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A Simple Strategy to prune Neural Networks with an Application to Economic Time Series

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Author Info
Johan F. Kaashoek
Herman K. van Dijk () (Erasmus University Rotterdam)

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Abstract

A major problem in applying neural networks is specifying the size of the network. Even for moderately sized networks the number of parameters may become large compared to the number of data. In this paper network performance is examined while reducing the size of the network through the use of multiple correlation coefficients and graphical analysis of network output per hidden layer cell and input layer cell.

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Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 97-123/4.

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Date of creation: 03 Dec 1997
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Handle: RePEc:dgr:uvatin:19970123

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  1. Schotman, Peter C & van Dijk, Herman K, 1991. "On Bayesian Routes to Unit Roots," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 387-401, Oct.-Dec.. [Downloadable!] (restricted)
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  1. J.F. Kaashoek & H.K. Van Dijk, 2001. "Neural networks as econometric tool," Econometric Institute Report 213, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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  2. J.F. Kaashoek & H.K. van Dijk, 1999. "Neural networks analysis of varying trends in real exchange rates," Econometric Institute Report 143, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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