In many neural network applications, the selection of best training set to represent the entire sample space is one of the most important problems. Active learning algorithms in the literature for neural networks are not appropriate for Probabilistic Neural Networks (PNN). In this paper, a new active learning method is proposed for PNN. The method was applied to several benchmark problems. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Bolat, B., & Yildirim, T. (2005). Active learning for Probabilistic Neural Networks. In Lecture Notes in Computer Science (Vol. 3610, pp. 110–118). Springer Verlag. https://doi.org/10.1007/11539087_13
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