Machine Learning Based Approaches for Cancer Classification Using Gene Expression Data

Abstract

The classification of different types of tumor is of great importance in cancer diagnosis and drug discovery. Earlier studies on cancer classification have limited diagnostic ability. The recent development of DNA microarray technology has made monitoring of thousands of gene expression simultaneously. By using this abundance of gene expression data researchers are exploring the possibilities of cancer classification. There are number of methods proposed with good results, but lot of issues still need to be addressed. This paper present an overview of various cancer classification methods and evaluate these proposed methods based on their classification accuracy, computational time and ability to reveal gene information. We have also evaluated and introduced various proposed gene selection method. In this paper, several issues related to cancer classification have also been discussed.