Analysis of the performance of ensemble of perceptrons

Pitoyo Hartono, Shuji Hashimoto

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this study we analyze the performance of an ensemble model composed of several Perceptrons that can effectively deal with nonlinear classification problems. Although each member of the ensemble can only deal with linear classification problems, through a competitive training mechanism, the ensemble is able to automatically allocate a part of the learning space that is linearly separable to each member, thus decomposing non-linear classification problems into several more manageable linear problems. In this paper, we gave the performance analysis of the ensemble with regard to some benchmark problems.

    Original languageEnglish
    Title of host publicationIEEE International Conference on Neural Networks - Conference Proceedings
    Pages5171-5176
    Number of pages6
    Publication statusPublished - 2006
    EventInternational Joint Conference on Neural Networks 2006, IJCNN '06 - Vancouver, BC
    Duration: 2006 Jul 162006 Jul 21

    Other

    OtherInternational Joint Conference on Neural Networks 2006, IJCNN '06
    CityVancouver, BC
    Period06/7/1606/7/21

    ASJC Scopus subject areas

    • Software

    Fingerprint Dive into the research topics of 'Analysis of the performance of ensemble of perceptrons'. Together they form a unique fingerprint.

  • Cite this

    Hartono, P., & Hashimoto, S. (2006). Analysis of the performance of ensemble of perceptrons. In IEEE International Conference on Neural Networks - Conference Proceedings (pp. 5171-5176). [1716819]