889
iter 10 value 94.056764
iter 20 value 93.346427
iter 30 value 83.002267
iter 40 value 81.946345
iter 50 value 81.901615
iter 60 value 81.871332
final value 81.871260
converged
Fitting Repeat 3
# weights: 103
initial value 100.704617
iter 10 value 93.979504
iter 20 value 90.506563
iter 30 value 89.530961
iter 40 value 89.437137
iter 50 value 84.026664
iter 60 value 81.310546
iter 70 value 80.390312
iter 80 value 80.190975
iter 90 value 80.098186
iter 100 value 79.719461
final value 79.719461
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.201433
iter 10 value 94.063827
iter 20 value 94.054962
iter 30 value 94.054904
iter 40 value 91.235012
iter 50 value 86.639406
iter 60 value 84.375628
iter 70 value 83.214549
iter 80 value 81.823215
iter 90 value 81.656393
iter 100 value 81.644863
final value 81.644863
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 114.745443
iter 10 value 94.021475
iter 20 value 88.854950
iter 30 value 86.865015
iter 40 value 85.015671
iter 50 value 84.881468
iter 60 value 83.359140
iter 70 value 82.534524
iter 80 value 81.619181
iter 90 value 81.609495
final value 81.608562
converged
Fitting Repeat 1
# weights: 305
initial value 101.095828
iter 10 value 93.033005
iter 20 value 83.231372
iter 30 value 82.427429
iter 40 value 81.911515
iter 50 value 81.599147
iter 60 value 81.203991
iter 70 value 81.173387
iter 80 value 81.170928
iter 90 value 81.145456
iter 100 value 80.873061
final value 80.873061
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.099748
iter 10 value 93.241505
iter 20 value 82.607930
iter 30 value 81.885800
iter 40 value 81.392866
iter 50 value 81.210514
iter 60 value 80.850012
iter 70 value 79.490142
iter 80 value 78.988045
iter 90 value 78.518119
iter 100 value 78.246763
final value 78.246763
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.453347
iter 10 value 93.813210
iter 20 value 93.646338
iter 30 value 84.437157
iter 40 value 81.796606
iter 50 value 80.555529
iter 60 value 79.191812
iter 70 value 78.741660
iter 80 value 78.447707
iter 90 value 78.423374
iter 100 value 78.399916
final value 78.399916
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 98.072758
iter 10 value 84.007711
iter 20 value 81.853756
iter 30 value 80.775114
iter 40 value 80.390076
iter 50 value 79.369609
iter 60 value 78.560824
iter 70 value 78.374092
iter 80 value 78.331808
iter 90 value 78.263531
iter 100 value 78.143647
final value 78.143647
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.445175
iter 10 value 94.841763
iter 20 value 88.595826
iter 30 value 82.312576
iter 40 value 81.343017
iter 50 value 81.090071
iter 60 value 80.468052
iter 70 value 80.133214
iter 80 value 80.031708
iter 90 value 79.847356
iter 100 value 79.806660
final value 79.806660
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 117.036996
iter 10 value 94.463849
iter 20 value 93.882477
iter 30 value 87.017386
iter 40 value 82.214556
iter 50 value 81.578675
iter 60 value 80.599807
iter 70 value 78.332519
iter 80 value 77.723320
iter 90 value 77.677583
iter 100 value 77.622521
final value 77.622521
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.459735
iter 10 value 94.037765
iter 20 value 91.618213
iter 30 value 86.360155
iter 40 value 84.741129
iter 50 value 83.522998
iter 60 value 81.909554
iter 70 value 79.897670
iter 80 value 79.010352
iter 90 value 78.923167
iter 100 value 78.643734
final value 78.643734
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.546123
iter 10 value 94.361134
iter 20 value 89.340079
iter 30 value 84.422978
iter 40 value 82.051228
iter 50 value 81.402644
iter 60 value 80.136164
iter 70 value 79.051991
iter 80 value 78.515839
iter 90 value 78.152663
iter 100 value 77.891844
final value 77.891844
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.626373
iter 10 value 94.232724
iter 20 value 85.036394
iter 30 value 84.023016
iter 40 value 83.326189
iter 50 value 80.230646
iter 60 value 79.462153
iter 70 value 78.827859
iter 80 value 78.564170
iter 90 value 78.188529
iter 100 value 78.027845
final value 78.027845
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.736860
iter 10 value 94.256162
iter 20 value 85.149335
iter 30 value 82.672678
iter 40 value 81.413155
iter 50 value 81.121503
iter 60 value 80.962971
iter 70 value 80.152874
iter 80 value 78.927948
iter 90 value 78.351706
iter 100 value 78.016594
final value 78.016594
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.366358
final value 94.054473
converged
Fitting Repeat 2
# weights: 103
initial value 94.563093
final value 94.054539
converged
Fitting Repeat 3
# weights: 103
initial value 94.553827
final value 94.054435
converged
Fitting Repeat 4
# weights: 103
initial value 94.955483
iter 10 value 94.054705
iter 20 value 94.052907
iter 30 value 91.656556
iter 40 value 86.584148
iter 50 value 86.503495
iter 60 value 86.380597
iter 70 value 86.281684
iter 80 value 86.280881
final value 86.280746
converged
Fitting Repeat 5
# weights: 103
initial value 95.430194
final value 94.054565
converged
Fitting Repeat 1
# weights: 305
initial value 107.896839
iter 10 value 94.043110
iter 20 value 94.038598
iter 30 value 94.021774
iter 40 value 84.622586
iter 50 value 81.581932
iter 60 value 80.635842
iter 70 value 80.586523
iter 80 value 80.586298
iter 80 value 80.586297
iter 80 value 80.586297
final value 80.586297
converged
Fitting Repeat 2
# weights: 305
initial value 118.737411
iter 10 value 94.058200
iter 20 value 93.789160
iter 30 value 90.966348
iter 40 value 86.215212
iter 50 value 86.207409
iter 60 value 84.361950
iter 70 value 83.291365
iter 80 value 82.712945
iter 90 value 82.487960
iter 100 value 82.485425
final value 82.485425
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.310676
iter 10 value 92.198436
iter 20 value 92.052343
iter 30 value 91.506078
iter 40 value 91.408322
iter 50 value 82.572153
iter 60 value 81.590586
iter 70 value 81.577844
iter 80 value 80.613822
iter 90 value 80.588538
