CrossValidationReport.inspection.coefficients#
- CrossValidationReport.inspection.coefficients()[source]#
Retrieve the coefficients across splits, including the intercept.
- Returns:
CoefficientsDisplayThe 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=5 >>> ) >>> display = report.inspection.coefficients() >>> display.frame() split feature coefficients 0 0 Intercept 0.0... 1 0 Feature #0 74.1... 2 0 Feature #1 27.3... 3 0 Feature #2 17.3... 4 1 Intercept 0.0... 5 1 Feature #0 74.2... 6 1 Feature #1 27.5... 7 1 Feature #2 17.3... 8 2 Intercept 0.0... 9 2 Feature #0 74.1... 10 2 Feature #1 27.6... 11 2 Feature #2 17.2... 12 3 Intercept 0.1... 13 3 Feature #0 74.2... 14 3 Feature #1 27.5... 15 3 Feature #2 17.3... 16 4 Intercept 0.0... 17 4 Feature #0 74.2... 18 4 Feature #1 27.5... 19 4 Feature #2 17.3... >>> display.plot() # shows plot