scikit-learn · simarssidhu · Jan 21, 2025 · Jan 21, 2025 · Jan 22, 2025 · Jan 22, 2025
diff --git a/sklearn/svm/_base.py b/sklearn/svm/_base.py
@@ -183,6 +183,9 @@ def fit(self, X, y, sample_weight=None):

        If X is a dense array, then the other methods will not support sparse
        matrices as input.
+
+        For an example of handling weighed samples with :class:`svm.SVC`s, please see:
+        :ref:`sphx_glr_auto_examples_svm_plot_weighted_samples.py`
        """
        rnd = check_random_state(self.random_state)


diff --git a/sklearn/svm/_classes.py b/sklearn/svm/_classes.py
@@ -843,7 +843,7 @@ class SVC(BaseSVC):
    >>> print(clf.predict([[-0.8, -1]]))
    [1]

-    For a comparison of the SVC with other classifiers see:
+    For an example on how to enable probability estimates for SVC, see:
    :ref:`sphx_glr_auto_examples_classification_plot_classification_probability.py`.
    """