# ✅ 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

*Select a single answer*

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

*Select a single answer*

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.

*Select a single answer*

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

*Select a single answer*