iter 100 value 80.588254
final value 80.588254
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.802903
iter 10 value 94.057883
iter 20 value 90.478693
iter 30 value 82.378598
final value 82.378560
converged
Fitting Repeat 5
# weights: 305
initial value 95.071855
iter 10 value 93.675372
iter 20 value 84.686593
iter 30 value 84.577052
iter 40 value 84.402595
iter 50 value 84.385454
iter 60 value 84.255929
iter 70 value 82.016364
iter 80 value 78.775041
iter 90 value 78.527705
iter 100 value 78.522771
final value 78.522771
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 98.602789
iter 10 value 94.061475
iter 20 value 94.025942
iter 30 value 84.218952
iter 40 value 84.212564
final value 84.212543
converged
Fitting Repeat 2
# weights: 507
initial value 119.518686
iter 10 value 94.061599
iter 20 value 94.053921
iter 30 value 94.044119
iter 40 value 94.018686
iter 50 value 93.980268
final value 93.980265
converged
Fitting Repeat 3
# weights: 507
initial value 95.851098
iter 10 value 94.046456
iter 20 value 94.037679
iter 30 value 84.831767
iter 40 value 82.278528
iter 50 value 82.271556
iter 60 value 81.633463
iter 70 value 81.606524
iter 80 value 80.778662
iter 90 value 80.075310
iter 100 value 78.850646
final value 78.850646
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 101.332669
iter 10 value 94.058609
iter 20 value 93.680752
iter 30 value 86.909452
iter 40 value 79.895753
iter 50 value 78.925189
iter 60 value 78.469393
iter 70 value 78.027764
iter 80 value 77.980093
iter 90 value 77.906893
iter 100 value 77.628194
final value 77.628194
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.171248
iter 10 value 94.046227
iter 20 value 94.039428
iter 30 value 91.657504
iter 40 value 82.268041
iter 50 value 80.287226
iter 60 value 79.517260
iter 70 value 79.516046
iter 80 value 79.448754
iter 90 value 79.095902
iter 100 value 79.086193
final value 79.086193
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 112.539397
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 113.617999
final value 94.477594
converged
Fitting Repeat 3
# weights: 103
initial value 100.588380
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.510988
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 99.251853
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 99.089981
final value 94.275362
converged
Fitting Repeat 2
# weights: 305
initial value 99.495213
iter 10 value 94.275363
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 3
# weights: 305
initial value 101.227281
final value 94.484210
converged
Fitting Repeat 4
# weights: 305
initial value 110.890830
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 96.487155
final value 94.448052
converged
Fitting Repeat 1
# weights: 507
initial value 94.574917
iter 10 value 88.750729
iter 20 value 86.515857
iter 30 value 86.495713
final value 86.495642
converged
Fitting Repeat 2
# weights: 507
initial value 120.980773
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 96.622461
iter 10 value 93.492775
iter 20 value 91.315701
iter 30 value 89.304840
final value 89.304766
converged
Fitting Repeat 4
# weights: 507
initial value 125.793852
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 104.714561
iter 10 value 93.607287
iter 10 value 93.607287
iter 10 value 93.607287
final value 93.607287
converged
Fitting Repeat 1
# weights: 103
initial value 107.083977
iter 10 value 94.568705
iter 20 value 89.842504
iter 30 value 85.732355
iter 40 value 84.952115
iter 50 value 84.749472
iter 60 value 84.689906
iter 70 value 84.650863
final value 84.644077
converged
Fitting Repeat 2
# weights: 103
initial value 97.681589
iter 10 value 94.493969
iter 20 value 93.977385
iter 30 value 93.725822
iter 40 value 93.640683
iter 50 value 90.933744
iter 60 value 88.217184
iter 70 value 87.196882
iter 80 value 87.121454
iter 90 value 85.231349
iter 100 value 85.124465
final value 85.124465
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 104.493297
iter 10 value 94.487605
iter 20 value 92.625575
iter 30 value 87.279887
iter 40 value 87.180983
iter 50 value 87.119348
iter 60 value 85.810624
iter 70 value 84.066838
iter 80 value 83.127724
iter 90 value 82.892912
iter 100 value 82.815830
final value 82.815830
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.939696
iter 10 value 93.651858
iter 20 value 87.129015
iter 30 value 86.191881
iter 40 value 85.087346
iter 50 value 85.064442
iter 60 value 85.064350
final value 85.064349
converged
Fitting Repeat 5
# weights: 103
initial value 99.918513
iter 10 value 94.500949
iter 20 value 87.483873
iter 30 value 86.899183
iter 40 value 85.211732
iter 50 value 83.539052
iter 60 value 82.856381
iter 70 value 82.806686
iter 80 value 82.732562
iter 90 value 82.661274
final value 82.661110
converged
Fitting Repeat 1
# weights: 305
initial value 101.665725
iter 10 value 94.133372
iter 20 value 88.684825
iter 30 value 85.743640
iter 40 value 82.698457
iter 50 value 82.241819
iter 60 value 81.991533
iter 70 value 81.948615
iter 80 value 81.920896
iter 90 value 81.917576
iter 100 value 81.904250
final value 81.904250
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 145.180576
iter 10 value 94.369469
iter 20 value 93.804748
iter 30 value 93.530486
iter 40 value 92.644304
iter 50 value 85.361604
iter 60 value 83.831695
iter 70 value 83.177448
iter 80 value 82.463864
iter 90 value 82.162907
iter 100 value 82.000879
final value 82.000879
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.487029
iter 10 value 94.508207
iter 20 value 90.074750
iter 30 value 87.070197
iter 40 value 85.908209
iter 50 value 83.995718
iter 60 value 83.268485
iter 70 value 82.676055
iter 80 value 81.987288
iter 90 value 81.877607
iter 100 value 81.817376
final value 81.817376
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.726226
iter 10 value 94.632249
iter 20 value 88.814542
iter 30 value 86.286885
iter 40 value 84.535844
iter 50 value 84.234833
iter 60 value 84.002647
iter 70 value 83.940774
