Structure-Based Attribute Reduction in Variable Precision Rough Set Models | Zendy

Masahiro Inuiguchi | Zendy

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Structure-Based Attribute Reduction in Variable Precision Rough Set Models

Author(s) -

Masahiro Inuiguchi

Publication year - 2006

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2006.p0657

Subject(s) - rough set , reduction (mathematics) , computer science , data mining , set (abstract data type) , attribute domain , variable (mathematics) , artificial intelligence , algorithm , pattern recognition (psychology) , mathematics , mathematical analysis , geometry , programming language

In this paper, structure-enhancing approaches to attribute reduction are proposed. Ten kinds of meaningful reducts are defined. The relations among them are clarified. Moreover their relations to reducts by structure-preserving approaches are also investigated. A few computational approaches to the proposed reducts are briefly described.

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