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A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification

Deris, Safaai and Omatu, Sigeru and Zainal, Anazida and Yoshioka, Michifuci and Mohamad, Mohd. Saberi (2008) A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification. Jurnal Teknologi Maklumat, 20 (4). pp. 155-162. ISSN 0128-3790

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Abstract

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 optimization 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 the experimental method and other related previous works in terms of classification accuracy and the number of selected genes.

Item Type:Article
Uncontrolled Keywords:gene selection, hybrid approach, microarray data, particle swarm optimization
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics
Divisions:Computer Science and Information System (Formerly known)
ID Code:8192
Deposited By: Farah Nadzirah Jamrus
Deposited On:02 Apr 2009 04:34
Last Modified:27 Oct 2010 03:46

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