File Entry: An Improved Binary Particle Swarm Optimisation for Gene Selection in Classifying Cancer Classes.

Created: 2012-05-11 01:58:19
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Version created on: 2012-05-11 01:58:19


Information Description

 The application of microarray data for cancer classification has recently

gained in popularity. The main problem that needs to be addressed is the
selection of a smaller subset of genes from the thousands of genes in the data that
contributes to a disease. This selection process is difficult because of the availability
of the small number of samples compared to the huge number of genes,
many irrelevant genes, and noisy genes. Therefore, this paper proposes an improved
binary particle swarm optimisation to select a near-optimal (smaller) subset
of informative genes that is relevant for cancer classification. Experimental
results show that the performance of the proposed method is superior to a standard
version of particle swarm optimisation and other related previous works in
terms of classification accuracy and the number of selected genes.

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