EstimatorReport.feature_importance.coefficients#

EstimatorReport.feature_importance.coefficients()[source]#

Retrieve the coefficients of a linear model, including the intercept.

Examples

>>> from sklearn.datasets import load_diabetes
>>> from sklearn.linear_model import Ridge
>>> from skore import train_test_split
>>> from skore import EstimatorReport
>>> X, y = load_diabetes(return_X_y=True)
>>> split_data = train_test_split(X=X, y=y, random_state=0, as_dict=True)
>>> regressor = Ridge()
>>> report = EstimatorReport(regressor, **split_data)
>>> report.feature_importance.coefficients()
           Coefficient
Intercept     152.4...
Feature #0     21.2...
Feature #1    -60.4...
Feature #2    302.8...
Feature #3    179.4...
Feature #4      8.9...
Feature #5    -28.8...
Feature #6   -149.3...
Feature #7    112.6...
Feature #8    250.5...
Feature #9     99.5...