•Overfitting is a general phenomenon that plagues all machine learning methods.
•That is one reason why you must never evaluate on the training data set.
•Overfitting can also occur more generally.
•Therefore choose the best method for the data domain.
•Performance is not expected to be as good on new test data.
•Try dividing data into train, test and validation.
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