Particle Swarm Algorithm for Minimal Attribute Reduction of Decision Data Tables

Author

Dai, Jianhua ; Chen, Weidong ; Gu, Hongying ; Pan, Yunhe

Author_Institution

Inst. of Artificial Intelligence, Zhejiang Univ.

Volume

2

fYear

2006

fDate

20-24 June 2006

Firstpage

572

Lastpage

575

Abstract

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

Keywords

computational complexity; data mining; data reduction; decision tables; particle swarm optimisation; very large databases; bird flocking social behavior; decision data tables; fish schooling; minimal attribute reduction; particle swarm algorithm; stochastic optimization strategy; Artificial intelligence; Birds; Data mining; Educational institutions; Heuristic algorithms; Marine animals; Optimization methods; Particle swarm optimization; Set theory; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on

Conference_Location

Hanzhou, Zhejiang

Print_ISBN

0-7695-2581-4

Type

conf

DOI

10.1109/IMSCCS.2006.249

Filename

4673767