id: 06095315
dt: a
an: 06095315
au: Olmo, Juan Luis; Romero, José Raúl; Ventura, Sebastián
ti: Multi-objective ant programming for mining classification rules.
so: Moraglio, Alberto (ed.) et al., Genetic programming. 15th European
    conference, EuroGP 2012, Málaga, Spain, April 11‒13, 2012.
    Proceedings. Berlin: Springer (ISBN 978-3-642-29138-8/pbk). Lecture
    Notes in Computer Science 7244, 146-157 (2012).
py: 2012
pu: Berlin: Springer
la: EN
cc: 
ut: data mining; classification; ant programming; genetic programming;
    multi-objective optimization
ci: 
li: doi:10.1007/978-3-642-29139-5_13
ab: Summary: Ant programming (AP) is a kind of automatic programming that
    generates computer programs by using the ant colony optimization
    metaheuristic. It has recently demonstrated a good generalization
    ability when extracting classification rules. We extend the
    investigation on the application of AP to classification, developing an
    algorithm that addresses rules’ evaluation using a novel
    multi-objective approach specially devised for the classification task.
    The algorithm proposed also incorporates an evolutionary computing
    niching procedure to increment the diversity of the population of
    programs found so far. Results obtained by this algorithm are compared
    with other three genetic programming algorithms and other industry
    standard algorithms from different areas, proving that multi-objective
    AP is a good technique at tackling classification problems.
rv: