Add documentation on f1, recall and precision score with averaging mechanisms in api.rst. (#477)

Author: ahn1340

doc/api.rst

@@ -37,6 +37,11 @@ Built-in Metrics
 
 Classification
 ~~~~~~~~~~~~~~
+Note: The default ``autosklearn.metrics.f1``, ``autosklearn.metrics.precision`` and ``autosklearn.metrics.recall``
+built-in metrics are applicable only for binary classification. In order to apply them on multilabel and multiclass
+classification, please use the corresponding metrics with an appropriate averaging mechanism, such as ``autosklearn.metrics.f1_macro``.
+For more information about how these metrics are used, please read
+`this scikit-learn documentation <http://scikit-learn.org/stable/modules/model_evaluation.html#precision-recall-and-f-measures>`_.
 
 .. autoclass:: autosklearn.metrics.accuracy