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FSelectorRcpp  

'Rcpp' Implementation of 'FSelector' Entropy-Based Feature Selection Algorithms with a Sparse Matrix Support
View on CRAN: Click here


Download and install FSelectorRcpp package within the R console
Install from CRAN:
install.packages("FSelectorRcpp")

Install from Github:
library("remotes")
install_github("cran/FSelectorRcpp")

Install by package version:
library("remotes")
install_version("FSelectorRcpp", "0.3.13")



Attach the package and use:
library("FSelectorRcpp")
Maintained by
Zygmunt Zawadzki
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-03-06
Latest Update: 2024-10-02
Description:
'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.) with a sparse matrix support.
How to cite:
Zygmunt Zawadzki (2017). FSelectorRcpp: 'Rcpp' Implementation of 'FSelector' Entropy-Based Feature Selection Algorithms with a Sparse Matrix Support. R package version 0.3.13, https://cran.r-project.org/web/packages/FSelectorRcpp. Accessed 07 Aug. 2026.
Previous versions and publish date:
0.1.0 (2017-03-06 11:28), 0.1.2 (2017-03-12 22:39), 0.1.3 (2017-04-29 15:00), 0.1.8 (2017-09-05 10:12), 0.1.10 (2018-06-27 23:34), 0.2.1 (2018-08-02 12:30), 0.3.0 (2018-11-12 21:40), 0.3.1 (2019-04-22 13:40), 0.3.3 (2020-01-24 07:50), 0.3.7 (2020-10-08 11:20), 0.3.8 (2021-01-14 16:00), 0.3.10 (2023-04-23 11:50), 0.3.11 (2023-04-28 18:10), (2026-07-09 08:03)
Other packages that cited FSelectorRcpp R package
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Other R packages that FSelectorRcpp depends, imports, suggests or enhances
Complete documentation for FSelectorRcpp
Functions, R codes and Examples using the FSelectorRcpp R package
Some associated functions: cut_attrs . discretize . discretize_transform . feature_search . information_gain . relief . to_formula . 
Some associated R codes: RcppExports.R . cut_attrs.R . discretize.R . discretize_transform.R . feature_search.R . information_gain.R . relief.R . utils.R .  Full FSelectorRcpp package functions and examples
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