Growing network that optimizes between undertraining and overtraining

Goutam Chakraborty*, Mitsuru Murakami, Norio Shiratori, Shoichi Noguchi

*この研究の対応する著者

    研究成果: Conference contribution

    3 被引用数 (Scopus)

    抄録

    Feedforward neural network classifier trained with a finite set of available sample tries to estimate properly the different class boundaries in the input feature space. This enables the network to classify unknown new samples with some confidence. A new method for ascertaining proper network size for maximizing generalization as well as correct classification is proposed. An algorithm is also proposed to grow the network to that size.

    本文言語English
    ホスト出版物のタイトルIEEE International Conference on Neural Networks - Conference Proceedings
    Place of PublicationPiscataway, NJ, United States
    出版社IEEE
    ページ1116-1120
    ページ数5
    2
    出版ステータスPublished - 1995
    イベントProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust
    継続期間: 1995 11 271995 12 1

    Other

    OtherProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)
    CityPerth, Aust
    Period95/11/2795/12/1

    ASJC Scopus subject areas

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