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An Algorithm of Attribute Reduction Based on Data Analysis Method

Feng Chong-ling

Open publisher page 1 citations

Abstract

Attribute reduction is one of important topics in the research on rough set theory. The methed of attribute reduction by the data analysis method is discussed in this paper. This algorithm is easy to be understand, can obtain all attribute reductions, and overcomes the problem of no completeness of heuristic algorithm, as well as the waste questions of the time and space based on discrimination matrix attribute reduction. The example indicated this algorithm is effective.

About this research paper

What this paper is about

Attribute reduction is one of important topics in the research on rough set theory. The methed of attribute reduction by the data analysis method is discussed in this paper. This algorithm is easy to be understand, can obtain all attribute reductions, and overcomes the problem of no completeness of heuristic algorithm, as well as the waste questions of the time and space based on discrimination matrix attribute reduction. The example indicated this algorithm is effective.

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Available abstract

Attribute reduction is one of important topics in the research on rough set theory. The methed of attribute reduction by the data analysis method is discussed in this paper. This algorithm is easy to be understand, can obtain all attribute reductions, and overcomes the problem of no completeness of heuristic algorithm, as well as the waste questions of the time and space based on discrimination matrix attribute reduction. The example indicated this algorithm is effective.

Key concepts: Computer science, Rough set, Attribute domain, Reduction (mathematics), Completeness (order theory), Heuristic, Data mining, Data reduction

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