Abstract
Constructive neural network (CoNN) algorithms enable the architecture of a neural network to be constructed along with the learning process. This chapter describes a new feedforward CoNN algorithm suitable for multiclass domains named MBabCoNN, which can be considered an extension of its counterpart BabCoNN, suitable for two-class classification tasks. Besides describing the main concepts involved in the MBabCoNN proposal, the chapter also presents a comparative analysis of its performance versus the multiclass versions of five well-known constructive algorithms, in eight knowledge domains, as empirical evidence of the MBabCoNN suitability and efficiency for multiclass classification tasks.
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Bertini, J.R., do Carmo Nicoletti, M. (2009). A Feedforward Constructive Neural Network Algorithm for Multiclass Tasks Based on Linear Separability. In: Franco, L., Elizondo, D.A., Jerez, J.M. (eds) Constructive Neural Networks. Studies in Computational Intelligence, vol 258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04512-7_8
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