Paper Title:
Microarray Data Classification Based on Evolutionary Multiple Classifier System
  Abstract

Designing an evolutionary multiple classifier system (MCS) is a relatively new research area. In this paper, we propose a genetic algorithm (GA) based MCS for microarray data classification. We construct a feature poll with different feature selection methods first, and then a multi-objective GA is applied to implement ensemble feature selection process so as to generate a set of classifiers. When this GA stops, a set of base classifiers are generated. Here we use all the nondominated individuals in last generation to build an ensemble system and test the proposed ensemble method and the method that apply a classifier selection process to select proper classifiers from all the individuals in last generation. The experimental results show the proposed ensemble method is roubust and can lead to promising results.

  Info
Periodical
Edited by
Han Zhao
Pages
2077-2080
DOI
10.4028/www.scientific.net/AMM.130-134.2077
Citation
Z. G. Gu, K. H. Liu, "Microarray Data Classification Based on Evolutionary Multiple Classifier System", Applied Mechanics and Materials, Vols. 130-134, pp. 2077-2080, 2012
Online since
October 2011
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Price
$32.00
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