./math/herisvm, svm-train wrapper running cross-validation in parallel

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Branch: CURRENT, Version: 0.8.0nb4, Package name: herisvm-0.8.0nb4, Maintainer: cheusov

herisvm project is a collection of simple tools implementing
evaluation algorithms for classification (machine learning).
In particular heri-eval implements N-fold cross-validation
where training and testing is run in parallel.
This may be useful if you use multi-CPU computer.


Required to run:
[lang/ruby26-base]

Required to build:
[devel/mk-configure] [pkgtools/cwrappers]

Master sites:

Filesize: 14.949 KB

Version history: (Expand)

CVS history: (Expand)


   2024-02-10 15:42:40 by Takahiro Kambe | Files touched by this commit (21) 
Log message:
Bump revision by changing default version of Ruby.
   2022-10-11 16:38:48 by Takahiro Kambe | Files touched by this commit (6) 
Log message:
Bump revision by default Ruby's version change.
   2021-10-26 12:56:13 by Nia Alarie | Files touched by this commit (458) 
Log message:
math: Replace RMD160 checksums with BLAKE2s checksums

All checksums have been double-checked against existing RMD160 and
SHA512 hashes
   2021-10-07 16:28:36 by Nia Alarie | Files touched by this commit (458) 
Log message:
math: Remove SHA1 hashes for distfiles
   2021-07-21 16:40:32 by Takahiro Kambe | Files touched by this commit (29) 
Log message:
Bump PKGREVISION for affected packages by changing default Ruby's version.
   2019-12-15 16:38:59 by Takahiro Kambe | Files touched by this commit (12) 
Log message:
Bump PKGREVISION by change of default Ruby version

Bump PKGREVISION by change of default Ruby version from 2.4.x to 2.6.x.
These packages are depends on Ruby in some ways.
   2017-02-17 12:12:15 by Aleksey Cheusov | Files touched by this commit (2) 
Log message:
Update herisvm to 0.8.0
   2016-07-25 11:18:51 by Aleksey Cheusov | Files touched by this commit (4) 
Log message:
import herisvm-0.7.0

herisvm project is a collection of simple tools implementing
evaluation algorithms for classification (machine learning).
In particular heri-eval implements N-fold cross-validation
where training and testing is run in parallel.
This may be useful if you use multi-CPU computer.