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lastFile:skore/src/skore/sklearn/_comparison/metrics_accessor.py
probabl-ai · Feb 6, 2025 · b6004d5 · b6004d5
1 parent 0a6747d
commit b6004d5
Showing 1 changed file with 39 additions and 16 deletions.
diff --git a/skore/src/skore/sklearn/_comparison/metrics_accessor.py b/skore/src/skore/sklearn/_comparison/metrics_accessor.py
@@ -93,26 +93,49 @@ def report_metrics(
         --------
         >>> from sklearn.datasets import load_breast_cancer
         >>> from sklearn.linear_model import LogisticRegression
-        >>> from skore import EstimatorReport
-        >>> from skore import ComparisonReport
-
-        >>> estimator = LogisticRegression().fit(X_train, y_train)
-
+        >>> from skore import ComparisonReport, EstimatorReport, train_test_split
+        >>>
         >>> X, y = load_breast_cancer(return_X_y=True)
         >>> X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)
-        >>> classifier1 = LogisticRegression(max_iter=10_000)
-        >>> classifier2 = LogisticRegression(max_iter=10_000)
-
-        >>> estimator_report1 = EstimatorReport(classifier1, X_test=X_test, y_test=y_test)
-        >>> estimator_report2 = EstimatorReport(classifier2, X_test=X_test, y_test=y_test)
-
-        >>> comparison_report = ComparisonReport([estimator_report1, estimator_report2])
+        >>> estimator_1 = LogisticRegression(random_state=42)
+        >>> estimator_report_1 = EstimatorReport(
+        ...     estimator_1,
+        ...     X_train=X_train,
+        ...     y_train=y_train,
+        ...     X_test=X_test,
+        ...     y_test=y_test,
+        ... )
+        >>>
+        >>> estimator_2 = LogisticRegression(random_state=42)
+        >>> estimator_report_2 = EstimatorReport(
+        ...     estimator_2,
+        ...     X_train=X_train,
+        ...     y_train=y_train,
+        ...     X_test=X_test,
+        ...     y_test=y_test,
+        ... )
+        >>>
+        >>> comparison_report = ComparisonReport(
+        ...     [estimator_report_1, estimator_report_2]
+        ... )
+        >>>
+        >>> comparison_report.metrics.report_metrics(
+        ...     scoring=["precision", "recall"],
+        ...     pos_label=1,
+        ... )
+        Metric                Precision (↗︎)  Recall (↗︎)
+          Estimator
+        0 LogisticRegression        0.96...     0.97...
+        1 LogisticRegression        0.96...     0.97...
+        >>>
         >>> comparison_report.metrics.report_metrics(
-        ...     scoring=["precision", "recall"], pos_label=1, aggregate=["mean", "std"]
+        ...     scoring=["precision", "recall"],
+        ...     pos_label=1,
+        ...     aggregate=["mean", "std"],
         ... )
-        Metric                   Precision (↗︎)  Recall (↗︎)
-        LogisticRegression mean        0.94...     0.96...
-                           std         0.02...     0.02...
+        Metric  Precision (↗︎)  Recall (↗︎)
+        mean          0.96...     0.97...
+        std           0.00...     0.00...
         """
         return self._compute_metric_scores(
             report_metric_name="report_metrics",