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Author:

He, Ming (He, Ming.)

Indexed by:

CPCI-S EI Scopus

Abstract:

Reduct finding, especially optimal reduct finding, similar to feature selection problem, is a crucial task in rough set applications to data mining. In this paper, we have studied the basic concepts of rough set theory, and discussed several special cases of the Ant Colony Optimization metaheuristic algorithms. Based on the above study, we propose a feature selection algorithm within a mixed framework based on rough set theory and Ant Colony Optimization. Experimental results show that the algorithm of this paper is flexible for feature selection.

Keyword:

ant colony optimization feature selection rough set

Author Community:

  • [ 1 ] Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China

Reprint Author's Address:

  • [He, Ming]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China

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Related Keywords:

Source :

ICCEE 2008: PROCEEDINGS OF THE 2008 INTERNATIONAL CONFERENCE ON COMPUTER AND ELECTRICAL ENGINEERING

Year: 2008

Page: 70-72

Language: English

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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