fix docstrings

Author: MarieSacksick

skore/src/skore/_sklearn/_estimator/feature_importance_accessor.py

@@ -155,7 +155,7 @@ def _check_metric(metric: Any) -> Scoring | None:
             # Convert to scorer
             return {metric: metric_to_scorer[cast(Metric, metric)]}
         raise TypeError(
-            "If scoring is a string, it must be one of "
+            "If metric is a string, it must be one of "
             f"{list(metric_to_scorer.keys())}; got '{metric}'"
         )
     elif isinstance(metric, list | tuple):

skore/src/skore/_sklearn/_estimator/metrics_accessor.py

@@ -1263,7 +1263,7 @@ def log_loss(
         >>> split_data = train_test_split(X=X, y=y, random_state=0, as_dict=True)
         >>> classifier = LogisticRegression(max_iter=10_000)
         >>> report = EstimatorReport(classifier, **split_data)
-        >>> report.sklearn_metrics.log_loss()
+        >>> report.metrics.log_loss()
         0.10...
         """
         return self._log_loss(