Package jhpro.nnet

Class Summary

Class	Description
BackpropagationNet	Backpropagation is a supervised learning algorithm and is mainly used by Multi-Layer-Perceptrons to change the weights connected to the net's hidden neuron layer(s).
Example
InputMatrix	Input matrix.
InputValue
KohonenFeatureMap	KohonenFeatureMap.
MapNeuron
Neuron	This class builds a single neuron.
NeuronLayer
NeuronMatrix
Pattern	The pattern file of a Backpropagation Net contains the input and target patterns for the net.
ThreeD
WeightMatrix	The connection structure between two neuron layers of a neural net.