Abstract
In this study we introduce an ensemble of neural networks, in which each member is a linear perceptron. Our main objective is to build an ensemble of neural networks that can automatically and effectively divide the problem space and assign a subspace to each member. By assigning only a portion of the problem space, we expect that the learning difficulty for each member can be reduced, thus leading to better classification ability. To investigate the effectiveness of the proposed method in dividing the problem space, in this paper we deal with ensemble consists only of linear perceptrons, each with an additional output neuron that indicates the confidence level of the output.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - HIS'04: 4th International Conference on Hybrid Intelligent Systems |
| Editors | M. Ishikawa, S. Hashimoto, M. Paprzycki, E. Barakova, K. Yoshida, M. Koppen, D.M. Corne, A. Abraham |
| Pages | 186-191 |
| Number of pages | 6 |
| Publication status | Published - 2005 |
| Event | Proceedings - HIS'04: 4th International Conference on Hybrid Intelligent Systems - Kitakyushu Duration: 2004 Dec 5 → 2004 Dec 8 |
Other
| Other | Proceedings - HIS'04: 4th International Conference on Hybrid Intelligent Systems |
|---|---|
| City | Kitakyushu |
| Period | 04/12/5 → 04/12/8 |
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Keywords
- Competitive learning
- Confidence level
- Linear perceptron
- Neural network ensemble
- Problem subspace
ASJC Scopus subject areas
- Engineering(all)
Cite this
Ensemble of linear perceptrons with confidence level output. / Hartono, Pitoyo; Hashimoto, Shuji.
Proceedings - HIS'04: 4th International Conference on Hybrid Intelligent Systems. ed. / M. Ishikawa; S. Hashimoto; M. Paprzycki; E. Barakova; K. Yoshida; M. Koppen; D.M. Corne; A. Abraham. 2005. p. 186-191.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Ensemble of linear perceptrons with confidence level output
AU - Hartono, Pitoyo
AU - Hashimoto, Shuji
PY - 2005
Y1 - 2005
N2 - In this study we introduce an ensemble of neural networks, in which each member is a linear perceptron. Our main objective is to build an ensemble of neural networks that can automatically and effectively divide the problem space and assign a subspace to each member. By assigning only a portion of the problem space, we expect that the learning difficulty for each member can be reduced, thus leading to better classification ability. To investigate the effectiveness of the proposed method in dividing the problem space, in this paper we deal with ensemble consists only of linear perceptrons, each with an additional output neuron that indicates the confidence level of the output.
AB - In this study we introduce an ensemble of neural networks, in which each member is a linear perceptron. Our main objective is to build an ensemble of neural networks that can automatically and effectively divide the problem space and assign a subspace to each member. By assigning only a portion of the problem space, we expect that the learning difficulty for each member can be reduced, thus leading to better classification ability. To investigate the effectiveness of the proposed method in dividing the problem space, in this paper we deal with ensemble consists only of linear perceptrons, each with an additional output neuron that indicates the confidence level of the output.
KW - Competitive learning
KW - Confidence level
KW - Linear perceptron
KW - Neural network ensemble
KW - Problem subspace
UR - http://www.scopus.com/inward/record.url?scp=28344433000&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=28344433000&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:28344433000
SN - 0769522912
SP - 186
EP - 191
BT - Proceedings - HIS'04: 4th International Conference on Hybrid Intelligent Systems
A2 - Ishikawa, M.
A2 - Hashimoto, S.
A2 - Paprzycki, M.
A2 - Barakova, E.
A2 - Yoshida, K.
A2 - Koppen, M.
A2 - Corne, D.M.
A2 - Abraham, A.
ER -