This paper introduces a software tool named
KEEL which is a software tool to assess evolutionary algorithms for Data Mining problems of various kinds including as regression,
classification, unsupervised learning, etc. It includes evolutionary learning algorithms based on different approaches: Pittsburgh,
Michigan and IRL, as well as the integration of evolutionary learning techniques with different pre-processing techniques,
allowing it to perform a complete analysis of any learning model in comparison to existing software tools. Moreover, KEEL
has been designed with a double goal: research and educational.
Keywords Computer-based education - Data mining - Evolutionary computation - Experimental design - Graphical programming - Java - Knowledge extraction - Machine learning
Supported by the Spanish Ministry of Science and Technology under Projects TIN-2005-08386-C05-(01, 02, 03, 04 and 05). The
work of Dr. Bacardit is also supported by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant GR/T07534/01.