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In this work our aim is to increase the performance of fuzzy rule based classifications systems in the framework of imbalanced data-sets by means of the application of a genetic tuning step. We focus on the imbalanced data-set problem since it appears in many real application areas and, for this reason, it has become a relevant topic in the area of machine learning. This problem occurs when the number...
Microarray technology allows to measure the expression levels of thousands of genes in an experiment. The use of computational methods is fundamental in cancer research. One of the possibilities is the use of artificial intelligence techniques. Several of these techniques have been used to analyze expression arrays. This paper presents a case-based reasoning (CBR) system for automatic classification...
XCS is a learning classifier system that combines a reinforcement learning scheme with evolutionary algorithms to evolve rule sets on-line by means of the interaction with an environment. Usually, research conducted on XCS has mainly focused on the analysis and improvement of the reinforcement learning component, overlooking the evolutionary discovery process to some extent. Recently, the first efforts...
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