Determination of the number of hidden units from a statistical viewpoint

T. Hayasaka, K. Hagiwara, N. Toda, S. Usui
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引用次数: 3

Abstract

One of the important problems for 3-layered neural networks (3-LNN) is to determine the optimal network structure with high generalization ability. Although this can be formulated in terms of a statistical model selection, there remains a problem in applying traditional criteria for 3-LNN. We suggest the type of effective criteria for the model selection problem of 3-LNN by analyzing the statistical properties of some simplified nonlinear models. Results of numerical experiments are also presented.
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从统计学角度确定隐藏单位的数量
确定具有高泛化能力的最优网络结构是三层神经网络的重要问题之一。虽然这可以用统计模型选择来表述,但在应用3-LNN的传统标准时仍然存在问题。通过分析一些简化非线性模型的统计性质,提出了3-LNN模型选择问题的有效准则类型。并给出了数值实验结果。
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