抄録
In training supervised-type neural networks, the quality of the training data is one of the most important factors in deciding the quality of the neural networks. Unfortunately, in real world problems, error-free training data are not always easy to obtain. For complex data, it is always possible that erroneous training samples are included, causing to decrease the performance of the neural networks. In this research, we propose a model of neural network ensemble that, through a competition mechanism, has an ability to automatically train one of its members to learn only from the correct training patterns, thus minimizing the effect of the imperfect data.
本文言語 | English |
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ホスト出版物のタイトル | ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age |
出版社 | Institute of Electrical and Electronics Engineers Inc. |
ページ | 2561-2565 |
ページ数 | 5 |
巻 | 5 |
ISBN(電子版) | 9810475241, 9789810475246 |
DOI | |
出版ステータス | Published - 2002 |
イベント | 9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore 継続期間: 2002 11月 18 → 2002 11月 22 |
Other
Other | 9th International Conference on Neural Information Processing, ICONIP 2002 |
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国/地域 | Singapore |
City | Singapore |
Period | 02/11/18 → 02/11/22 |
ASJC Scopus subject areas
- コンピュータ ネットワークおよび通信
- 情報システム
- 信号処理