Package javax.datamining.algorithm.feedforwardneuralnet

This package contains definitions for describing the algorithm settings specific to building a fully connected, n-layer, feed-forward neural network model.

See:
Description

Interface Summary

Backpropagation	A Backpropagation object specifies the parameters used by the backpropagation learning algorithm.
BackpropagationFactory	A factory class that creates instances of Backpropagation.
FeedForwardNeuralNetSettings	A FeedForwardNeuralNetSettings object captures the parameters associated with a neural network algorithm.
FeedForwardNeuralNetSettingsFactory	A factory class that creates instances of FeedForwardNeuralNetSettings.
LearningAlgorithm	The interface LearningAlgorithm is a generic specification of the learning algorithm to be employed in training a neural network.
NeuralLayer	A NeuralLayer object captures the parameters required to describe a layer in a neural network model.
NeuralLayerFactory	A factory class that creates instances of NeuralLayer.

Class Summary

ActivationFunction	The enumeration AcivationFunction indicates the type of activation function used by the neural layer.
FeedForwardNeuralNetCapability	The enumeration FeedForwardNeuralNetCapability enumerates a list of the capabilities of the feed forward neural network algorithm being supported in a particular implementation.

Package javax.datamining.algorithm.feedforwardneuralnet Description

This package contains definitions for describing the algorithm settings specific to building a fully connected, n-layer, feed-forward neural network model. Feed-forward neural networks allow only unidirectional forward connections among the neurons.