Neural Network Classification: cost function, regularization parameter, availability of the hidden layers...
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Richard Palmer
le 27 Mai 2015
Commenté : Richard Palmer
le 28 Mai 2015
How do I derive the cost function J from a nn classification model?
How can I set a regularization parameter? Is this approached using your weights capability?
Are the hidden layer values available after modeling?
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Greg Heath
le 28 Mai 2015
You cannot derive a cost function from a model.
You specify the cost function for a design.
If you are new at this, start out by accepting the NNToolbox defaults. First check out the relatively simple examples in the classification documentation
help patternnet
doc patternnet
Then search the NEWSGROUP and ANSWERS for posted examples. For example
greg patternnet
The default transfer functions are tansig (hidden layer) and softmax (output layer)
The "cost" function is crossentropy
Many questions on terminology and details can be obtained using the commands help, doc and type, e.g.,
help patternnet
doc patternnet
type patternnet
Hope this helps.
Thank you for formally accepting my answer
Greg
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