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Neural Networks > over fittingを防ぐ式 > (n + 2)M + 1 < m @ 2005年

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Approximation of complex nonlinear functions by means of neural networks
Thomas Most
presented at the 2nd Weimar Optimization and Stochastic Days 2005

論文ではmutli-layer perceptron (also called feed-forward back-propagation network)を使い、Katsuki and Frangopol(1994) による関数の近似例がある。

over fittingを防ぐ式としてEquation 2が紹介されている (Hagen et al., 1996).

(n + 2)M + 1 < m 

m: the number of training samples
n: the number of input values
M: the number of hidden neurons for a network with single hidden layer

Hagan, M. T. ; Demuth, H. B. ; Beale, M.: Neural Network Design. PWS Publishing Company, 1996


セブンオブナインです。Unimatrix 01の第三付属物 9の7という識別番号です。Star trek Voyagerの好きなキャラクターです。まとめ記事は後日タイトルから内容がわからなくなるため、title検索で見つかるよう個々の記事にしてます。いわゆるBorg集合体の有名なセリフから「お前たち(の知識)を吸収する。抵抗は無意味だ」。Thanks in advance.
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