A multi-objective particle swarm optimization algorithm for rule discovery

Sheng Tun Li, Chih Chuan Chen, Jian Wei Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Rule discovery is usually posed as a multi-objective optimization problem with two criteria, predictive accuracy and comprehensibility. Single-objective particle swarm optimization algorithm, which combines the two criteria into one, has been shown to have convincing results on the classification tasks. However, it does not take the nature of the optimality conditions for multiple objectives into account. It is well known that accuracy and comprehensibility are hardly attainable simultaneously, which makes the optimization problem difficult to solve efficiently. In this paper, we propose a multi-objective PSO algorithm to solve the problem. The experimental result shows that our algorithm has better performance than its single-objective counterpart.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007.
Pages597-600
Number of pages4
DOIs
Publication statusPublished - 2007
Event3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007 - Kaohsiung, Taiwan
Duration: 2007 Nov 262007 Nov 28

Publication series

NameProceedings - 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007.
Volume2

Other

Other3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007
Country/TerritoryTaiwan
CityKaohsiung
Period07-11-2607-11-28

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Information Systems and Management

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