A Survey on Different Feature Selection Methods for Microarray Data Analysis

Abstract

In the field of medical science diseases diagnosis by Tissue microarrays is one of the active areas of research .There are various gene selection techniques in the literature. Gene selection provides genes subsets that are capable to describe in which category those gene are (active, hyperactive or silent).Various application areas like combinatorial chemistry, text mining, multivariate imaging, or bioinformatics are using huge data sets. The problem has been addressed of selection of a small subset of genes from broad patterns of gene expression data, recorded on DNA micro-arrays for cancer classification. Usually till now survey paper discuss various conventional & evolutionary methods of gene selection like filters, wrappers methods.