Learning with ensemble of linear perceptrons

Pitoyo Hartono; Shuji Hashimoto

Learning with ensemble of linear perceptrons

Pitoyo Hartono^*, Shuji Hashimoto

^*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

In this paper we introduce a model of ensemble of linear perceptrons. The objective of the ensemble is to automatically divide the feature space into several regions and assign one ensemble member into each region and training the member to develop an expertise within the region. Utilizing the proposed ensemble model, the learning difficulty of each member can be reduced, thus achieving faster learning while guaranteeing the overall performance.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	115-120
Number of pages	6
Volume	3697 LNCS
Publication status	Published - 2005
Event	15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005 - Warsaw Duration: 2005 Sept 11 → 2005 Sept 15

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3697 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005
City	Warsaw
Period	05/9/11 → 05/9/15

ASJC Scopus subject areas

Computer Science(all)
Biochemistry, Genetics and Molecular Biology(all)
Theoretical Computer Science

Cite this

Hartono, P., & Hashimoto, S. (2005). Learning with ensemble of linear perceptrons. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3697 LNCS, pp. 115-120). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3697 LNCS).

Learning with ensemble of linear perceptrons. / Hartono, Pitoyo; Hashimoto, Shuji.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3697 LNCS 2005. p. 115-120 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3697 LNCS).

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

Hartono, P & Hashimoto, S 2005, Learning with ensemble of linear perceptrons. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3697 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3697 LNCS, pp. 115-120, 15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005, Warsaw, 05/9/11.

Hartono P, Hashimoto S. Learning with ensemble of linear perceptrons. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3697 LNCS. 2005. p. 115-120. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Hartono, Pitoyo ; Hashimoto, Shuji. / Learning with ensemble of linear perceptrons. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3697 LNCS 2005. pp. 115-120 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Learning with ensemble of linear perceptrons

Abstract

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ASJC Scopus subject areas

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