Gene selection based on MDA-RS algorithm
基于MDA-RS算法的特征基因选取方法*

Feature gene selection is an essential step to establish the classification model.The dependency analysis method of rough set theory can effectively analyze the data.In order to get the atrribute which influenced the decision-making mostly, this paper proposed a novle method called MDA-RS.Here applied the MDA-RS method to gene selection.First applied heuristic K-means clustering algorithm to analyze these genes for clustering. Then selected a representative gene from the clusering gene using MDA-RS. Then considered the set of representative genes classification features. Finally used this method to analyze the gene expression profiles of colon tumor on support vector machine(SVM). The experimental result reveals that the proposed approach is feasible and effective. The algorithm selected genes which are mostly related with the disease classification.