Dear Rooters,
I’m trying to understand how the output of “TMultiLayerPerceptron::Evaluate” should be interpreted.
The documentation says “Returns the Neural Net for a given set of input parameters #parameters must equal #input neurons.” I understand the latter. However, “return the Neural Net” sounds vague to me.
I assumed the output should be the output of the last neuron. By default, sigmoid functions are used. As a result, I expect the output to be between 0 and 1. This doesn’t seem to happen to me (the output ranges between -1 & 1).
So…1) I have made a mistake or 2) my understanding of “TMultiLayerPerceptron::Evaluate” is incorrect.
Cheers,
Johan
PS. I see that there are possibilities to use other functions besides sigmoids (tanh, linear, etc.). I tried to use them but it shows me “Error in TMultiLayerPerceptron::TMultiLayerPerceptron::Train(): Line search fail”