Title: Application of a radial basis function neuralnetwork for diagnosis of diabetes mellitus
Abstract: In this article an attempt is made to study the applicability
of a general purpose, supervised feed forward
neural network with one hidden layer, namely. Radial
Basis Function (RBF) neural network. It uses relatively
smaller number of locally tuned units and is
adaptive in nature. RBFs are suitable for pattern recognition
and classification. Performance of the RBF neural
network was also compared with the most commonly used
multilayer perceptron network model and the classical
logistic regression. Diabetes database was used for
empirical comparisons and the results show that RBF
network performs better than other models.
Publication Year: 2006
Publication Date: 2006-01-01
Language: en
Type: article
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