Diagnose effective evolutionary prototype selection using an overlapping measure

Salvador García, José Ramón Cano, Ester BernadÓ-Mansilla, Francisco Herrera

    Research output: Indexed journal article Articlepeer-review

    19 Citations (Scopus)

    Abstract

    Evolutionary prototype selection has shown its effectiveness in the past in the prototype selection domain. It improves in most of the cases the results offered by classical prototype selection algorithms but its computational cost is expensive. In this paper, we analyze the behavior of the evolutionary prototype selection strategy, considering a complexity measure for classification problems based on overlapping. In addition, we have analyzed different k values for the nearest neighbour classifier in this domain of study to see its influence on the results of PS methods. The objective consists of predicting when the evolutionary prototype selection is effective for a particular problem, based on this overlapping measure.

    Original languageEnglish
    Pages (from-to)1527-1548
    Number of pages22
    JournalInternational Journal of Pattern Recognition and Artificial Intelligence
    Volume23
    Issue number8
    DOIs
    Publication statusPublished - Dec 2009

    Keywords

    • Complexity measures
    • Data complexity
    • Evolutionary prototype selection
    • Overlapping measure
    • Prototype selection

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