'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.


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install.packages("FSelectorRcpp")

0.1.8 by Zygmunt Zawadzki, 3 months ago


http://mi2-warsaw.github.io/FSelectorRcpp/


Report a bug at https://github.com/mi2-warsaw/FSelectorRcpp/issues


Browse source code at https://github.com/cran/FSelectorRcpp


Authors: Zygmunt Zawadzki [aut, cre], Marcin Kosinski [aut], Krzysztof Slomczynski [ctb], Damian Skrzypiec [ctb]


Documentation:   PDF Manual  


GPL-2 license


Imports Rcpp, foreach, iterators

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

Linking to Rcpp, BH, RcppArmadillo, testthat

System requirements: C++11


See at CRAN