DOC added example to permutation importance (scikit-learn#16460)

Author: magda-zielinska

sklearn/inspection/_permutation_importance.py

@@ -100,6 +100,21 @@ def permutation_importance(estimator, X, y, scoring=None, n_repeats=5,
     ----------
     .. [BRE] L. Breiman, "Random Forests", Machine Learning, 45(1), 5-32,
              2001. https://doi.org/10.1023/A:1010933404324
+
+    Examples
+    --------
+    >>> from sklearn.linear_model import LogisticRegression
+    >>> from sklearn.inspection import permutation_importance
+    >>> X = [[1, 9, 9],[1, 9, 9],[1, 9, 9],
+    ...      [0, 9, 9],[0, 9, 9],[0, 9, 9]]
+    >>> y = [1, 1, 1, 0, 0, 0]
+    >>> clf = LogisticRegression().fit(X, y)
+    >>> result = permutation_importance(clf, X, y, n_repeats=10,
+    ...                                 random_state=0)
+    >>> result.importances_mean
+    array([0.4666..., 0.       , 0.       ])
+    >>> result.importances_std
+    array([0.2211..., 0.       , 0.       ])
     """
     if not hasattr(X, "iloc"):
         X = check_array(X, force_all_finite='allow-nan', dtype=None)