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

页码：572 / +

页数：2

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