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ICANN
2010
Springer
14 years 11 months ago
Computational Properties of Probabilistic Neural Networks
We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
Jiri Grim, Jan Hora
IJCSS
2007
122views more  IJCSS 2007»
14 years 11 months ago
Artificial Neural Network Type Learning with Single Multiplicative Spiking Neuron
In this paper, learning algorithm for a single multiplicative spiking neuron (MSN) is proposed and tested for various applications where a multilayer perceptron (MLP) neural netwo...
Deepak Mishra, Abhishek Yadav, Sudipta Ray, Prem K...
CORR
2010
Springer
150views Education» more  CORR 2010»
14 years 11 months ago
Extraction of Symbolic Rules from Artificial Neural Networks
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...
S. M. Kamruzzaman, Md. Monirul Islam
APIN
2005
127views more  APIN 2005»
14 years 11 months ago
Evolutionary Radial Basis Functions for Credit Assessment
Credit analysts generally assess the risk of credit applications based on their previous experience. They frequently employ quantitative methods to this end. Among the methods used...
Estefane G. M. de Lacerda, André Carlos Pon...
IJON
2008
88views more  IJON 2008»
14 years 11 months ago
Neural network construction and training using grammatical evolution
The term neural network evolution usually refers to network topology evolution leaving the network's parameters to be trained using conventional algorithms. In this paper we ...
Ioannis G. Tsoulos, Dimitris Gavrilis, Euripidis G...