64 search results - page 8 / 13 » Training Multi-layer Perceptrons Using MiniMin Approach |
IBPRIA
2005
Springer
14 years 1 months ago
2005
Springer
A natural way to deal with training samples in imbalanced class problems is to prune them removing redundant patterns, easy to classify and probably over represented, and label noi...
CCE
2008
13 years 7 months ago
2008
An efficient algorithm to train general differential recurrent neural networks is proposed. The trained network can be directly used as the internal model of a predictive controll...
NPL
2006
13 years 7 months ago
2006
Effective backpropagation training of multi-layer perceptrons depends on the incorporation of an appropriate error or objective function. Classification-based (CB) error functions ...
ESANN
2008
13 years 9 months ago
2008
Standard learning procedures are better fitted to estimation than to classification problems, and focusing the training on appropriate samples provides performance advantages in cl...
ANNPR
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. Recently, the authors described a training method for a convolutional neural network of threshold neurons. Hidden layers are trained by by clustering, in a feed-forward m...