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A Discretization Algorithm for Decision Table in Rough Set Theory

Shi YunPing

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Abstract

Discretization of continuous attributes is one of important problems in Machine Learning,Data Mining and the other research area.The algorithm of this paper is based on the rough set theory and the importance of condition attributes.Firstly,the paper gives some concept of rough set theory:decision table,indiscernible relation,information entropy and condition entropy.And then discusses the problem of discretization,a discretization algorithm of continue attributes in rough set based on the importance of condition attributes is illustrated.

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What this paper is about

Discretization of continuous attributes is one of important problems in Machine Learning,Data Mining and the other research area.The algorithm of this paper is based on the rough set theory and the importance of condition attributes.Firstly,the paper gives some concept of rough set theory:decision table,indiscernible relation,information entropy and condition entropy.And then discusses the problem of discretization,a discretization algorithm of continue attributes in rough set based on the importance of condition attributes is illustrated.

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Available abstract

Discretization of continuous attributes is one of important problems in Machine Learning,Data Mining and the other research area.The algorithm of this paper is based on the rough set theory and the importance of condition attributes.Firstly,the paper gives some concept of rough set theory:decision table,indiscernible relation,information entropy and condition entropy.And then discusses the problem of discretization,a discretization algorithm of continue attributes in rough set based on the importance of condition attributes is illustrated.

Key concepts: Rough set, Discretization, Discretization of continuous features, Decision table, Dominance-based rough set approach, Entropy (arrow of time), Mathematics, Algorithm

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