Dividing the data into training,testing,validation
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I have a dataset of 75x6,in which i want to divide the data into training ,testing and validation and use rbf neural network to classify them,please tell how to divide and classify using rbfneural network
i used newrbe for training and testing before ,but how to include validation data in it
for reference
please help
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Accepted Answer
Greg Heath
on 7 Sep 2012
Edited: Greg Heath
on 15 Jun 2016
>> lookfor divide
...
divideblock - Partition indices into three sets using blocks of indices.
divideind - Partition indices into three sets using specified indices.
divideint - Partition indices into three sets using interleaved indices.
dividerand - Partition indices into three sets using random indices.
dividetrain - Partition indices into training set only.
dividevec - Divide problem vectors into training, validation and test vectors.
>> help divideblock, doc divideblock ...
To use a function like newrbe with divided data:
1. Use the training design data to create several (10?) nets with different spread values.
2. Use the validation training set to choose the best net.
3. Return to 1 if you want to refine your search for an optimal spread value
4. Use the nondesign test set to predict performance on unseen nondesign data.
5. If the result is unsatifactory
a. In order to reduce the bias of future test set predictions,
obtain a new division of the data (perhaps with differet percentages).
b. Return to step 1
Hope this helps
Thank you for accepting my answer.
Greg
10 Comments
Greg Heath
on 13 Sep 2012
Reread my instructions
Do not enter the command plotFcn.
Either
Enter the command net without the ending semicolon. Then look for plotFcn.
or
Enter the command
net.plotFcn
In fact, do both so that you will understand
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