CrossValidationReport.inspection.coefficients#

CrossValidationReport.inspection.coefficients()[source]#

Retrieve the coefficients across splits, including the intercept.

Returns:
CoefficientsDisplay

The feature importance display containing model coefficients and intercept.

Examples

>>> from sklearn.datasets import make_regression
>>> from sklearn.linear_model import Ridge
>>> from skore import CrossValidationReport
>>> X, y = make_regression(n_features=3, random_state=42)
>>> report = CrossValidationReport(estimator=Ridge(), X=X, y=y, splitter=2)
>>> display = report.inspection.coefficients()
>>> display.frame()
    split     feature   coefficient
0       0   Intercept       -0.1...
1       0  Feature #0       73.2...
2       0  Feature #1       26.6...
3       0  Feature #2       17.1...
4       1   Intercept        0.2...
5       1  Feature #0       73.8...
6       1  Feature #1       27.4...
7       1  Feature #2       17.1...
>>> display.plot() # shows plot