Learning-data selection mechanism through neural networks ensemble

Pitoyo Hartono, Shuji Hashimoto

    研究成果: Conference contribution

    3 被引用数 (Scopus)

    抄録

    In this paper we propose a model of neural networks ensemble consisting of a number of MLPs, that deals with an imperfect learning supervisor that occasionally produces incorrect teacher signals. It is known that a conventional unitary neural network will not learn optimally from this kind of supervisor. We consider that the imperfect supervisor generates two kinds of input-output relations, the correct relation and the incorrect one. The learning characteristics of the proposed model allows the ensemble to automatically train one of its members to learn only from the correct input-output relation, producing a neural network that can to some extent tolerate the imperfection of the super- visor.

    本文言語English
    ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    出版社Springer Verlag
    ページ188-197
    ページ数10
    2096
    ISBN(印刷版)3540422846, 9783540422846
    出版ステータスPublished - 2001
    イベント2nd International Workshop on Multiple Classifier Systems, MCS 2001 - Cambridge, United Kingdom
    継続期間: 2001 7 22001 7 4

    出版物シリーズ

    名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    2096
    ISSN(印刷版)03029743
    ISSN(電子版)16113349

    Other

    Other2nd International Workshop on Multiple Classifier Systems, MCS 2001
    国/地域United Kingdom
    CityCambridge
    Period01/7/201/7/4

    ASJC Scopus subject areas

    • コンピュータ サイエンス(全般)
    • 理論的コンピュータサイエンス

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