Data Mining Approach for Classifying Gene Expression Data of Cancer
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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 ...
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.
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