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Microarray data has been widely applied to cancer classification, where the purpose is to classify and predict the category of a sample by its gene expression profile. DNA microarray is a gene chip which consists of expression levels for a huge number of genes on a relatively small number of samples. Out of this huge number of genes, only a small number are contributing to accurate cancer classification. So the challenging task is to identify a small subset of informative genes which have maximum amount of information about class and it also minimizes the classification errors. Recently, data mining has become a a great tool for the process of extracting the hidden and useful information from huge noisy data sets.