Speciated GA for optimal ensemble classifiers in DNA microarray classification

Sung Bae Cho, Chanho Park

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

3 Citations (Scopus)

Abstract

With a development of microarray technology, the classification of microarray data has arisen as an important topic over the past decade. From various feature selection methods and classifiers, it is very hard to find a perfect method to classify microarray data due to the incompleteness of algorithms, the defects of data, etc. This paper proposes a sophisticated ensemble of such features and classifiers to obtain high classification performance. Speciated genetic algorithm has been exploited to get the diverse ensembles of features and classifiers in a reasonable time. Experimental results with two well-known datasets indicate that the proposed method finds many good ensembles that are superior to other individual classifiers.

Original languageEnglish
Title of host publicationProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Pages590-597
Number of pages8
Publication statusPublished - 2004 Sep 13
EventProceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR, United States
Duration: 2004 Jun 192004 Jun 23

Publication series

NameProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Volume1

Other

OtherProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
CountryUnited States
CityPortland, OR
Period04/6/1904/6/23

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All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Cho, S. B., & Park, C. (2004). Speciated GA for optimal ensemble classifiers in DNA microarray classification. In Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 (pp. 590-597). (Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004; Vol. 1).