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

Kohei Hatano

doi:10.1007/3-540-45583-3_8

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

Kohei Hatano

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Algorithmic Learning Theory - 12th International Conference, ALT 2001, Proceedings
Editors	Naoki Abe, Roni Khardon, Thomas Zeugmann
Publisher	Springer Verlag
Pages	77-92
Number of pages	16
ISBN (Print)	3540428755, 9783540428756
DOIs	https://doi.org/10.1007/3-540-45583-3_8
Publication status	Published - 2001
Externally published	Yes
Event	12th Annual Conference on Algorithmic Learning Theory, ALT 2001 - Washington, United States Duration: Nov 25 2001 → Nov 28 2001

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2225
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	12th Annual Conference on Algorithmic Learning Theory, ALT 2001
Country/Territory	United States
City	Washington
Period	11/25/01 → 11/28/01

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/3-540-45583-3_8

Cite this

Hatano, K. (2001). A simpler analysis of the multi-way branching decision tree boosting algorithm. In N. Abe, R. Khardon, & 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. https://doi.org/10.1007/3-540-45583-3_8

A simpler analysis of the multi-way branching decision tree boosting algorithm. / Hatano, Kohei.

Algorithmic Learning Theory - 12th International Conference, ALT 2001, Proceedings. ed. / Naoki Abe; Roni Khardon; Thomas Zeugmann. Springer Verlag, 2001. p. 77-92 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2225).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hatano, K 2001, A simpler analysis of the multi-way branching decision tree boosting algorithm. in N Abe, R Khardon & T Zeugmann (eds), Algorithmic Learning Theory - 12th International Conference, ALT 2001, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2225, Springer Verlag, pp. 77-92, 12th Annual Conference on Algorithmic Learning Theory, ALT 2001, Washington, United States, 11/25/01. https://doi.org/10.1007/3-540-45583-3_8

Hatano K. A simpler analysis of the multi-way branching decision tree boosting algorithm. In Abe N, Khardon R, Zeugmann T, editors, Algorithmic Learning Theory - 12th International Conference, ALT 2001, Proceedings. Springer Verlag. 2001. p. 77-92. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45583-3_8

Hatano, Kohei. / A simpler analysis of the multi-way branching decision tree boosting algorithm. Algorithmic Learning Theory - 12th International Conference, ALT 2001, Proceedings. editor / Naoki Abe ; Roni Khardon ; Thomas Zeugmann. Springer Verlag, 2001. pp. 77-92 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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

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