CrossValidationReport.metrics.timings

CrossValidationReport.metrics.timings(aggregate=('mean', 'std'))

Get all measured processing times related to the estimator.

The index of the returned dataframe is the name of the processing time. When the estimators were not used to predict, no timings regarding the prediction will be present.

Parameters:

aggregate{“mean”, “std”} or list of such str, default=None

Function to aggregate the timings across the cross-validation splits.

Returns:

pd.DataFrame

A dataframe with the processing times.

Examples

>>> from sklearn.datasets import make_classification
>>> from sklearn.linear_model import LogisticRegression
>>> X, y = make_classification(random_state=42)
>>> estimator = LogisticRegression()
>>> from skore import CrossValidationReport
>>> report = CrossValidationReport(estimator, X=X, y=y, splitter=2)
>>> report.metrics.timings()
                  mean       std
Fit time (s)       ...       ...
>>> report.cache_predictions(response_methods=["predict"])
>>> report.metrics.timings()
                            mean       std
Fit time (s)                 ...       ...
Predict time test (s)        ...       ...
Predict time train (s)       ...       ...