I have trained a NN with Back Propagation algorithm and calculated the MSE. Now I want to find the percentage of correctly classified results (i am facing a classification problem). Any help?
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I have trained a NN with Back Propagation algorithm and calculated the MSE. Now I want to find the percentage of correctly classified results (i am facing a classification problem). Any help?
It depends on your dataset whether you generate the data or whether you are given a dataset with samples.
In the first case you feed your NN with a generated sample and check whether NN predicts the correct class. You repeat it let say 100 times. And for each correctly classified sample you increment the counter CorrectlyClassified by one. Then the percentage of correctly classified results is equal to CorrectlyClassified. For higher accuracy you may not generate 100 samples, but X samples (where X is bigger than 100). Then the percentage of correctly classified results is:
CorrectlyClassified/X*100.If you are given a dataset you should use cross-validation. See MATLAB documentation for an example.