sar is a Rough Set-based Attribute Reduction (aka Feature Selection) implementation. This is an implementation of ideas described, among other places, in the following paper: Qiang Shen and Alexios Chouchoulas, A Modular Approach to Generating Fuzzy Rules with Reduced Attributes for the Monitoring of Complex Systems. Engineering Applications of Artificial Intelligence, 13(3):263-278, 2000. rsar reads in a MIMO (Multiple Input, Multiple Output) dataset, performs RS-based feature selection on it, and returns the selected feature subset. Four versions of the QuickReduct algorithm are supported, QuickReduct, QuickReduct III, QuickReduct IV and QuickReduct V (progressively faster implementations). QuickReduct II is a backward elimination version of QuickReduct and is not supported yet neither is exhaustive search for reducts.

96913396rsar_1.3.3.tar

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