TY - GEN
T1 - An improved binary particle swarm optimisation for gene selection in classifying cancer classes
AU - Mohamad, Mohd Saberi
AU - Omatu, Sigeru
AU - Deris, Safaai
AU - Yoshioka, Michifumi
AU - Zainal, Anazida
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - Gene selection
KW - Hybrid approach
KW - Microarray data
KW - Particle swarm optimisation
UR - http://www.scopus.com/inward/record.url?scp=77952568219&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77952568219&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-02481-8_72
DO - 10.1007/978-3-642-02481-8_72
M3 - Conference contribution
AN - SCOPUS:77952568219
SN - 3642024807
SN - 9783642024801
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 495
EP - 502
BT - Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings
T2 - 10th International Work-Conference on Artificial Neural Networks, IWANN 2009
Y2 - 10 June 2009 through 12 June 2009
ER -