Microarray Data Classification Based on Evolutionary Multiple Classifier System

Abstract:

Article Preview

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 and 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

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.