Hello guys!
I am working with some classifiers ( SVM,C4.5,RNA,etc) using 10-C.V.
Once I have the model of each one, I make the validation of these models in
one dataset. Then,with my model and the dataset, I extract a confusion
matrix to know the capacity of prediction from the model. And finally, I
extract the accuracy of this prediction based on the diagonal from the
confusion matrix.
The fact is that I need to do that process for each partition of 10-CV. I
need to do 10 times the previous process to obtain the accuracy of each
partition from CV to know how response each partition in the prediction of
the dataset.
Do you know any method in R to do it?
Thanks a lot, of course!
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