DOC: trivial rst fix (scikit-learn#13765)

GaelVaroquaux · jnothman · commit 0da8f75bf6ee · 2019-05-06T23:13:30.000+10:00
diff --git a/examples/impute/plot_iterative_imputer_variants_comparison.py b/examples/impute/plot_iterative_imputer_variants_comparison.py
@@ -8,13 +8,13 @@
 variable as an output in turn.
 
 In this example we compare some estimators for the purpose of missing feature
-imputation with :class:`sklearn.imputeIterativeImputer`::
+imputation with :class:`sklearn.imputeIterativeImputer`:
 
-    :class:`~sklearn.linear_model.BayesianRidge`: regularized linear regression
-    :class:`~sklearn.tree.DecisionTreeRegressor`: non-linear regression
-    :class:`~sklearn.ensemble.ExtraTreesRegressor`: similar to missForest in R
-    :class:`~sklearn.neighbors.KNeighborsRegressor`: comparable to other KNN
-    imputation approaches
+* :class:`~sklearn.linear_model.BayesianRidge`: regularized linear regression
+* :class:`~sklearn.tree.DecisionTreeRegressor`: non-linear regression
+* :class:`~sklearn.ensemble.ExtraTreesRegressor`: similar to missForest in R
+* :class:`~sklearn.neighbors.KNeighborsRegressor`: comparable to other KNN
+  imputation approaches
 
 Of particular interest is the ability of
 :class:`sklearn.impute.IterativeImputer` to mimic the behavior of missForest, a
