Update example to use predefined_split properly (#1340)

examples/40_advanced/example_resampling.py

@@ -98,8 +98,9 @@
 # data by the first feature. In practice, one would use a splitting according
 # to the use case at hand.
 
+selected_indices = (X_train[:, 0] < np.mean(X_train[:, 0])).astype(int)
 resampling_strategy = sklearn.model_selection.PredefinedSplit(
-    test_fold=np.where(X_train[:, 0] < np.mean(X_train[:, 0]))[0]
+    test_fold=selected_indices
 )
 
 automl = autosklearn.classification.AutoSklearnClassifier(
@@ -111,6 +112,8 @@
 )
 automl.fit(X_train, y_train, dataset_name='breast_cancer')
 
+print(automl.sprint_statistics())
+
 ############################################################################
 # For custom resampling strategies (i.e. resampling strategies that are not
 # defined as strings by Auto-sklearn) it is necessary to perform a refit: