Fuzzy Discretization for Rough Set Based Gene Selection Algorithm

Selection of reliable genes from micro array gene expression data is essential to carry out a diagnostic test and successful treatment. In this regard, a rough set based gene selection algorithm is developed recently to select genes from micro array data. In this paper, a fuzzy discretization method is proposed for rough set based gene selection algorithm to compute relevance and significance of continuous valued genes directly. The performance of the proposed fuzzy discretization method, along with a comparison with crisp counterpart, is presented in terms of classification accuracy of K-nearest neighbor rule and support vector machine on seven micro array data sets. An important finding is that the proposed discretization method is shown to be effective in selecting relevant and significant genes from micro array data.