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Overfitting occurs when the learner makes predictions based on regularities that appear in the training examples but do not appear in the test examples or in the world from which the data is taken. It typically happens when the model tries to find signal in randomness or when the learner becomes overconfident in its model.
— Jul 07, 2019 07:29PM
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