NDLI: Efficient hash-based approximate reduct generation

Content Provider	IEEE Xplore Digital Library
Author	Pai-Chou Wang
Copyright Year	2011
Description	Author affiliation: Department of Information Management, Southern Taiwan University, Tainan, Taiwan ROC (Pai-Chou Wang)
Abstract	Approximate reduct relaxes the requirement for the discernibility preserving and it can be applied to generate approximate decision rules. To compute such reducts, discernibility matrix and sorting are commonly used and they take $O(mn^{2})$ and $O(m^{2}n$ log n) respectively to generate a reduct where m is the total number of attributes and n is the total number of instances. Instead of applying these methods, this paper proposes a hash-based discerning algorithm and an approximate reduct can be generated in $O(m^{2}n)$ time. Empirical results of using four of ten most popular UCI datasets are presented and they are compared to the Rough Set Exploration System (RSES). Besides approximate reducts, the hash-based discerning algorithm can be extended to generate other reducts like possible reduct, dynamic reduct, and generalized reduct.
Starting Page	703
Ending Page	707
File Size	306470
Page Count	5
File Format	PDF
ISBN	9781457703720
e-ISBN	9781457703713
DOI	10.1109/GRC.2011.6122683
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-08
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis hash based discerning algorithm Merging Rough sets Approximation algorithms Approximation methods rough set theory Approximate reduct Sorting
Content Type	Text
Resource Type	Article

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