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Decision algorithm for finding reduct based on approximation quality of rough set

HU Shou-song

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Abstract

The rough set theory is studied, and an algorithm for finding attribute-oriented reduct based on approximation quality of rough set is presented. With all the condition attributes as the initial reduct, this algorithm takes the approximation quality of rough set as the iterative criterion to assure that the classification ability of the resulted reduct does not decline. The time complexity of the algorithm is analyzed and an example is investigated to verify this algorithm. The results show this algorithm can find the attribute-oriented reduct effectively with less computational effort.

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What this paper is about

The rough set theory is studied, and an algorithm for finding attribute-oriented reduct based on approximation quality of rough set is presented. With all the condition attributes as the initial reduct, this algorithm takes the approximation quality of rough set as the iterative criterion to assure that the classification ability of the resulted reduct does not decline. The time complexity of the algorithm is analyzed and an example is investigated to verify this algorithm. The results show this algorithm can find the attribute-oriented reduct effectively with less computational effort.

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Available abstract

The rough set theory is studied, and an algorithm for finding attribute-oriented reduct based on approximation quality of rough set is presented. With all the condition attributes as the initial reduct, this algorithm takes the approximation quality of rough set as the iterative criterion to assure that the classification ability of the resulted reduct does not decline. The time complexity of the algorithm is analyzed and an example is investigated to verify this algorithm. The results show this algorithm can find the attribute-oriented reduct effectively with less computational effort.

Key concepts: Reduct, Rough set, Set (abstract data type), Algorithm, Mathematics, Quality (philosophy), Data mining, Computer science

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