2010Unpublished venueRequires access

The Algorithm for the Reduction of Decision Table Based on Rough Entropy

Song Lan

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Abstract

The attribute reduction is a core theory of the rough set theory. It has been proven that computing the optimal reduction of decision table is a NP-hard problem. In the paper here, the application of rough entropy in rough sets theory is analyzed, the uncertainty measure of the importance of attribute in decision table is proposed, then, a heuristic algorithm based on rough entropy for reduction of knowledge is proposed.

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What this paper is about

The attribute reduction is a core theory of the rough set theory. It has been proven that computing the optimal reduction of decision table is a NP-hard problem. In the paper here, the application of rough entropy in rough sets theory is analyzed, the uncertainty measure of the importance of attribute in decision table is proposed, then, a heuristic algorithm based on rough entropy for reduction of knowledge is proposed.

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Available abstract

The attribute reduction is a core theory of the rough set theory. It has been proven that computing the optimal reduction of decision table is a NP-hard problem. In the paper here, the application of rough entropy in rough sets theory is analyzed, the uncertainty measure of the importance of attribute in decision table is proposed, then, a heuristic algorithm based on rough entropy for reduction of knowledge is proposed.

Key concepts: Rough set, Decision table, Dominance-based rough set approach, Entropy (arrow of time), Reduction (mathematics), Computer science, Algorithm, Mathematics

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