documentation updates

README.rst

@@ -287,14 +287,14 @@ In short, we recommend to use joblib or pickle for saving and loading PyOD model
 See `"examples/save_load_model_example.py" <https://github.com/yzhao062/pyod/blob/master/examples/save_load_model_example.py>`_ for an example.
 In short, it is simple as below:
 
-   .. code-block:: python
+.. code-block:: python
 
-       from joblib import dump, load
+    from joblib import dump, load
 
-       # save the model
-       dump(clf, 'clf.joblib')
-       # load the model
-       clf = load('clf.joblib')
+    # save the model
+    dump(clf, 'clf.joblib')
+    # load the model
+    clf = load('clf.joblib')
 
 
 ----

docs/example.rst

@@ -71,6 +71,7 @@ Full example: `knn_example.py <https://github.com/yzhao062/Pyod/blob/master/exam
 
     .. code-block:: python
 
+        from pyod.utils.data import evaluate_print
         # evaluate and print the results
         print("\nOn Training Data:")
         evaluate_print(clf_name, y_train, y_train_scores)

docs/model_persistence.rst

@@ -8,11 +8,11 @@ In short, we recommend to use joblib or pickle for saving and loading PyOD model
 See `"examples/save_load_model_example.py" <https://github.com/yzhao062/pyod/blob/master/examples/save_load_model_example.py>`_ for an example.
 In short, it is simple as below:
 
-   .. code-block:: python
+.. code-block:: python
 
-       from joblib import dump, load
+    from joblib import dump, load
 
-       # save the model
-       dump(clf, 'clf.joblib')
-       # load the model
-       clf = load('clf.joblib')
+    # save the model
+    dump(clf, 'clf.joblib')
+    # load the model
+    clf = load('clf.joblib')