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Logistic Regression by Means of Evolutionary Radial Basis Function Neural Networks

✍ Scribed by Gutiérrez, P.A.; Hervás-Martínez, C.; Martínez-Estudillo, F.J.

Book ID
115538076
Publisher
IEEE
Year
2011
Tongue
English
Weight
512 KB
Volume
22
Category
Article
ISSN
1045-9227

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This paper proposes a radial basis function neural network (RBFNN), called the q-Gaussian RBFNN, that reproduces different radial basis functions (RBFs) by means of a real parameter q. The architecture, weights and node topology are learnt through a hybrid algorithm (HA). In order to test the overal