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Title: Improving learning and generalization capabilities of the C-Mantec constructive neural network algorithm
Authors: Gómez, Iván
Mesa, Héctor
Ortega Zamorano, Francisco 
Jerez-Aragonés, José M.
Franco, Leonardo
UNESCO Clasification: 1203 Ciencia de los ordenadores
Keywords: Constructive neural network
Feed-forward network
Support vector machine
Learning and generalization properties, et al
Issue Date: 2020
Journal: Neural Computing and Applications 
Abstract: C-Mantec neural network constructive algorithm Ortega (C-Mantec neural network algorithm implementation on MATLAB., 2015) creates very compact architectures with generalization capabilities similar to feed-forward networks trained by the well-known back-propagation algorithm. Nevertheless, constructive algorithms suffer much from the problem of overfitting, and thus, in this work the learning procedure is first analyzed for networks created by this algorithm with the aim of trying to understand the training dynamics that will permit optimization possibilities. Secondly, several optimization strategies are analyzed for the position of class separating hyperplanes, and the results analyzed on a set of public domain benchmark data sets. The results indicate that with these modifications a small increase in prediction accuracy of C-Mantec can be obtained but in general this was not better when compared to a standard support vector machine, except in some cases when a mixed strategy is used.
ISSN: 0941-0643
DOI: 10.1007/s00521-019-04388-2
Source: Neural Computing and Applications [ISSN 0941-0643], n. 32, p. 8955-8963
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