## Constructive Feedforward Neural Networks for Regression Problems: A Survey (1995)

Citations: | 21 - 0 self |

### BibTeX

@MISC{Kwok95constructivefeedforward,

author = {Tin-yau Kwok and Dit-Yan Yeung},

title = {Constructive Feedforward Neural Networks for Regression Problems: A Survey},

year = {1995}

}

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### OpenURL

### Abstract

In this paper, we review the procedures for constructing feedforward neural networks in regression problems. While standard back-propagation performs gradient descent only in the weight space of a network with fixed topology, constructive procedures start with a small network and then grow additional hidden units and weights until a satisfactory solution is found. The constructive procedures are categorized according to the resultant network architecture and the learning algorithm for the network weights. The Hong Kong University of Science & Technology Technical Report Series Department of Computer Science 1 Introduction In recent years, many neural network models have been proposed for pattern classification, function approximation and regression problems. Among them, the class of multi-layer feedforward networks is perhaps the most popular. Standard back-propagation performs gradient descent only in the weight space of a network with fixed topology; this approach is analogous to ...