iter 80 value 83.845523
iter 90 value 83.621392
iter 100 value 83.394492
final value 83.394492
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.385739
iter 10 value 94.488577
iter 20 value 87.949190
iter 30 value 87.388456
iter 40 value 86.751506
iter 50 value 85.199899
iter 60 value 84.748659
iter 70 value 84.655200
iter 80 value 84.186022
iter 90 value 83.553419
iter 100 value 83.362846
final value 83.362846
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 127.309858
iter 10 value 94.461576
iter 20 value 87.312679
iter 30 value 85.288184
iter 40 value 85.101194
iter 50 value 85.006149
iter 60 value 84.790841
iter 70 value 83.553735
iter 80 value 82.871628
iter 90 value 82.601203
iter 100 value 82.083545
final value 82.083545
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.885735
iter 10 value 94.812630
iter 20 value 91.947606
iter 30 value 85.920171
iter 40 value 85.423813
iter 50 value 84.697008
iter 60 value 84.124162
iter 70 value 82.189813
iter 80 value 81.914013
iter 90 value 81.861575
iter 100 value 81.783743
final value 81.783743
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.721577
iter 10 value 94.503831
iter 20 value 93.965861
iter 30 value 85.850664
iter 40 value 85.208545
iter 50 value 84.959419
iter 60 value 84.616552
iter 70 value 83.833688
iter 80 value 83.090491
iter 90 value 83.030615
iter 100 value 82.278149
final value 82.278149
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.104906
iter 10 value 94.417202
iter 20 value 92.730148
iter 30 value 91.912455
iter 40 value 85.495747
iter 50 value 83.473433
iter 60 value 82.860052
iter 70 value 82.588512
iter 80 value 82.021739
iter 90 value 81.795293
iter 100 value 81.681889
final value 81.681889
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 119.429154
iter 10 value 95.186119
iter 20 value 91.006639
iter 30 value 88.580135
iter 40 value 87.147129
iter 50 value 86.429359
iter 60 value 85.027167
iter 70 value 83.553286
iter 80 value 82.229006
iter 90 value 81.899581
iter 100 value 81.756172
final value 81.756172
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.565841
final value 94.485632
converged
Fitting Repeat 2
# weights: 103
initial value 107.107483
final value 94.485800
converged
Fitting Repeat 3
# weights: 103
initial value 94.799998
final value 94.485892
converged
Fitting Repeat 4
# weights: 103
initial value 101.587961
final value 94.485961
converged
Fitting Repeat 5
# weights: 103
initial value 109.099135
final value 94.485838
converged
Fitting Repeat 1
# weights: 305
initial value 104.136314
iter 10 value 94.489086
iter 20 value 94.439102
iter 30 value 85.078311
iter 40 value 84.689420
final value 84.687237
converged
Fitting Repeat 2
# weights: 305
initial value 102.950293
iter 10 value 94.488550
iter 20 value 93.127066
iter 30 value 87.876091
iter 40 value 87.862391
iter 50 value 87.860677
iter 60 value 83.745212
iter 70 value 83.729341
iter 80 value 83.620068
iter 90 value 82.380315
iter 100 value 82.027773
final value 82.027773
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.676789
iter 10 value 94.310849
iter 20 value 94.042127
iter 30 value 93.583835
iter 40 value 93.575182
iter 50 value 91.215372
iter 60 value 82.650890
iter 70 value 82.427591
iter 80 value 82.061963
iter 90 value 82.049735
iter 100 value 82.020674
final value 82.020674
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.377511
iter 10 value 94.489156
iter 20 value 94.472249
final value 94.275502
converged
Fitting Repeat 5
# weights: 305
initial value 108.001324
iter 10 value 94.489150
iter 20 value 94.414616
iter 30 value 93.850335
iter 40 value 93.552122
iter 50 value 91.819815
iter 60 value 91.739077
iter 70 value 91.669147
iter 80 value 91.667880
iter 90 value 91.058850
iter 100 value 88.458521
final value 88.458521
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 101.180368
iter 10 value 94.492190
iter 20 value 94.408020
iter 30 value 92.455560
iter 40 value 86.787671
iter 50 value 86.754262
iter 60 value 86.668459
final value 86.668310
converged
Fitting Repeat 2
# weights: 507
initial value 95.200629
iter 10 value 94.283785
iter 20 value 94.240841
iter 30 value 86.682400
iter 40 value 86.643248
iter 50 value 86.642177
iter 60 value 86.639221
iter 70 value 86.633334
iter 80 value 86.632136
iter 90 value 86.628786
iter 100 value 86.626678
final value 86.626678
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.857759
iter 10 value 92.348981
iter 20 value 83.985169
iter 30 value 83.900980
iter 40 value 83.897770
iter 50 value 83.847707
iter 60 value 83.846681
iter 70 value 83.839413
iter 80 value 83.813273
iter 90 value 83.735227
iter 100 value 83.727702
final value 83.727702
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 96.978663
iter 10 value 89.674176
iter 20 value 86.709986
iter 30 value 86.694413
iter 40 value 86.662352
iter 50 value 84.606423
iter 60 value 84.500189
iter 70 value 84.495560
final value 84.495556
converged
Fitting Repeat 5
# weights: 507
initial value 97.085149
iter 10 value 91.487471
iter 20 value 87.478955
iter 30 value 87.391873
iter 40 value 87.390405
iter 50 value 87.387442
iter 50 value 87.387442
final value 87.387442
converged
Fitting Repeat 1
# weights: 103
initial value 96.618933
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.834480
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.812550
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.713423
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 103.195125
iter 10 value 94.060582
iter 20 value 94.058489
final value 94.058479
converged
Fitting Repeat 1
# weights: 305
initial value 95.181576
iter 10 value 94.354418
final value 94.354396
converged
Fitting Repeat 2
# weights: 305
initial value 94.823531
final value 94.484137
converged
Fitting Repeat 3
# weights: 305
initial value 101.321634
final value 94.354396
converged
Fitting Repeat 4
# weights: 305
initial value 99.261816
final value 94.354396
converged
Fitting Repeat 5
