FSelectorRcpp: 'Rcpp' Implementation of 'FSelector' Entropy-Based Feature Selection Algorithms with a Sparse Matrix Support

'Rcpp' (free of 'Java'/'Weka') implementation of 'FSelector' entropy-based feature selection algorithms based on an MDL discretization (Fayyad U. M., Irani K. B.: Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning. In 13'th International Joint Conference on Uncertainly in Artificial Intelligence (IJCAI93), pages 1022-1029, Chambery, France, 1993.) <https://www.ijcai.org/Proceedings/93-2/Papers/022.pdf> with a sparse matrix support. It is also equipped with a parallel backend.

Version: 0.1.8
Depends: R (≥ 3.3.2)
Imports: Rcpp (≥ 0.12.12), foreach, iterators
LinkingTo: Rcpp, BH, RcppArmadillo, testthat
Suggests: testthat, Matrix, RcppArmadillo, dplyr, RWeka, entropy, FSelector, randomForest, doParallel, rpart, MASS, covr, parallel, htmltools, magrittr, knitr, RTCGA.rnaseq, ggplot2, microbenchmark, pbapply, tibble, rmarkdown, lintr
Published: 2017-09-05
Author: Zygmunt Zawadzki [aut, cre], Marcin Kosinski [aut], Krzysztof Slomczynski [ctb], Damian Skrzypiec [ctb]
Maintainer: Zygmunt Zawadzki <zygmunt at zstat.pl>
BugReports: https://github.com/mi2-warsaw/FSelectorRcpp/issues
License: GPL-2
URL: http://mi2-warsaw.github.io/FSelectorRcpp/
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: FSelectorRcpp results

Downloads:

Reference manual: FSelectorRcpp.pdf
Vignettes: Microbenchmarks of FSelectoRcpp and FSelector - discretization
Get started: Motivation, Installation and Quick Workflow
Package source: FSelectorRcpp_0.1.8.tar.gz
Windows binaries: r-devel: FSelectorRcpp_0.1.8.zip, r-release: FSelectorRcpp_0.1.8.zip, r-oldrel: FSelectorRcpp_0.1.8.zip
OS X El Capitan binaries: r-release: FSelectorRcpp_0.1.8.tgz
OS X Mavericks binaries: r-oldrel: not available
Old sources: FSelectorRcpp archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=FSelectorRcpp to link to this page.