Particle swarm algorithm for minimal attribute reduction of decision data tables

被引：10
|
作者：
Dai, Jianhua [1 ]
Chen, Weidong [1 ]
Gu, Hongying [1 ]
Pan, Yunhe [1 ]
机构：
[1] Zhejiang Univ, Inst Artificial Intelligence, Hangzhou 310027, Peoples R China
来源：
FIRST INTERNATIONAL MULTI-SYMPOSIUMS ON COMPUTER AND COMPUTATIONAL SCIENCES (IMSCCS 2006), PROCEEDINGS, VOL 2 | 2006年
关键词：
D O I：
10.1109/IMSCCS.2006.249
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Attribute reduction is an important issue when dealing with huge amounts of data. It has been proved that computing the minimal reduct of a decision data table is NP-complete. Particle swarm algorithm is a new population based stochastic optimization strategy inspired by social behavior of bird flocking and fish schooling. In this paper, a novel particle swarm algorithm for the minimal reduction problem is proposed. Our algorithm gives a new idea to the minimal reduction problem. The implementation techniques of the algorithm are presented. The effectiveness is showed in the experiment.
引用
收藏
页码：572 / +
页数：2
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