# weights: 305
initial value 103.679722
final value 94.052434
converged
Fitting Repeat 1
# weights: 507
initial value 98.176602
final value 94.484137
converged
Fitting Repeat 2
# weights: 507
initial value 114.331812
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 103.555586
final value 94.484210
converged
Fitting Repeat 4
# weights: 507
initial value 112.807408
iter 10 value 93.618839
iter 20 value 91.829864
iter 30 value 90.691342
iter 40 value 90.328621
final value 90.324940
converged
Fitting Repeat 5
# weights: 507
initial value 114.801463
iter 10 value 89.061925
iter 20 value 85.840146
iter 20 value 85.840146
iter 20 value 85.840146
final value 85.840146
converged
Fitting Repeat 1
# weights: 103
initial value 103.710262
iter 10 value 94.488513
iter 20 value 92.378388
iter 30 value 84.502977
iter 40 value 84.017713
iter 50 value 81.858684
iter 60 value 80.399705
iter 70 value 80.369136
final value 80.368862
converged
Fitting Repeat 2
# weights: 103
initial value 97.473704
iter 10 value 93.195633
iter 20 value 87.299019
iter 30 value 84.499459
iter 40 value 84.221116
iter 50 value 83.981184
iter 60 value 83.971505
iter 60 value 83.971504
iter 60 value 83.971504
final value 83.971504
converged
Fitting Repeat 3
# weights: 103
initial value 102.849959
iter 10 value 94.263268
iter 20 value 85.680986
iter 30 value 84.368364
iter 40 value 84.333697
final value 84.333694
converged
Fitting Repeat 4
# weights: 103
initial value 97.181219
iter 10 value 94.484472
iter 20 value 91.781345
iter 30 value 91.412119
iter 40 value 89.087748
iter 50 value 88.940185
iter 60 value 88.895249
iter 70 value 88.894593
final value 88.894589
converged
Fitting Repeat 5
# weights: 103
initial value 97.619888
iter 10 value 94.520123
iter 20 value 94.488451
iter 30 value 85.216064
iter 40 value 84.422081
iter 50 value 84.025205
iter 60 value 82.874644
iter 70 value 82.435324
iter 80 value 82.399839
final value 82.399815
converged
Fitting Repeat 1
# weights: 305
initial value 102.303646
iter 10 value 94.466986
iter 20 value 93.729849
iter 30 value 86.081128
iter 40 value 83.130124
iter 50 value 81.285316
iter 60 value 80.763698
iter 70 value 80.331881
iter 80 value 79.815509
iter 90 value 79.128863
iter 100 value 79.033028
final value 79.033028
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.804474
iter 10 value 94.254532
iter 20 value 87.491927
iter 30 value 83.982787
iter 40 value 82.419890
iter 50 value 82.022292
iter 60 value 79.839403
iter 70 value 79.453150
iter 80 value 79.373173
iter 90 value 79.145885
iter 100 value 78.926583
final value 78.926583
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.657962
iter 10 value 94.448185
iter 20 value 91.021756
iter 30 value 88.141586
iter 40 value 84.843296
iter 50 value 84.491745
iter 60 value 84.345478
iter 70 value 84.313711
iter 80 value 83.739810
iter 90 value 81.632652
iter 100 value 80.429435
final value 80.429435
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.443884
iter 10 value 94.610444
iter 20 value 94.211663
iter 30 value 94.141574
iter 40 value 92.922951
iter 50 value 88.215869
iter 60 value 83.143617
iter 70 value 81.951352
iter 80 value 81.560765
iter 90 value 81.074631
iter 100 value 80.419359
final value 80.419359
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 114.327949
iter 10 value 94.401240
iter 20 value 92.722808
iter 30 value 90.861662
iter 40 value 87.941876
iter 50 value 86.026040
iter 60 value 85.616175
iter 70 value 83.837095
iter 80 value 82.970390
iter 90 value 82.518722
iter 100 value 82.273619
final value 82.273619
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.887972
iter 10 value 94.507310
iter 20 value 94.220947
iter 30 value 92.758245
iter 40 value 84.875756
iter 50 value 84.159463
iter 60 value 83.862999
iter 70 value 81.636246
iter 80 value 79.681258
iter 90 value 79.422720
iter 100 value 79.233066
final value 79.233066
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.422231
iter 10 value 94.512673
iter 20 value 85.535190
iter 30 value 83.975174
iter 40 value 82.563209
iter 50 value 81.150999
iter 60 value 80.876315
iter 70 value 80.177273
iter 80 value 79.861517
iter 90 value 79.781277
iter 100 value 79.759679
final value 79.759679
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.186987
iter 10 value 93.916235
iter 20 value 85.627785
iter 30 value 84.059321
iter 40 value 81.580747
iter 50 value 80.523860
iter 60 value 80.328270
iter 70 value 79.463723
iter 80 value 79.036668
iter 90 value 78.651576
iter 100 value 78.596260
final value 78.596260
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 120.015712
iter 10 value 92.953481
iter 20 value 91.686347
iter 30 value 90.946056
iter 40 value 90.786335
iter 50 value 84.119689
iter 60 value 82.074475
iter 70 value 80.685214
iter 80 value 79.730893
iter 90 value 79.462314
iter 100 value 79.367654
final value 79.367654
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 114.287409
iter 10 value 95.130416
iter 20 value 92.257676
iter 30 value 90.832020
iter 40 value 88.816393
iter 50 value 87.987158
iter 60 value 85.173733
iter 70 value 82.669103
iter 80 value 80.850249
iter 90 value 80.474027
iter 100 value 79.457152
final value 79.457152
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.019419
final value 94.485862
converged
Fitting Repeat 2
# weights: 103
initial value 98.639142
final value 94.485927
converged
Fitting Repeat 3
# weights: 103
initial value 95.072990
final value 94.256237
converged
Fitting Repeat 4
# weights: 103
initial value 108.311162
iter 10 value 94.485797
iter 20 value 94.484117
iter 30 value 91.363953
iter 40 value 87.703661
iter 50 value 87.671180
iter 60 value 86.669050
iter 70 value 86.640441
iter 80 value 85.555635
iter 90 value 85.527818
iter 100 value 85.527380
final value 85.527380
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.324107
final value 94.485700
converged
Fitting Repeat 1
# weights: 305
initial value 128.573308
iter 10 value 94.488977
