how can i train my network for test and validation data?

x is the my input, y is the desired output then I split x as validation and test data y as well. How should be my algorithm? I want to see how weights are changing for each epoch.

x=[5,1,1,1,2,1,3,1,1;5,4,4,5,7,10,3,2,1;3,1,1,1,2,2,3,1,1;6,8,8,1,3,4,3,7,1;4,1,1,3,2,1,3,1,1;8,10,10,8,7,10,9,7,1;1,1,1,1,2,10,3,1,1;2,1,2,1,2,1,3,1,1;2,1,1,1,2,1,1,1,5;4,2,1,1,2,1,2,1,1;1,1,1,1,1,1,3,1,1;2,1,1,1,2,1,2,1,1;5,3,3,3,2,3,4,4,1;1,1,1,1,2,3,3,1,1;8,7,5,10,7,9,5,5,4;7,4,6,4,6,1,4,3,1;4,1,1,1,2,1,2,1,1;4,1,1,1,2,1,3,1,1;10,7,7,6,4,10,4,1,2;6,1,1,1,2,1,3,1,1;7,3,2,10,5,10,5,4,4;10,5,5,3,6,7,7,10,1;3,1,1,1,2,1,2,1,1;5,10,10,8,5,5,7,10,1;1,1,1,1,2,1,3,1,1;5,2,3,4,2,7,3,6,1;3,2,1,1,1,1,2,1,1;5,1,1,1,2,1,2,1,1;2,1,1,1,2,1,2,1,1;1,1,3,1,2,1,1,1,1];

y=[2;2;2;2;2;4;2;2;2;2;2;2;4;4;4;2;2;4;2;4;4;2;4;2;4;2;2;2;2]

x_test=x(1:20,:)

x_validation=x(21:end,:)

y_test=y(1:20,:)

y_validation=y(21:end,:)

Answer 1

[Greg Heath]

Where is your training data?

The MATLAB default is a random choice of trn/val/tst = 0.7/0.15/0.15

I choose candidate values of H to avoid overfitting and, 10-to-20 random initial sets of weights.

There are zillions of my examples in BOTH COMP.SOFT-SYS.MATLAB & ANSWERS

Hope this helps.

Thank you for formally accepting my answer

Greg

[Ahsen Feyza Dogan]

Actually I am new at this field so I confused that I am on the right way. I am trying to do split my data set x into test and validation then using single and multilayer perceptron get output as 2 or 4 depends on my input. Could you briefly explain what am I suppose to do?

Thanks

Answer 2

[Greg Heath]

The MATLAB default AUTOMATICALLY splits the data into TRAINING + VALIDATION+TEST SUBSETS in the ratios

0.7/0.15/0.15.

For regression and curvefitting see the documentation and examples using the commands

help fitnet

and

doc fitnet

For classification and pattern recognition use

help patternnet

and

doc patternnet

For examples just add "greg" to the commands.

Hope this helps

Greg