Package com.imsl.datamining.neural

Interface Summary

Activation	Interface implemented by perceptron activation functions.
QuasiNewtonTrainer.Error	Error function to be minimized by trainer.
Trainer	Interface implemented by classes used to train a network.

Class Summary

BinaryClassification	Classifies patterns into two classes.
EpochTrainer	Two-stage training using randomly selected training patterns in stage I.
FeedForwardNetwork	A representation of a feed forward neural network.
HiddenLayer	Hidden layer in a neural network.
InputLayer	Input layer in a neural network.
InputNode	A Node in the InputLayer.
Layer	The base class for Layers in a neural network.
LeastSquaresTrainer	Trains a FeedForwardNetwork using a Levenberg-Marquardt algorithm for minimizing a sum of squares error.
Link	A link in a neural network.
MultiClassification	Classifies patterns into three or more classes.
Network	Neural network base class.
Node	A Node in a neural network.
OutputLayer	Output layer in a neural network.
OutputPerceptron	A Perceptron in the output layer.
Perceptron	A Perceptron node in a neural network.
QuasiNewtonTrainer	Trains a network using the quasi-Newton method, MinUnconMultiVar.
ScaleFilter	Scales or unscales continuous data prior to its use in neural network training, testing, or forecasting.
TimeSeriesClassFilter	Converts time series data contained within nominal categories to a lagged format for processing by a neural network.
TimeSeriesFilter	Converts time series data to a lagged format used as input to a neural network.
UnsupervisedNominalFilter	Converts nominal data into a series of binary encoded columns for input to a neural network.
UnsupervisedOrdinalFilter	Encodes ordinal data into percentages for input to a neural network.