Beyond homemade artificial data sets

Núria MacIà, Albert Orriols-Puig, Ester Bernadó-Mansilla

    Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

    7 Cites (Scopus)


    One of the most important challenges in supervised learning is how to evaluate the quality of the models evolved by different machine learning techniques. Up to now, we have relied on measures obtained by running the methods on a wide test bed composed of real-world problems. Nevertheless, the unknown inherent characteristics of these problems and the bias of learners may lead to inconclusive results. This paper discusses the need to work under a controlled scenario and bets on artificial data set generation. A list of ingredients and some ideas about how to guide such generation are provided, and promising results of an evolutionary multi-objective approach which incorporates the use of data complexity estimates are presented.

    Idioma originalAnglès
    Títol de la publicacióHybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings
    Nombre de pàgines8
    Estat de la publicacióPublicada - 2009
    Esdeveniment4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009 - Salamanca, Spain
    Durada: 10 de juny 200912 de juny 2009

    Sèrie de publicacions

    NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volum5572 LNAI
    ISSN (imprès)0302-9743
    ISSN (electrònic)1611-3349


    Conferència4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009


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