iter 20 value 94.475510
iter 30 value 84.208876
iter 40 value 83.626005
iter 50 value 83.607637
iter 60 value 83.485513
iter 70 value 83.480016
iter 80 value 83.478752
iter 90 value 83.211048
iter 100 value 83.059446
final value 83.059446
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.611921
iter 10 value 94.488842
iter 20 value 94.361206
final value 94.354590
converged
Fitting Repeat 3
# weights: 305
initial value 112.494118
iter 10 value 94.488084
final value 94.484597
converged
Fitting Repeat 4
# weights: 305
initial value 99.248704
iter 10 value 94.497769
iter 20 value 94.430057
iter 30 value 93.705883
iter 40 value 91.903640
iter 50 value 91.066344
iter 60 value 90.359762
iter 70 value 88.100605
iter 80 value 88.077186
iter 90 value 88.076423
iter 90 value 88.076423
iter 90 value 88.076423
final value 88.076423
converged
Fitting Repeat 5
# weights: 305
initial value 97.150418
iter 10 value 94.358843
iter 20 value 94.070019
iter 30 value 94.058083
iter 40 value 93.988698
iter 50 value 86.970439
iter 60 value 86.873966
iter 70 value 86.873746
final value 86.872674
converged
Fitting Repeat 1
# weights: 507
initial value 112.339392
iter 10 value 94.362575
iter 20 value 94.351103
iter 30 value 92.878679
final value 92.787063
converged
Fitting Repeat 2
# weights: 507
initial value 112.582090
iter 10 value 94.492650
iter 20 value 94.303606
iter 30 value 88.880490
iter 40 value 86.809520
iter 50 value 85.589917
iter 60 value 85.579101
iter 70 value 85.243959
iter 80 value 82.405448
iter 90 value 79.654085
iter 100 value 79.339475
final value 79.339475
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 98.551650
iter 10 value 94.363147
iter 20 value 94.354791
iter 30 value 90.749696
iter 40 value 83.792338
iter 50 value 83.657727
iter 60 value 83.656647
iter 70 value 83.651934
final value 83.651813
converged
Fitting Repeat 4
# weights: 507
initial value 98.461416
iter 10 value 93.977749
iter 20 value 93.973863
iter 30 value 93.418833
iter 40 value 90.322994
iter 50 value 83.708248
iter 60 value 81.207080
iter 70 value 80.993533
iter 80 value 80.964330
iter 90 value 80.962474
iter 100 value 80.961339
final value 80.961339
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.442423
iter 10 value 94.491488
iter 20 value 94.469656
iter 30 value 94.354617
iter 40 value 94.353833
iter 50 value 94.353787
final value 94.353782
converged
Fitting Repeat 1
# weights: 103
initial value 109.464648
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 109.953178
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 102.575872
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 100.249436
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 99.095184
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 102.576767
final value 94.050155
converged
Fitting Repeat 2
# weights: 305
initial value 95.041795
iter 10 value 88.266941
final value 86.376995
converged
Fitting Repeat 3
# weights: 305
initial value 97.250229
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 105.730594
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 127.591263
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 120.620610
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 112.407692
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 108.619609
iter 10 value 93.582487
final value 93.582418
converged
Fitting Repeat 4
# weights: 507
initial value 95.305548
iter 10 value 87.327223
iter 20 value 86.706905
iter 30 value 86.703327
final value 86.703310
converged
Fitting Repeat 5
# weights: 507
initial value 118.787573
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 100.501623
iter 10 value 94.056679
iter 20 value 88.987358
iter 30 value 88.131517
iter 40 value 87.762750
iter 50 value 87.312684
iter 60 value 86.097339
iter 70 value 85.545520
iter 80 value 84.941156
iter 90 value 84.756883
final value 84.698294
converged
Fitting Repeat 2
# weights: 103
initial value 104.267752
iter 10 value 93.972504
iter 20 value 93.686983
iter 30 value 93.683707
iter 40 value 88.599826
iter 50 value 86.478004
iter 60 value 86.233200
iter 70 value 86.080479
iter 80 value 85.587632
iter 90 value 85.523214
final value 85.523048
converged
Fitting Repeat 3
# weights: 103
initial value 104.195213
iter 10 value 93.605598
iter 20 value 89.036921
iter 30 value 86.585275
iter 40 value 86.232562
iter 50 value 85.976828
iter 60 value 85.483443
iter 70 value 85.377993
iter 80 value 85.371959
final value 85.371958
converged
Fitting Repeat 4
# weights: 103
initial value 103.313771
iter 10 value 94.031937
iter 20 value 89.548190
iter 30 value 86.768835
iter 40 value 86.306186
iter 50 value 85.930754
iter 60 value 85.736436
iter 70 value 85.684644
iter 80 value 85.348577
iter 90 value 85.216653
iter 100 value 85.070237
final value 85.070237
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 107.966055
iter 10 value 94.020695
iter 20 value 93.779174
iter 30 value 91.125519
iter 40 value 89.124629
iter 50 value 88.160664
iter 60 value 85.596084
iter 70 value 85.382812
iter 80 value 83.953284
iter 90 value 83.862734
iter 100 value 83.855103
final value 83.855103
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 102.872374
iter 10 value 94.309177
iter 20 value 92.986438
iter 30 value 88.373273
iter 40 value 86.872421
iter 50 value 84.313334
iter 60 value 82.913692
iter 70 value 82.231151
iter 80 value 82.057904
iter 90 value 81.983896
iter 100 value 81.955414
final value 81.955414
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.659213
iter 10 value 94.099332
iter 20 value 93.920180
iter 30 value 93.382859
iter 40 value 89.438581
iter 50 value 88.586173
iter 60 value 87.412901
iter 70 value 86.979190
iter 80 value 86.847445
iter 90 value 86.053826
iter 100 value 85.437831
final value 85.437831
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.885478
iter 10 value 94.054857
iter 20 value 93.707822
iter 30 value 93.254067
iter 40 value 91.950347
iter 50 value 89.344997
iter 60 value 88.329886
