CrossValidationReport.cache_predictions

CrossValidationReport.cache_predictions(response_methods='auto', n_jobs=None)

Cache the predictions for sub-estimators reports.

Parameters:

response_methods{“auto”, “predict”, “predict_proba”, “decision_function”}, default=”auto

The methods to use to compute the predictions.

n_jobsint, default=None

The number of jobs to run in parallel. If None, we use the n_jobs parameter when initializing CrossValidationReport.

Examples

>>> from sklearn.datasets import load_breast_cancer
>>> from sklearn.linear_model import LogisticRegression
>>> from skore import CrossValidationReport
>>> X, y = load_breast_cancer(return_X_y=True)
>>> classifier = LogisticRegression(max_iter=10_000)
>>> report = CrossValidationReport(classifier, X=X, y=y, cv_splitter=2)
>>> report.cache_predictions()
>>> report._cache
{...}