✅ Quiz M7.05#

Question

What is the default score in scikit-learn when using a regressor?

  • a) \(R^2\)

  • b) mean absolute error

  • c) median absolute error

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Question

If we observe that the values returned by cross_val_scores(model, X, y, scoring="r2") increase after changing the model parameters, it means that the latest model:

  • a) generalizes better

  • b) generalizes worse

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Question

If all the values returned by cross_val_score(model_A, X, y, scoring="neg_mean_squared_error") are strictly lower than those returned by cross_val_score(model_B, X, y, scoring="neg_mean_squared_error") it means that model_B generalizes:

  • a) better than model_A

  • b) worse than model_A

Hint: Remember that "neg_mean_squared_error" is an alias for the negative of the Mean Squared Error.

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Question

Values returned by cross_val_scores(model, X, y, scoring="neg_mean_squared_error") are:

  • a) guaranteed to be positive or zero

  • b) guaranteed to be negative or zero

  • c) can be either positive or negative depending on the data

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