Two step particle swarm optimization to solve the feature selection problem

被引：70

作者：

Bello, Rafael ^{[1
]}

Gomez, Yudel ^{[1
]}

Nowe, Ann ^{[2
]}

Garcia, Maria M. ^{[1
]}

机构：

[1] Univ Cent Las Villas, Dept Comp Sci, Santa Clara, Cuba

[2] Vrije Univ Brussel, Dept Comp Sci, Comp Lab, Brussels, Belgium

来源：

PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS | 2007年

关键词：

FEATURE SUBSET-SELECTION; SYSTEM; COLONY;

D O I：

10.1109/ISDA.2007.101

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we propose a new model of Particle Swarm Optimization called Two-Step PSO. The basic idea is to split the heuristic search performed by particles into two stages. We have studied the performance of this new algorithm for the Feature Selection problem by using the reduct concept of the Rough Set Theory. Experimental results obtained show that the Two-step approach improves over the PSO model in calculating reducts, with the same computational cost.

引用

页码：691 / +

页数：3

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