DocumentCode
419048
Title
Speciated GA for optimal ensemble classifiers in DNA microarray classification
Author
Cho, Sung-Bae ; Park, Chanho
Author_Institution
Dept. of Comput. Sci., Yonsei Univ., South Korea
Volume
1
fYear
2004
fDate
19-23 June 2004
Firstpage
590
Abstract
With the development of microarray technology, the classification of microarray data has risen 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.
Keywords
DNA; biology computing; data analysis; feature extraction; genetic algorithms; genetics; pattern classification; DNA; feature selection; genetic algorithm; microarray classification; microarray data; microarray technology; optimal ensemble classifiers; Bioinformatics; Cancer; Computer science; DNA; Fluorescence; Gene expression; Genetic algorithms; Monitoring; Sequences; Solids;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN
0-7803-8515-2
Type
conf
DOI
10.1109/CEC.2004.1330911
Filename
1330911
Link To Document