Development of an Efficient Data Mining Classifier With Microarray Data Set for Gene Selection and Classification

Microarray sample classification has been studied extensively using classification techniques in machine learning and pattern recognition. In a microarray chip, the number of genes available is far greater than that of samples, which is a serious problem and the gene expression reduction, is important one. Prior to sample classification, it is important to perform gene selection and more interpretable genes to be identified as biomarkers, so that a more efficient, accurate, and reliable performance in classification can be achieved. For this purpose, a hybrid scheme was proposed and this scheme is called as Single Filter - Single Wrapper Classifier (SFSW).

Provided by: Journal of Theoretical and Applied Information Technology Topic: Big Data Date Added: Jan 2012 Format: PDF

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