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 evaluate
>>> X, y = load_diabetes(return_X_y=True)
>>> regressor = Ridge()
>>> report = evaluate(regressor, X, y, splitter=0.2)
>>> display = report.inspection.coefficients()
>>> display.frame()
       feature  coefficient
0    Intercept      151.9...
1   Feature #0       21.3...
2   Feature #1      -72.9...
3   Feature #2      301.3...
4   Feature #3      177.4...
5   Feature #4        2.8...
6   Feature #5      -35.2...
7   Feature #6     -155.5...
8   Feature #7      118.3...
9   Feature #8      257.3...
10  Feature #9      102.2...
>>> display.plot() # shows plot