Incorporating feature ranking and evolutionary methods for the classification of high-dimensional DNA microarray gene expression data

摘要

BackgroundDNA microarray gene expression classification poses a challenging task to the machine learning domain. Typically, the dimensionality of gene expression data sets could go from several thousands to over 10,000 genes. A potential solution to this issue is using feature selection to reduce the dimensionality.