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[SOLVED] discretize by entropy evaluation
I would like to use discretize by entropy operator with naive bayes classifier. As far as I understand discretize by entropy depends on class value and I it would not be correct to first discretize all dataset and then perform cross validation. I would like to set up experiment where in every test fold of cross-validation I discretize data by entropy and in test fold the classifier is evaluated on on test set discretize by bin intervals from train set fold. Is this possible. I am not sure If I was clear, simply I wish to classified new data using classifier build on discretized data, how I should apply the same discretization intervals on new data?
Any help, comment would be very appreciated.