@inproceedings{oai:kanazawa-u.repo.nii.ac.jp:00007643,
 author = {Keeni, Kanad and Nakayama, Kenji and Shimodaira, Hiroshi},
 book = {Proceedings of the International Joint Conference on Neural Networks},
 month = {Jul},
 note = {A method has been proposed for weight initialization in back-propagation feed-forward networks. Training data is analyzed and the notion of critical point is introduced for determining the initial weights and the number of hidden units. The proposed method has been applied to artificial data and the publicly available cancer database. The experimental results of artificial data show that the proposed method takes 1/3 of the training time required for standard back-propagation. In order to verify the effectiveness of the proposed method, standard back-propagation, where the learning starts with random initial weights was also applied to the cancer database. The experimental results indicate that the proposed weight initialization method results in better generalization.},
 pages = {1652--1656},
 publisher = {IEEE(Institute of Electrical and Electronics Engineers)},
 title = {Estimation of initial weights and hidden units for fast learning of multi-layer neural networks for pattern classification},
 volume = {3},
 year = {1999}
}