An effective gene selection method based on relevance analysis and discernibility matrix

Authors:
Li-Juan Zhang;Zhou-Jun Li;Huo-Wang Chen
Affiliations:
National Laboratory for Parallel and Distributed Processing, Changsha, China;School of Computer Science & Engineering, Beihang University, Beijing, China;National Laboratory for Parallel and Distributed Processing, Changsha, China
Venue:
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2007

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Abstract

Selecting a small number of discriminative genes from thousands of genes in microarray data is very important for accurate classification of diseases or phenotypes. In this paper, we provide more elaborate and complete definitions of feature relevance and develop a novel feature selection method, which is based on relevance analysis and discernibility matrix to select small enough genes and improve the classification accuracy. The extensive experimental study using microarray data shows the proposed approach is very effective in selecting genes and improving classification accuracy.