iter 70 value 87.799362
iter 80 value 86.261575
iter 90 value 85.136807
iter 100 value 84.271972
final value 84.271972
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.546885
iter 10 value 94.227448
iter 20 value 93.802054
iter 30 value 93.076005
iter 40 value 88.280070
iter 50 value 86.373394
iter 60 value 85.680237
iter 70 value 84.670051
iter 80 value 84.124081
iter 90 value 83.692357
iter 100 value 82.903395
final value 82.903395
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 111.567010
iter 10 value 93.863518
iter 20 value 88.165507
iter 30 value 87.377639
iter 40 value 85.147787
iter 50 value 83.157286
iter 60 value 82.919611
iter 70 value 82.881757
iter 80 value 82.759816
iter 90 value 82.158788
iter 100 value 82.027538
final value 82.027538
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.445917
iter 10 value 94.078783
iter 20 value 92.966595
iter 30 value 87.515919
iter 40 value 87.036176
iter 50 value 86.717247
iter 60 value 86.476124
iter 70 value 83.531462
iter 80 value 82.568409
iter 90 value 82.295641
iter 100 value 82.248939
final value 82.248939
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.045478
iter 10 value 94.306190
iter 20 value 90.881652
iter 30 value 87.766474
iter 40 value 86.234008
iter 50 value 84.470580
iter 60 value 83.877167
iter 70 value 83.283299
iter 80 value 83.199077
iter 90 value 83.174025
iter 100 value 82.841765
final value 82.841765
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.619823
iter 10 value 93.452303
iter 20 value 92.062066
iter 30 value 87.606778
iter 40 value 86.183481
iter 50 value 85.016578
iter 60 value 82.749664
iter 70 value 82.376893
iter 80 value 82.344848
iter 90 value 82.162212
iter 100 value 81.858132
final value 81.858132
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.000621
iter 10 value 94.563097
iter 20 value 94.371284
iter 30 value 93.251354
iter 40 value 88.506129
iter 50 value 87.987281
iter 60 value 86.298488
iter 70 value 85.162693
iter 80 value 84.048330
iter 90 value 83.748541
iter 100 value 83.042907
final value 83.042907
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.944987
iter 10 value 94.102085
iter 20 value 93.105792
iter 30 value 88.048214
iter 40 value 84.312154
iter 50 value 82.974967
iter 60 value 82.842609
iter 70 value 82.401451
iter 80 value 82.189286
iter 90 value 82.145310
iter 100 value 82.121041
final value 82.121041
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 104.652985
final value 94.054372
converged
Fitting Repeat 2
# weights: 103
initial value 97.101922
iter 10 value 93.584539
iter 20 value 93.582739
final value 93.582592
converged
Fitting Repeat 3
# weights: 103
initial value 97.712237
final value 94.054611
converged
Fitting Repeat 4
# weights: 103
initial value 100.780701
final value 94.054525
converged
Fitting Repeat 5
# weights: 103
initial value 100.652286
final value 94.054527
converged
Fitting Repeat 1
# weights: 305
initial value 96.928280
iter 10 value 94.057721
iter 20 value 94.045121
iter 30 value 93.779665
iter 40 value 92.737889
iter 50 value 92.734780
iter 60 value 92.733615
iter 70 value 89.203980
iter 80 value 89.003553
iter 90 value 88.001011
iter 100 value 87.976354
final value 87.976354
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 94.846511
iter 10 value 94.057755
iter 20 value 94.046830
final value 93.582695
converged
Fitting Repeat 3
# weights: 305
initial value 102.430028
iter 10 value 93.947991
iter 20 value 93.942224
iter 30 value 93.806152
iter 40 value 93.805742
iter 50 value 93.803334
iter 60 value 91.149515
iter 70 value 90.659655
iter 80 value 90.657471
iter 90 value 90.657238
iter 100 value 90.657030
final value 90.657030
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.560765
iter 10 value 92.749943
iter 20 value 92.432060
iter 30 value 92.280476
iter 40 value 92.276592
final value 92.275893
converged
Fitting Repeat 5
# weights: 305
initial value 117.179633
iter 10 value 90.070303
iter 20 value 88.968199
iter 30 value 88.950007
iter 40 value 88.744211
iter 50 value 88.728096
iter 60 value 88.565933
iter 70 value 87.691895
iter 80 value 87.001835
iter 90 value 86.994244
iter 100 value 86.993870
final value 86.993870
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 95.102533
iter 10 value 93.605512
iter 20 value 93.589514
iter 30 value 93.583932
iter 40 value 93.582698
iter 50 value 93.564563
iter 60 value 90.967193
iter 70 value 90.706484
iter 80 value 90.703030
iter 90 value 90.702486
iter 100 value 90.702336
final value 90.702336
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.485042
iter 10 value 93.591260
iter 20 value 93.583004
final value 93.582856
converged
Fitting Repeat 3
# weights: 507
initial value 101.157201
iter 10 value 94.061194
iter 20 value 93.980085
iter 30 value 93.603525
final value 93.583031
converged
Fitting Repeat 4
# weights: 507
initial value 103.052216
iter 10 value 94.060356
iter 20 value 93.908518
iter 30 value 91.563818
iter 40 value 87.205986
iter 50 value 87.202607
final value 87.202595
converged
Fitting Repeat 5
# weights: 507
initial value 98.496042
iter 10 value 94.003522
iter 20 value 92.004730
iter 30 value 91.982724
iter 40 value 91.973978
iter 50 value 91.933480
iter 60 value 91.911821
iter 70 value 91.907147
iter 80 value 91.410053
iter 90 value 91.206753
final value 91.206458
converged
Fitting Repeat 1
# weights: 103
initial value 103.033259
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 101.506993
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.923475
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.556919
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.725149
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 102.473567
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 99.785831
iter 10 value 94.422598
final value 94.422596
converged
Fitting Repeat 3
# weights: 305
initial value 109.791911
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 94.344044
iter 10 value 84.908606
