A method for estimating the number of hidden neurons in feed-forward neural networks based on information entropy

Author:

Yuan H.C.,Xiong F.L.,Huai X.Y.

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference6 articles.

1. First- and second-order methods for learning: between steepest descent and Newton's method;Battiti;Neural Comput.,1992

2. Introduction to the Theory of Neural Computation;Hertz,1991

3. A method to directly estimate the number of the hidden neurons in the feedforward neural networks;Li;J. Comput.,1999

4. Lin, G., 1991. Using multi-variable analysis method to evaluate the quality of Chinese tea and Japanese tea. Doctoral thesis of MingCheng University (in Japanese).

5. A neural network construction algorithm which maximizes the likelihood function;Setiono;Connect. Sci.,1995

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