Handling gene redundancy in microarray data using Grey Relational Analysis

Gene selection is one of the important and frequently used techniques for microarray data classification. In this paper, we introduce a new metric to measure gcne-class relevance and gene-gene redundancy. The new metric is based on Grey Relational Analysis (GRA), called Grey Relational Grade (GRG), and ricver used in gene selection before. Based on the GRG, we develop a nc\v gene selection method. WhiCh uses GRG to group similar genes to clusters, and then select inforniative genes frorri each cluster to avoid n redundancy. Experiments on public data sets demonstrate the effectiveness of the proposed method.