Evaluation of a machine learning tool in the domain of genetic host responses

Abstract

This report examines the use of Support Vector Machines and Genetic Programming Classifiers (GPCs) to distinguish between classes of cancer based on gene expression data. The effect of feature selection on classifier accuracy and on the convergence time of GPCs is experimentally investigated, with the goal of making classification problems on gene expression data tractable to GPCs.