Tutorial series on brain-inspired computing part 6: Geometrical structure of boosting algorithm

Takafumi Kanamori, Takashi Takenouchi, Noboru Murata

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    In this article, several boosting methods are discussed, which are notable implementations of the ensemble learning. Starting from the firstly introduced "boosting by filter" which is an embodiment of the proverb "Two heads are better than one", more advanced versions of boosting methods "AdaBoost" and "U-Boost" are introduced. A geometrical structure and some statistical properties such as consistency and robustness of boosting algorithms are discussed, and then simulation studies are presented for confirming discussed behaviors of algorithms.

    Original languageEnglish
    Pages (from-to)117-141
    Number of pages25
    JournalNew Generation Computing
    Volume25
    Issue number1
    DOIs
    Publication statusPublished - 2007

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    Keywords

    • Boosting
    • Classification problem
    • Large-scale learning machine
    • Statistical learning theory

    ASJC Scopus subject areas

    • Hardware and Architecture
    • Theoretical Computer Science
    • Computational Theory and Mathematics

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