EstimatorReport.inspection.coefficients#

EstimatorReport.inspection.coefficients()[source]#

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

Returns:
CoefficientsDisplay

The feature importance display containing model coefficients and 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, shuffle=False, as_dict=True)
>>> regressor = Ridge()
>>> report = EstimatorReport(regressor, **split_data)
>>> display = report.inspection.coefficients()
>>> display.frame()
            coefficient
feature
Intercept      151.4...
Feature #0      30.6...
Feature #1     -69.8...
Feature #2     254.8...
Feature #3     168.3...
Feature #4      18.3...
Feature #5     -19.5...
Feature #6    -134.6...
Feature #7     117.2...
Feature #8     242.1...
Feature #9     113.2...
>>> display.plot() # shows plot