iter 20 value 84.628527
iter 30 value 82.556321
iter 40 value 81.788076
iter 50 value 81.763325
final value 81.763268
converged
Fitting Repeat 5
# weights: 305
initial value 97.523660
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 99.806057
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 130.242146
iter 10 value 93.991342
iter 10 value 93.991342
iter 10 value 93.991342
final value 93.991342
converged
Fitting Repeat 3
# weights: 507
initial value 98.994940
iter 10 value 93.957832
final value 93.957576
converged
Fitting Repeat 4
# weights: 507
initial value 96.648819
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 108.783725
iter 10 value 94.371628
iter 20 value 93.998066
final value 93.991348
converged
Fitting Repeat 1
# weights: 103
initial value 100.373334
iter 10 value 94.209891
iter 20 value 90.097587
iter 30 value 85.881298
iter 40 value 82.738941
iter 50 value 81.707012
iter 60 value 79.886778
iter 70 value 79.480532
iter 80 value 79.032823
iter 90 value 78.747969
iter 100 value 78.687630
final value 78.687630
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.038791
iter 10 value 94.505124
iter 20 value 94.382394
iter 30 value 93.797613
iter 40 value 92.436815
iter 50 value 92.181376
iter 60 value 92.146899
iter 70 value 89.828265
iter 80 value 85.642440
iter 90 value 83.684054
iter 100 value 80.879000
final value 80.879000
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.542741
iter 10 value 94.447521
iter 20 value 92.642335
iter 30 value 84.416530
iter 40 value 83.603752
iter 50 value 80.227360
iter 60 value 79.194118
iter 70 value 78.964596
iter 80 value 78.893321
iter 90 value 78.833635
iter 100 value 78.717077
final value 78.717077
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 103.918837
iter 10 value 94.487251
iter 20 value 94.141829
iter 30 value 88.596327
iter 40 value 87.031938
iter 50 value 80.180063
iter 60 value 79.629248
iter 70 value 79.428262
iter 80 value 79.185202
iter 90 value 78.956060
iter 100 value 78.805639
final value 78.805639
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.216715
iter 10 value 94.488787
iter 20 value 94.370671
iter 30 value 94.037351
iter 40 value 93.927280
iter 50 value 90.659293
iter 60 value 87.413120
iter 70 value 85.670675
iter 80 value 79.721865
iter 90 value 79.182210
iter 100 value 78.926318
final value 78.926318
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.552736
iter 10 value 94.550060
iter 20 value 93.611348
iter 30 value 90.583916
iter 40 value 90.462273
iter 50 value 86.489073
iter 60 value 81.171459
iter 70 value 78.220285
iter 80 value 76.957609
iter 90 value 76.659931
iter 100 value 76.611526
final value 76.611526
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.354189
iter 10 value 94.473959
iter 20 value 92.985307
iter 30 value 84.759655
iter 40 value 80.891681
iter 50 value 79.890298
iter 60 value 79.392183
iter 70 value 79.144361
iter 80 value 78.947710
iter 90 value 78.182988
iter 100 value 77.890272
final value 77.890272
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 110.048047
iter 10 value 94.450383
iter 20 value 86.101465
iter 30 value 82.257341
iter 40 value 81.822854
iter 50 value 81.719565
iter 60 value 80.159634
iter 70 value 79.365723
iter 80 value 79.092379
iter 90 value 79.035742
iter 100 value 78.976165
final value 78.976165
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.469423
iter 10 value 94.168258
iter 20 value 94.043485
iter 30 value 94.015538
iter 40 value 87.129919
iter 50 value 81.469594
iter 60 value 79.615900
iter 70 value 77.485656
iter 80 value 77.118690
iter 90 value 77.054746
iter 100 value 77.038111
final value 77.038111
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 134.594522
iter 10 value 94.090859
iter 20 value 90.773640
iter 30 value 83.746482
iter 40 value 80.753327
iter 50 value 80.483305
iter 60 value 80.193608
iter 70 value 79.470210
iter 80 value 78.966418
iter 90 value 78.130903
iter 100 value 77.871180
final value 77.871180
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 120.478566
iter 10 value 94.469939
iter 20 value 86.112125
iter 30 value 82.190126
iter 40 value 80.603075
iter 50 value 79.956046
iter 60 value 78.242642
iter 70 value 77.799016
iter 80 value 77.492170
iter 90 value 77.462927
iter 100 value 77.406700
final value 77.406700
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 139.808078
iter 10 value 94.664582
iter 20 value 89.779000
iter 30 value 85.676556
iter 40 value 84.368391
iter 50 value 81.828606
iter 60 value 81.229665
iter 70 value 80.358411
iter 80 value 79.921197
iter 90 value 78.573709
iter 100 value 77.177613
final value 77.177613
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.979527
iter 10 value 94.406731
iter 20 value 88.962559
iter 30 value 82.192841
iter 40 value 81.764825
iter 50 value 81.566705
iter 60 value 80.261502
iter 70 value 79.338922
iter 80 value 79.188367
iter 90 value 78.365063
iter 100 value 77.777666
final value 77.777666
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 117.580469
iter 10 value 95.638775
iter 20 value 86.377488
iter 30 value 84.840535
iter 40 value 82.150757
iter 50 value 79.157072
iter 60 value 78.212023
iter 70 value 78.031565
iter 80 value 77.838112
iter 90 value 77.492562
iter 100 value 77.260017
final value 77.260017
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 116.596202
iter 10 value 93.868256
iter 20 value 84.013059
iter 30 value 81.577768
iter 40 value 79.619142
iter 50 value 78.984555
iter 60 value 78.854394
iter 70 value 78.632329
iter 80 value 78.396509
iter 90 value 77.999067
iter 100 value 77.789928
final value 77.789928
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.903143
final value 94.485965
converged
Fitting Repeat 2
# weights: 103
initial value 97.443853
iter 10 value 94.485956
iter 20 value 94.476368
iter 30 value 84.725718
iter 40 value 83.140927
iter 50 value 81.177166
iter 60 value 81.008070
iter 70 value 81.003526
iter 80 value 81.003260
