FS-XCS vs. GRD-XCS: An analysis using high-dimensional DNA microarray gene expression data sets

Abstract

XCS, a Genetic Based Machine Learning model that combines reinforcement learning with evolutionary algorithms to evolve a population of classifiers in the form of condition-action rules, has been used successfully for many classification tasks. However, like many other machine learning algorithms, XCS becomes less effective when it is applied to high-dimensional data sets. In this paper, we present an analysis of two XCS extensions - FS-XCS and GRD-XCS - in an attempt to overcome the dimensionality issue. FS-XCS is a standard combination of a feature selection method and XCS. As for GRD-XCS, we use feature quality information to bias the evolutionary operators without removing any features f..