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
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;
Conference_Titel :
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN :
0-7803-8515-2
DOI :
10.1109/CEC.2004.1330911