get

EstimatorReport.metrics.get(name, data_source='test', **kwargs)

Get a metric value.

Parameters:

namestr

Name of the metric to compute. Get all available metrics with available(). Metrics added with a neg_ prefix can also be retrieved without it; the alias is resolved automatically.

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 metric value, or None if the metric is not available.

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.get("precision")
{0: 0.90..., 1: 0.98...}