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A Survey on Hybrid Feature Selection Methods in Microarray Gene Expression Data For Cancer Classification
2019
IEEE Access
The emergence of DNA Microarray technology has enabled researchers to analyze the expression level of thousands of genes simultaneously. The Microarray data analysis is the process of finding the most informative genes as well as remove redundant and irrelevant genes. One of the most important applications of the Microarray data analysis is cancer classification. However, the curse of dimensionality and the curse of sparsity make classifying gene expression profiles a challenging task. One of
doi:10.1109/access.2019.2922987
fatcat:hnfhi5lrnbaozplhjidlkta6su