| Neural Network Toolbox | |
Purpose
Plot network performance for Bayesian regularization training.
Syntax
Description
plotbr(tr,name,epoch) takes these inputs,
TR - Training record returned by train.
name - Training function name, default = ''.
epoch - Number of epochs, default = length of training record.
and plots the training sum squared error, the sum squared weight, and the effective number of parameters.
Examples
Here are input values P and associated targets T.
p = [-1:.05:1]; t = sin(2*pi*p)+0.1*randn(size(p));
The code below creates a network and trains it on this problem.
net=newff([-1 1],[20,1],{'tansig','purelin'},'trainbr');
[net,tr] = train(net,p,t);
During training plotbr was called to display the training record. You can also call plotbr directly with the final training record TR, as shown below.
plotbr(tr)
| | normr | plotep | |