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A HEURISTIC ALGORITHM FOR REDUCTION OF KNOWLEDGE

Miao Duo

Open publisher page 159 citations

Abstract

Reduction of knowledge is one of the important topics in the research on rough set theory. It has been proven that computing the optimal (minimal) reduction of decision table is a NP hard problem. In the paper here, first, the significance of attributes in decision table is defined from the viewpoint of information; then, a heuristic algorithm based on mutual information for reduction of knowledge is proposed, and the complexity of this algorithm is analyzed; Finally, the experimental results show that this algorithm can find the minimal reduction for most decision tables.

About this research paper

What this paper is about

Reduction of knowledge is one of the important topics in the research on rough set theory. It has been proven that computing the optimal (minimal) reduction of decision table is a NP hard problem. In the paper here, first, the significance of attributes in decision table is defined from the viewpoint of information; then, a heuristic algorithm based on mutual information for reduction of knowledge is proposed, and the complexity of this algorithm is analyzed; Finally, the experimental results show that this algorithm can find the minimal reduction for most decision tables.

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OpenAlex reports 159 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Reduction of knowledge is one of the important topics in the research on rough set theory. It has been proven that computing the optimal (minimal) reduction of decision table is a NP hard problem. In the paper here, first, the significance of attributes in decision table is defined from the viewpoint of information; then, a heuristic algorithm based on mutual information for reduction of knowledge is proposed, and the complexity of this algorithm is analyzed; Finally, the experimental results show that this algorithm can find the minimal reduction for most decision tables.

Key concepts: Decision table, Reduction (mathematics), Rough set, Computer science, Heuristic, Algorithm, Set (abstract data type), Table (database)

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