A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2007; you can also visit the original URL.
The file type is application/pdf
.
GENETIC ALGORITHMS AND SILHOUETTE MEASURES APPLIED TO MICROARRAY DATA CLASSIFICATION
2005
Proceedings of the 3rd Asia-Pacific Bioinformatics Conference
Microarray technology allows large-scale parallel measurements of the expression of many thousands genes and thus aiding in the development of efficient cancer diagnosis and classification platforms. In this paper, we apply the genetic algorithm and the silhouette statistic in conjunction with several distance functions to the problem of multi-class prediction. We examine two widely used sets of gene expression data, measured across sets of tumors, and present the results of classification
doi:10.1142/9781860947322_0023
fatcat:ij4kdakonjbjfepwqhpulhlsz4