An Attribute Reduction Algorithm Based on Partition and Ant Colony Optimization

doi:10.13190/jbupt.201106.55.wangh

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2011, Vol. 34 ›› Issue (6): 55-58.doi: 10.13190/jbupt.201106.55.wangh

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An Attribute Reduction Algorithm Based on Partition and Ant Colony Optimization

Received:2011-06-02 Revised:2011-07-15 Online:2011-12-28 Published:2011-10-18
Contact: WANG Hui E-mail:wanghui_wwh@163.com

Abstract

Abstract:

To decrease the time complexity of the attribute reduction algorithm based on information entropy, the concurrent processing of ants colony optimization is introduced into partition. This process based on the judgement of attribute reduction between partition and information entropy. In this searching process the strategy of state transfer and pheromone update reflect the difference of the attribute’s importance in order to optimize the results. By the analysis of this algorithm’s complexity and the example’s application,it is shown that the algorithm can avoid the blindness of the ant colony searching and reduce the size of the iteration to obtain reduction faster.This is more suitable for large data base.

CLC Number:

TN929.53

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An Attribute Reduction Algorithm Based on Partition and Ant Colony Optimization

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