An Effective Gene Selection Method Based on Relevance Analysis and Discernibility Matrix.

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. [ABSTRACT FROM AUTHOR]