DOC Fix typo in random forest feature importance comparison example.
@@ -60,7 +60,7 @@ X_train, X_test, y_train, y_test = train_test_split(X, y, stratify=y, random_sta
# We define a predictive model based on a random forest. Therefore, we will make
# the following preprocessing steps:
#
-# - use :class:`~sklearn.preprocessing.OrdinaleEcnoder` to encode the
+# - use :class:`~sklearn.preprocessing.OrdinalEncoder` to encode the
# categorical features;
# - use :class:`~sklearn.impute.SimpleImputer` to fill missing values for
# numerical features using a mean strategy.
