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Title of Journal: Soft Comput

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Abbravation: Soft Computing

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Springer Berlin Heidelberg

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DOI

10.1007/bf00354241

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1433-7479

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Minimal attribute reduction with rough set based o

Authors: Yu Jiang Yang Yu
Publish Date: 2015/03/12
Volume: 20, Issue: 6, Pages: 2233-2243
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Abstract

Minimal attribute reduction plays an important role in rough set Heuristic algorithms are proposed in literature reviews to get a minimal reduction and yet an unresolved issue is that many redundancy nonempty elements involving duplicates and supersets exist in discernibility matrix To be able to eliminate the related redundancy and pointless elements in this paper we propose a compactness discernibility information tree CDItree The CDItree has the ability to map nonempty elements into one path and allow numerous nonempty elements share the same prefix which is recognized as a compact structure to store nonempty elements in discernibility matrix A complete algorithm is presented to address Pawlak reduction based on CDItree The experiment results reveal that the proposed algorithm is more efficient than the benchmark algorithms to find out a minimal attribute reduction

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