A GA-based approach for mining membership functions and concept-drift patterns

Chun Hao Chen, Yu Li, Tzung Pei Hong, Yan Kang Li, Eric Hsueh Chan Lu

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

1 Citation (Scopus)

Abstract

Since customers' behaviors may change over time in real applications, algorithms that can be utilized to mine these drift patterns are needed. In this paper, we propose a GA-based approach for mining fuzzy concept-drift patterns. It consists of two phases. The first phase mines membership functions and the second one finds fuzzy concept-drift patterns. In the first phase, appropriate membership functions for items are derived by GA with a designed fitness function. Then, the derived membership functions are utilized to mine fuzzy concept-drift patterns in the second phase. Experiments on simulated datasets are also made to show the effectiveness of the proposed approach.

Original languageEnglish
Title of host publication2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2961-2965
Number of pages5
ISBN (Electronic)9781479974924
DOIs
Publication statusPublished - 2015 Sep 10
EventIEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, Japan
Duration: 2015 May 252015 May 28

Publication series

Name2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

Other

OtherIEEE Congress on Evolutionary Computation, CEC 2015
CountryJapan
CitySendai
Period15-05-2515-05-28

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computational Mathematics

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