National Tsing Hua University Institutional Repository:Active training of backpropagation neural networks using the learning by experimentation methodology
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    题名: Active training of backpropagation neural networks using the learning by experimentation methodology
    作者: Lin FR;Shaw MJ
    教師: 林福仁
    日期: 1997
    出版者: Springer Verlag
    關聯: ANNALS OF OPERATIONS RESEARCH, Springer Verlag, Volume 75, Number 0, Pages 105-122,1997
    关键词: neural networks
    Learning by Experimentation Methodology
    active learning
    摘要: This paper proposes the Learning by Experimentation Methodology (LEM) to facilitate the active training of neural networks. In an active learning paradigm, a learning mechanism can actively interact with its environment to acquire new knowledge and revise itself. The learning by experimentation is an active learning strategy. Experiments are conducted to form hypotheses, and the evaluation of those hypotheses feeds back to the learning mechanism to revise knowledge. We use a backpropagation neural network as the learning mechanism. We also adopt a weight space analysis method and a heuristic to select salient attributes to perform new experiments in order to revise the network. Finally we illustrate performance by solving the sonar signal classification problem.
    URI: http:/dx.doi.org/10.1023/A:1018999110972
    http://www.springerlink.com/
    http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/84795
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