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Before you watch the video or read the documentation, please complete this exercise that explores overuse of feature crosses.

Task 1: Run the model as is, with all of the given cross-product features. Are there any surprises in the way the model fits the data? What is the issue?

Task 2: Try removing various cross-product features to improve performance (albeit only slightly). Why would removing features improve performance?

(Answers appear just below the exercise.)