Multiclass classification and gene selection with a stochastic algorithm

Abstract

Microarray technology allows for the monitoring of thousands of gene expressions in various biological conditions, but most of these genes are irrelevant for classifying these conditions. Feature selection is consequently needed to help reduce the dimension of the variable space. Starting from the application of the stochastic meta-algorithm "Optimal Feature Weighting" (OFW) for selecting features in various classification problems, focus is made on the multiclass problem that wrapper methods rarely handle. From a computational point of view, one of the main difficulties comes from the unbalanced classes situation that is commonly encountered in microarray data. From a theoretical point of v..