train: Neural network training function.

Description

For a given data set (training set), this function modifies the neural network weights and biases to approximate the relationships amongst variables present in the training set. These may serve to satisfy several needs, i.e. fitting non-linear functions.

Usage

train(net,P,T,n.epochs,g=adapt.NeuralNet, error.criterium="MSE", Stao=NA, report=TRUE, show.step)

Arguments

net

Neural Network to train.

Training set input values.

Training set output values

n.epochs

Number of epochs to train.

Adaptative function used for training. The default provides a quicker C code version of the adaptative backpropagation with momentum method.

error.criterium

Criterium used to measure the goodness of fit.

Stao

Initial value of the S parameter used by the TAO algorithm.

report

Logical value indicating whether the training function should keep quiet or should provide graphical/written information during the training process instead.

show.step

If report is TRUE then a report is provided every show.step epochs.

Value

This function returns a trained Neural Network object with weights and biases adjusted by the adaptative backpropagation with momentum method. The whole training set is considered.

encoding

latin1

References

Pernia Espinoza, A.V. TAO-ROBUST BACKPROPAGATION LEARNING ALGORITHM Simon Haykin. Neural Networks. A comprehensive foundation. 2nd Edition.