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Introduction to the Experimental Design in the Data Mining Tool KEEL

KEEL is a Data Mining software tool to assess the behaviour of evolutionary learning algorithms in particular and soft computing algorithms in general for different kinds of Data Mining problems including as regression, classification, clustering, pattern mining and so on. It allows us to perform a complete analysis of some learning model in comparison to existing ones, including a statistical test module for comparison. In this chapter the authors will provide a complete description of KEEL, the kind of problems and algorithms implemented, and they will present a case of study for showing the experimental design and statistical analysis that they can do with KEEL. J. Alcalá-Fdez University of Granada, Spain I. Robles University of Granada, Spain F. Herrera University of Granada, Spain S. García University of Jaén, Spain M.J. del Jesus University of Jaén, Spain L. Sánchez University of Oviedo, Spain E. Bernadó-Mansilla University Ramon Llull, Spain A. Peregrín University of Huelva, Spain S. Ventura University of Córdoba, Spain DOI: 10.4018/978-1-61520-757-2.ch001