You have built a regression model to predict future crops of tomato based on a range of growing conditions. The model seems to fit well to the training data, but when any new data is tested it performs very poorly. How would you typically describe a model where this occurs? This is described as a well performing model. The model can't be expected to Press 1 get it right all the time. This is described as prediction error. The model happens to have got it wrong Press 2 for all of the test data. This is described as underfitting. The model hasn't picked out enough information to perform well yet. Press 3 This is described as overfitting. The model has picked out details in the data that don't generalize. Press 4

Q: Suppose that I want to purchase a tablet computer . I can choose either a large,medium or small…

A:

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A:

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A: