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Book Chapter
A Heuristic Algorithm for Maximum Distribution Reduction
Book Series
Lecture Notes in Computer Science
Publisher
Springer Berlin / Heidelberg
ISSN
0302-9743 (Print) 1611-3349 (Online)
Volume
Volume 3613/2005
Book
Fuzzy Systems and Knowledge Discovery
DOI
10.1007/11539506
Copyright
2005
ISBN
978-3-540-28312-6
Category
Rough Sets
DOI
10.1007/11539506_163
Pages
1297-1302
Subject Collection
Computer Science
SpringerLink Date
Friday, July 29, 2005
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Rough Sets
A Heuristic Algorithm for Maximum Distribution Reduction
Xiaobing Pei
1
and YuanZhen Wang
1
(1)
Department of Computer Science, HuaZhong University of Science & Technology, Wuhan, Hubei 430074, China
Abstract
Attribute reduction is one of the basic contents in decision table. And it has been proved that computing the optimal attribute reduction is NP-complete. A lot of algorithms for the optimal attribute reduction were proposed in consistent decision table. But most decision tables are inconsistent in fact. In this paper, the judgment theorem with respect to maximum distribution reduction is obtained and the significance of attributes is defined in decision table, from which a polynomial heuristic algorithm for the optimal maximum distribution reduction is proposed. Finally, the experimental results show that this algorithm is effective and efficient.
Xiaobing
Pei
Email:
xiaobingp@tom.com
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