Nonlinear Regression with Neural Networks
نویسنده
چکیده
This document presents a series of examples of the use of multi-layer, non-linear neural networks. An overview of the mathematical derivation of the backpropagation algorithm is presented along with detailed samples of it programming in the R language. Several examples of different input and output dimensionality are presented to address issues of network complexity, training errors and over-fitting, hidden representation, model selection, and weight decay.
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