score#
- EstimatorReport.metrics.score(*, data_source='test')[source]#
Compute the estimator’s default score.
This calls the underlying estimator’s
scoremethod on the chosen data source. Forskrub.DataOpestimators, scorings registered viawith_scoring()are used.- Parameters:
- data_source{“test”, “train”}, default=”test”
The data source to use.
“test” : use the test set provided when creating the report.
“train” : use the train set provided when creating the report.
- Returns:
- The default score of the estimator.
Examples
>>> from sklearn.datasets import load_breast_cancer >>> from sklearn.linear_model import LogisticRegression >>> from skore import evaluate >>> X, y = load_breast_cancer(return_X_y=True) >>> classifier = LogisticRegression(max_iter=10_000) >>> report = evaluate(classifier, X, y, splitter=0.2) >>> report.metrics.score() 0.94...