'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.


Reference manual

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0.1.8 by Zygmunt Zawadzki, 14 days ago


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