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2006•Journal of Lanzhou Polytechnic CollegeRequires access

An Approach to Attribute Reduction Based on Rough Set Theory

Lei Wang

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Abstract

In this paper,the author discusses the attribute reduction in Rough Sets theory.The paper introduces the concept of the information quantity of decision attribute with relation to given condition attributes,and proves that its changing tendency is monotonously decreasing.The best attribute reduction is the set whose value is the minimum average of relevance of attributes.Then,a new attribute reduction algorithm based on information quantity is developed.An example shows that this algorithm is effective.

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What this paper is about

In this paper,the author discusses the attribute reduction in Rough Sets theory.The paper introduces the concept of the information quantity of decision attribute with relation to given condition attributes,and proves that its changing tendency is monotonously decreasing.The best attribute reduction is the set whose value is the minimum average of relevance of attributes.Then,a new attribute reduction algorithm based on information quantity is developed.An example shows that this algorithm is effective.

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Available abstract

In this paper,the author discusses the attribute reduction in Rough Sets theory.The paper introduces the concept of the information quantity of decision attribute with relation to given condition attributes,and proves that its changing tendency is monotonously decreasing.The best attribute reduction is the set whose value is the minimum average of relevance of attributes.Then,a new attribute reduction algorithm based on information quantity is developed.An example shows that this algorithm is effective.

Key concepts: Rough set, Attribute domain, Reduction (mathematics), Relevance (law), Mathematics, Relation (database), Data mining, Variable and attribute

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