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Heuristic algorithm to rough set attribute reduction based on discernibility matrix

Shi Chang-qiong

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Abstract

An algorithm to heuristic knowledge reduction based on discernibility matrix is proposed. According to the frequency of at- tribute in discernibility matrix, a new information system is designed and the maximum attribute every time is selected, until the selected attribute can discern information system, then all selected attribute is a reduction. The practical results show that in the most cases the minimum or a feasible solution reduction is obtained using the proposed method.

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What this paper is about

An algorithm to heuristic knowledge reduction based on discernibility matrix is proposed. According to the frequency of at- tribute in discernibility matrix, a new information system is designed and the maximum attribute every time is selected, until the selected attribute can discern information system, then all selected attribute is a reduction. The practical results show that in the most cases the minimum or a feasible solution reduction is obtained using the proposed method.

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Available abstract

An algorithm to heuristic knowledge reduction based on discernibility matrix is proposed. According to the frequency of at- tribute in discernibility matrix, a new information system is designed and the maximum attribute every time is selected, until the selected attribute can discern information system, then all selected attribute is a reduction. The practical results show that in the most cases the minimum or a feasible solution reduction is obtained using the proposed method.

Key concepts: Rough set, Reduction (mathematics), Computer science, Heuristic, Matrix (chemical analysis), Algorithm, Set (abstract data type), Data mining

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