scikit-learn · wesselhuising · Apr 18, 2023 · Apr 18, 2023 · Apr 18, 2023
diff --git a/sklearn/ensemble/_forest.py b/sklearn/ensemble/_forest.py
@@ -156,12 +156,16 @@ def _parallel_build_trees(
    verbose=0,
    class_weight=None,
    n_samples_bootstrap=None,
+    feature_names_in_=None,
 ):
    """
    Private function used to fit a single tree in parallel."""
    if verbose > 1:
        print("building tree %d of %d" % (tree_idx + 1, n_trees))

+    if feature_names_in_ is not None:
+        tree.feature_names_in_ = feature_names_in_
+
    if bootstrap:
        n_samples = X.shape[0]
        if sample_weight is None:
@@ -343,9 +347,15 @@ def fit(self, X, y, sample_weight=None):
        # Validate or convert input data
        if issparse(y):
            raise ValueError("sparse multilabel-indicator for y is not supported.")
+
        X, y = self._validate_data(
-            X, y, multi_output=True, accept_sparse="csc", dtype=DTYPE
+            X,
+            y,
+            multi_output=True,
+            accept_sparse="csc",
+            dtype=DTYPE,
        )
+
        if sample_weight is not None:
            sample_weight = _check_sample_weight(sample_weight, X)

@@ -467,6 +477,7 @@ def fit(self, X, y, sample_weight=None):
                    verbose=self.verbose,
                    class_weight=self.class_weight,
                    n_samples_bootstrap=n_samples_bootstrap,
+                    feature_names_in_=getattr(self, "feature_names_in_", None),
                )
                for i, t in enumerate(trees)
            )

diff --git a/sklearn/tree/_classes.py b/sklearn/tree/_classes.py
@@ -885,7 +885,6 @@ def fit(self, X, y, sample_weight=None, check_input=True):
        self : DecisionTreeClassifier
            Fitted estimator.
        """
-
        super().fit(
            X,
            y,