BATCHgdwm.MLPnet: Batch gradient descent with momentum training

In AMORE: Artificial Neural Network Training and Simulating

Description

Modifies the neural network weights and biases according to the training set.

Usage

BATCHgdwm.MLPnet(net,P,T, n.epochs, n.threads=0L)

Arguments

net	Neural Network to train.
P	Input data set.
T	Target output data set.
n.epochs	Number of epochs to train
n.threads	Number of threads to spawn. If <1, spawns NumberProcessors-1 threads. If no OpenMP is found, this argument will be ignored.

Value

This functions returns a neural network object modified according to the chosen data.

Author(s)

Manuel Castejón Limas. [e-mail]
Joaquin Ordieres Meré. [e-mail]
Ana González Marcos. [e-mail]
Alpha V. Pernía Espinoza. [e-mail]
Francisco Javier Martinez de Pisón. [e-mail]
Fernando Alba Elías. [e-mail]

References

Simon Haykin. Neural Networks – a Comprehensive Foundation. Prentice Hall, New Jersey, 2nd edition, 1999. ISBN 0-13-273350-1.

See Also

newff,train,BATCHgd.MLPnet

AMORE documentation built on Feb. 12, 2020, 9:07 a.m.