Analysis of the performance of ensemble of perceptrons

Pitoyo Hartono; Shuji Hashimoto

Analysis of the performance of ensemble of perceptrons

Pitoyo Hartono^*, Shuji Hashimoto

^*Corresponding author for this work

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

Abstract

In this study we analyze the performance of an ensemble model composed of several Perceptrons that can effectively deal with nonlinear classification problems. Although each member of the ensemble can only deal with linear classification problems, through a competitive training mechanism, the ensemble is able to automatically allocate a part of the learning space that is linearly separable to each member, thus decomposing non-linear classification problems into several more manageable linear problems. In this paper, we gave the performance analysis of the ensemble with regard to some benchmark problems.

Original language	English
Title of host publication	IEEE International Conference on Neural Networks - Conference Proceedings
Pages	5171-5176
Number of pages	6
Publication status	Published - 2006
Event	International Joint Conference on Neural Networks 2006, IJCNN '06 - Vancouver, BC Duration: 2006 Jul 16 → 2006 Jul 21

Other

Other	International Joint Conference on Neural Networks 2006, IJCNN '06
City	Vancouver, BC
Period	06/7/16 → 06/7/21

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title = "Analysis of the performance of ensemble of perceptrons",

abstract = "In this study we analyze the performance of an ensemble model composed of several Perceptrons that can effectively deal with nonlinear classification problems. Although each member of the ensemble can only deal with linear classification problems, through a competitive training mechanism, the ensemble is able to automatically allocate a part of the learning space that is linearly separable to each member, thus decomposing non-linear classification problems into several more manageable linear problems. In this paper, we gave the performance analysis of the ensemble with regard to some benchmark problems.",

author = "Pitoyo Hartono and Shuji Hashimoto",

year = "2006",

language = "English",

isbn = "0780394909",

pages = "5171--5176",

booktitle = "IEEE International Conference on Neural Networks - Conference Proceedings",

note = "International Joint Conference on Neural Networks 2006, IJCNN '06 ; Conference date: 16-07-2006 Through 21-07-2006",

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AU - Hartono, Pitoyo

AU - Hashimoto, Shuji

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AB - In this study we analyze the performance of an ensemble model composed of several Perceptrons that can effectively deal with nonlinear classification problems. Although each member of the ensemble can only deal with linear classification problems, through a competitive training mechanism, the ensemble is able to automatically allocate a part of the learning space that is linearly separable to each member, thus decomposing non-linear classification problems into several more manageable linear problems. In this paper, we gave the performance analysis of the ensemble with regard to some benchmark problems.

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M3 - Conference contribution

AN - SCOPUS:40649096597

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SN - 9780780394902

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BT - IEEE International Conference on Neural Networks - Conference Proceedings

T2 - International Joint Conference on Neural Networks 2006, IJCNN '06

Y2 - 16 July 2006 through 21 July 2006

ER -

Analysis of the performance of ensemble of perceptrons

Abstract

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