書誌事項
- タイトル別名
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- An ANN Learning Algorithm Based on Hierarchical Clustering of Training Data
- カイソウテキ モンダイ ブンカツ ニヨル ニューラル ネットワーク ガクシュウ
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抄録
We propose a new ANN learning algorithm based on hierarchical clustering of training data. The proposed algorithm first constructs a tree of sub-learning problems by hiearchically clustering given learning patterns in a bottom-up manner and decides a corresponding network structure. The proposed algorithm trains the whole network giving teacher signals of the original learning problem to the output units, and trains sub-networks giving teacher signals of the divided sub-learning problems to the hidden units simultaneously. The hidden units which learn sub-learning problems become feature detectors, which promote the learning of the original learning problem. We demonstrate the advantages of our learning algorithm by solving N-bits parity problems, a non-liner function approximation, iris classification problem, and two-spirals problem. Experimen-tal results show that our learning algorithm obtains better solutions than the standard back-propagation algorithms and one of constructive algorithms in terms of the learning speed and the convergence rate.
収録刊行物
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- 電気学会論文誌Ｃ（電子・情報・システム部門誌）
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電気学会論文誌Ｃ（電子・情報・システム部門誌） 118 (3), 326-332, 1998
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390001204607422592
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- NII論文ID
- 130006843388
- 10004161457
- 10002813236
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- NII書誌ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL書誌ID
- 4423997
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- データソース種別
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- JaLC
- NDL
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- 使用不可