Neural Network Toolbox™

Plot network performance for Bayesian regularization training

Syntax

• plotbr(TR,name,epoch)
  

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 is called to display the training record. You can also call plotbr directly with the final training record TR, as shown below.

• plotbr(TR)
  

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