final value 81.003213
converged
Fitting Repeat 3
# weights: 103
initial value 94.868220
final value 94.486056
converged
Fitting Repeat 4
# weights: 103
initial value 108.837282
final value 94.485772
converged
Fitting Repeat 5
# weights: 103
initial value 103.042631
final value 94.485868
converged
Fitting Repeat 1
# weights: 305
initial value 96.287998
iter 10 value 94.495642
iter 20 value 89.739453
iter 30 value 86.950557
iter 40 value 86.949170
iter 50 value 86.944659
iter 60 value 85.112672
iter 70 value 82.478219
iter 80 value 82.472216
iter 90 value 82.378508
iter 100 value 82.300884
final value 82.300884
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 96.319332
iter 10 value 91.496645
iter 20 value 85.530422
iter 30 value 84.819724
iter 40 value 84.818723
iter 50 value 84.818221
iter 60 value 84.815705
iter 70 value 84.215005
iter 80 value 84.212888
iter 90 value 84.212356
final value 84.211725
converged
Fitting Repeat 3
# weights: 305
initial value 95.068943
iter 10 value 94.447757
iter 20 value 94.440096
iter 30 value 85.217401
iter 40 value 80.663405
iter 50 value 79.311561
iter 60 value 77.263680
iter 70 value 77.068908
iter 80 value 77.068465
final value 77.067909
converged
Fitting Repeat 4
# weights: 305
initial value 137.594802
iter 10 value 94.489560
iter 20 value 94.485195
iter 30 value 94.255866
iter 40 value 86.068720
iter 50 value 85.742750
iter 60 value 80.428235
iter 70 value 80.263824
iter 80 value 80.263096
iter 90 value 80.014807
iter 100 value 79.991781
final value 79.991781
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 95.020200
iter 10 value 82.756003
iter 20 value 82.477842
iter 30 value 82.473953
iter 40 value 82.472295
iter 50 value 79.783313
iter 60 value 78.479630
iter 70 value 78.388924
iter 80 value 78.367118
final value 78.367083
converged
Fitting Repeat 1
# weights: 507
initial value 96.112758
iter 10 value 94.162983
iter 20 value 94.158100
iter 30 value 94.007672
iter 40 value 84.651775
iter 50 value 80.859647
iter 60 value 79.708093
iter 70 value 79.366652
iter 80 value 79.093516
iter 90 value 78.681968
iter 100 value 76.776316
final value 76.776316
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 96.961454
iter 10 value 94.197689
iter 20 value 94.192056
iter 30 value 89.001339
iter 40 value 85.311748
iter 50 value 85.293434
iter 60 value 85.292642
iter 70 value 85.200577
iter 80 value 85.162615
iter 90 value 85.162175
final value 85.161929
converged
Fitting Repeat 3
# weights: 507
initial value 98.894215
iter 10 value 94.455520
iter 20 value 94.257865
iter 30 value 94.018601
iter 40 value 93.994927
final value 93.992561
converged
Fitting Repeat 4
# weights: 507
initial value 96.518844
iter 10 value 93.999506
iter 20 value 93.992387
iter 30 value 93.967843
final value 93.967837
converged
Fitting Repeat 5
# weights: 507
initial value 96.163727
iter 10 value 94.262810
iter 20 value 94.257665
iter 30 value 93.978139
iter 40 value 93.977263
iter 50 value 93.975467
iter 60 value 93.975282
iter 70 value 93.975052
final value 93.975020
converged
Fitting Repeat 1
# weights: 305
initial value 139.968367
iter 10 value 117.875505
iter 20 value 108.533945
iter 30 value 103.806051
iter 40 value 102.794329
iter 50 value 102.158159
iter 60 value 101.856718
iter 70 value 101.342043
iter 80 value 101.257764
iter 90 value 101.213397
iter 100 value 101.158558
final value 101.158558
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 127.358689
iter 10 value 118.397302
iter 20 value 116.283995
iter 30 value 115.531132
iter 40 value 115.338299
iter 50 value 108.870083
iter 60 value 105.816465
iter 70 value 104.998062
iter 80 value 104.721896
iter 90 value 103.841446
iter 100 value 103.355962
final value 103.355962
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 141.056648
iter 10 value 117.904052
iter 20 value 114.150751
iter 30 value 110.013916
iter 40 value 106.014490
iter 50 value 105.444851
iter 60 value 104.157582
iter 70 value 103.514031
iter 80 value 103.043413
iter 90 value 102.409584
iter 100 value 101.810771
final value 101.810771
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 132.931308
iter 10 value 118.147429
iter 20 value 113.972875
iter 30 value 111.973080
iter 40 value 106.849982
iter 50 value 105.300400
iter 60 value 104.875180
iter 70 value 103.887320
iter 80 value 103.645454
iter 90 value 102.909250
iter 100 value 102.222177
final value 102.222177
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 136.063654
iter 10 value 118.031636
iter 20 value 115.467510
iter 30 value 114.954470
iter 40 value 113.568666
iter 50 value 109.152280
iter 60 value 108.280346
iter 70 value 104.919323
iter 80 value 104.113359
iter 90 value 102.530745
iter 100 value 101.956169
final value 101.956169
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 -- Mon Oct 16 03:09:42 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
40.07 1.64 42.31
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 28.35 | 1.40 | 29.78 | |
| FreqInteractors | 0.25 | 0.02 | 0.28 | |
| calculateAAC | 0.05 | 0.00 | 0.05 | |
| calculateAutocor | 0.37 | 0.08 | 0.45 | |
| calculateCTDC | 0.08 | 0.00 | 0.08 | |
| calculateCTDD | 0.69 | 0.07 | 0.76 | |
| calculateCTDT | 0.26 | 0.00 | 0.27 | |
| calculateCTriad | 0.35 | 0.00 | 0.36 | |
| calculateDC | 0.08 | 0.00 | 0.08 | |
| calculateF | 0.34 | 0.02 | 0.36 | |
| calculateKSAAP | 0.10 | 0.00 | 0.09 | |
| calculateQD_Sm | 1.54 | 0.09 | 1.64 | |
| calculateTC | 1.60 | 0.05 | 1.64 | |
| calculateTC_Sm | 0.22 | 0.02 | 0.23 | |
| corr_plot | 27.85 | 0.90 | 28.77 | |
| enrichfindP | 0.59 | 0.05 | 13.42 | |
| enrichfind_hp | 0.05 | 0.03 | 1.01 | |
| enrichplot | 0.23 | 0.02 | 0.25 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.02 | 0.00 | 2.49 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0.01 | 0.00 | 0.01 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.08 | 0.00 | 0.08 | |
| pred_ensembel | 12.34 | 0.37 | 9.47 | |
| var_imp | 29.30 | 0.77 | 30.08 | |