How to disable validation and test data set in neural network

I need to train patternnet neural network using all data set in the training set and avoiding validation check. I found two methods and they works very well in command line but not in a script returning very simple errors.

method 1:

   mynet.divideFcn = '';

method 2:

   mynet.divideParam.trainRatio = 1;
   mynet.divideParam.valRatio   = 0;
   mynet.divideParam.testRatio  = 0;

and the code:

   mynet=patternnet([]);

   P=rand(10,1000);
   T=rand(2,1000);

 [mynet,tr]=train(mynet,P,T);

Matlab R2012 b windows xp 32

Thanks !

Answer 1

[Greg Heath]

You have to define net before modifying any properties.

clear all, close all, clc

[x,t] = iris_dataset;

for i = 1:2

net = patternnet([]);

if i==1

net.divideFcn = '';

else

net.divideParam.trainRatio = 1;

net.divideParam.valRatio = 0;

net.divideParam.testRatio = 0;

end

net = train(net,x,t);

view(net)

y = net(x);

MSE(i) = mse(y-t)

end

MSE = 0.0084 0.0084

Hope this helps.

Greg

Answer 2

[Prasanth Sundaravelu]

Hi, I think you need to type specific Divide function, instead of blank.

Try this : mynet.divideFcn = 'dividerand';

[NILESH TANPANIYA]

Hi,

dividerand is the inbuilt function i think