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 |
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| 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 |
Keywords
- Competitive learning
- Confidence level
- Linear perceptron
- Neural network ensemble
- Problem subspace
ASJC Scopus subject areas
- Engineering(all)