2009•Unpublished venueRequires access

Attribute Reduction Based on Rough Neighborhood Approximation

Ming He, Yongping Du

Abstract

One of the main obstacles facing current data mining techniques is attribute reduction. This paper discusses the basic concepts of rough set, and studies two rough approximations operators under neighborhood systems. An attribute reduction method based on rough set theory and neighborhood systems is presented. The experimental results show that the method of attributes reduction with rough sets and neighborhood system is feasible and valid.

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Available abstract

Key concepts: Rough set, Reduction (mathematics), Data mining, Computer science, Set (abstract data type), Set theory, Dominance-based rough set approach, Mathematics