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 Jan 24

Keywords

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

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications

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