From 287bd072671ae2af6a81e454478fc0c91a13c4ad Mon Sep 17 00:00:00 2001
From: Jin Woo Ahn <ahnj@informatik.uni-freiburg.de>
Date: Mon, 14 May 2018 18:54:23 +0200
Subject: [PATCH] Add documentation on f1, recall and precision score with
 averaging mechanisms in api.rst.

---
 doc/api.rst | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/doc/api.rst b/doc/api.rst
index 34107e78a7..03e446b112 100644
--- a/doc/api.rst
+++ b/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