Introduction to the experimental design in the data mining tool KEEL

J. Alcalá-Fdez, I. Robles, F. Herrera, S. García, M. J. del Jesus, L. Sánchez, E. Bernadó-Mansilla, A. Peregrín, S. Ventura

    Research output: Book chapterChapterpeer-review

    1 Citation (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationIntelligent Soft Computation and Evolving Data Mining
    Subtitle of host publicationIntegrating Advanced Technologies
    PublisherIGI Global
    Pages1-25
    Number of pages25
    ISBN (Print)9781615207572
    DOIs
    Publication statusPublished - 2010

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