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.

Version: 0.3.3
Depends: R (≥ 3.4)
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, pkgdown
Published: 2020-01-24
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
Integer variables
Package source: FSelectorRcpp_0.3.3.tar.gz
Windows binaries: r-devel: FSelectorRcpp_0.3.3.zip, r-release: FSelectorRcpp_0.3.3.zip, r-oldrel: FSelectorRcpp_0.3.3.zip
macOS binaries: r-release: FSelectorRcpp_0.3.3.tgz, r-oldrel: FSelectorRcpp_0.3.3.tgz
Old sources: FSelectorRcpp archive

Reverse dependencies:

Reverse suggests: customLayout, mlr, mlr3filters, mlrCPO

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