A simpler analysis of the multi-way branching decision tree boosting algorithm

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

1 Citation (Scopus)

Abstract

We improve the analysis of the decision tree boosting algorithm proposed by Mansour and McAllester. For binary classification problems, the algorithm of Mansour and McAllester constructs a multiway branching decision tree using a set of multi-class hypotheses. Mansour and McAllester proved that it works under certain conditions. We give a much simpler analysis of the algorithm and simplify the conditions. From this simplification, we can provide a simpler algorithm, for which no prior knowledge on the quality of weak hypotheses is necessary.

Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 12th International Conference, ALT 2001, Proceedings
EditorsRoni Khardon, Naoki Abe, Thomas Zeugmann
PublisherSpringer Verlag
Pages77-92
Number of pages16
ISBN (Print)3540428755, 9783540428756
Publication statusPublished - Jan 1 2001
Externally publishedYes
Event12th Annual Conference on Algorithmic Learning Theory, ALT 2001 - Washington, United States
Duration: Nov 25 2001Nov 28 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2225
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th Annual Conference on Algorithmic Learning Theory, ALT 2001
CountryUnited States
CityWashington
Period11/25/0111/28/01

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Hatano, K. (2001). A simpler analysis of the multi-way branching decision tree boosting algorithm. In R. Khardon, N. Abe, & T. Zeugmann (Eds.), Algorithmic Learning Theory - 12th International Conference, ALT 2001, Proceedings (pp. 77-92). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2225). Springer Verlag.