抄録
We apply a combined method of heuristic attribute reduction and evaluation of relative reducts in rough set theory to gene expression data analysis. Our method extracts as many relative reducts as possible from gene expression data and select the best relative reduct from a viewpoint of constructing useful decision rules. As an experimental result, our method extracted decision rules about a gene that has been identified as a novel biomarker of human breast cancer in recent studies. This result indicates a possibility of our method as a useful tool for gene expression data analysis.
