Relation between VGA-classifier and MLP: determination of network architecture

Bandyopadhyay, Sanghamitra ; Pal, Sankar K. (1999) Relation between VGA-classifier and MLP: determination of network architecture Fundamenta Informaticae, 37 (1-2). pp. 177-199. ISSN 0169-2968

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An analogy between a genetic algorithm based pattern classification scheme (where hyperplanes are used to approximate the class boundaries through searching) and multilayer perceptron (MLP) based classifier is established. Based on this, a method for determining the MLP architecture automatically is described. It is shown that the architecture would need atmost two hidden layers, the neurons of which are responsible for generating hyperplanes and regions. The neurons in the second hidden and output layers perform the AND & OR functions respectively. The methodology also includes a post processing step which automatically removes any redundant neuron in the hidden/output layer. An extensive comparative study of the performance of the MLP, thus derived using the proposed method, with those of several other conventional MLPs is presented for different data sets.

Item Type:Article
Source:Copyright of this article belongs to IOS Press.
Keywords:Hyperplane Fitting; Boundary Approximation; Hard Limiting Neuron; Network Architecture Design; Variable String Length Genetic Algorithm
ID Code:77678
Deposited On:14 Jan 2012 06:03
Last Modified:14 Jan 2012 06:03

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