Evolutionary computation for optimal ensemble classifier in lymphoma cancer classification

Chanho Park, Sung-Bae Cho

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

11 Citations (Scopus)

Abstract

Owing to the development of DNA microarray technologies, it is possible to get thousands of expression levels of genes at once. If we make the effective classification system with such acquired data, we can predict the class of new sample, whether it is normal or patient. For the classification system, we can use many feature selection methods and classifiers, but a method cannot be superior to the others absolutely for feature selection or classification. Ensemble classifier has been using to yield improved performance in this situation, but it is almost impossible to get all ensemble results, if there are many feature selection methods and classifiers to be used for ensemble. In this paper, we propose GA based method for searching optimal ensemble of feature-classifier pairs on Lymphoma cancer dataset. We have used two ensemble methods, and GA finds optimal ensemble very efficiently.

Original languageEnglish
Title of host publicationFoundations of Intelligent Systems - 14th International Symposium, ISMIS 2003, Proceedings
EditorsZbigniew W. Ras, Einoshin Suzuki, Ning Zhong, Shusaku Tsumoto
PublisherSpringer Verlag
Pages521-530
Number of pages10
ISBN (Print)3540202560, 9783540202561
Publication statusPublished - 2003 Jan 1
Event14th International Symposium on Methodologies for Intelligent Systems, ISMIS 2003 - Maebashi City, Japan
Duration: 2003 Oct 282003 Oct 31

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2871
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th International Symposium on Methodologies for Intelligent Systems, ISMIS 2003
CountryJapan
CityMaebashi City
Period03/10/2803/10/31

Fingerprint

Cancer Classification
Ensemble Classifier
Evolutionary Computation
Evolutionary algorithms
Ensemble
Classifiers
Feature Selection
Feature extraction
Classifier
Ensemble Methods
DNA Microarray
Microarrays
Cancer
DNA
Genes
Gene
Predict
Gas

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Park, C., & Cho, S-B. (2003). Evolutionary computation for optimal ensemble classifier in lymphoma cancer classification. In Z. W. Ras, E. Suzuki, N. Zhong, & S. Tsumoto (Eds.), Foundations of Intelligent Systems - 14th International Symposium, ISMIS 2003, Proceedings (pp. 521-530). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2871). Springer Verlag.
Park, Chanho ; Cho, Sung-Bae. / Evolutionary computation for optimal ensemble classifier in lymphoma cancer classification. Foundations of Intelligent Systems - 14th International Symposium, ISMIS 2003, Proceedings. editor / Zbigniew W. Ras ; Einoshin Suzuki ; Ning Zhong ; Shusaku Tsumoto. Springer Verlag, 2003. pp. 521-530 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Park, C & Cho, S-B 2003, Evolutionary computation for optimal ensemble classifier in lymphoma cancer classification. in ZW Ras, E Suzuki, N Zhong & S Tsumoto (eds), Foundations of Intelligent Systems - 14th International Symposium, ISMIS 2003, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2871, Springer Verlag, pp. 521-530, 14th International Symposium on Methodologies for Intelligent Systems, ISMIS 2003, Maebashi City, Japan, 03/10/28.

Evolutionary computation for optimal ensemble classifier in lymphoma cancer classification. / Park, Chanho; Cho, Sung-Bae.

Foundations of Intelligent Systems - 14th International Symposium, ISMIS 2003, Proceedings. ed. / Zbigniew W. Ras; Einoshin Suzuki; Ning Zhong; Shusaku Tsumoto. Springer Verlag, 2003. p. 521-530 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2871).

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

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Park C, Cho S-B. Evolutionary computation for optimal ensemble classifier in lymphoma cancer classification. In Ras ZW, Suzuki E, Zhong N, Tsumoto S, editors, Foundations of Intelligent Systems - 14th International Symposium, ISMIS 2003, Proceedings. Springer Verlag. 2003. p. 521-530. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).