KEEL: A software tool to assess evolutionary algorithms for data mining problems

J. Alcalá-Fdez, Luciano Sánchez, Salva García, M. J. del Jesus, S. Ventura, Josep M. Garrell, J. Otero, C. Romero, J. Bacardit, V. M. Rivas, J. C. Fernández, F. Herrera

    Producció científica: Article en revista indexadaArticleAvaluat per experts

    1223 Cites (Scopus)

    Resum

    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.

    Idioma originalAnglès
    Pàgines (de-a)307-318
    Nombre de pàgines12
    RevistaSoft Computing
    Volum13
    Número3
    DOIs
    Estat de la publicacióPublicada - 2009

    Fingerprint

    Navegar pels temes de recerca de 'KEEL: A software tool to assess evolutionary algorithms for data mining problems'. Junts formen un fingerprint únic.

    Com citar-ho