DOC Add tiebreaking explanation to DecisionTreeClassifier docs (#17783)

Thomas9292 · alfaro96 · NicolasHug · web-flow · commit a8067f7190ad · 2020-07-04T16:35:16.000-04:00
Co-authored-by: Juan Carlos Alfaro Jiménez &lt;JuanCarlos.Alfaro@uclm.es&gt;
Co-authored-by: Nicolas Hug &lt;contact@nicolas-hug.com&gt;
Co-authored-by: thomas.wesselink@ing.com &lt;thomas.wesselink@ing.com&gt;
diff --git a/doc/modules/tree.rst b/doc/modules/tree.rst
@@ -106,8 +106,13 @@ After being fitted, the model can then be used to predict the class of samples::
     >>> clf.predict([[2., 2.]])
     array([1])
 
-Alternatively, the probability of each class can be predicted, which is the
-fraction of training samples of the same class in a leaf::
+In case that there are multiple classes with the same and highest
+probability, the classifier will predict the class with the lowest index
+amongst those classes.
+
+As an alternative to outputting a specific class, the probability of each class
+can be predicted, which is the fraction of training samples of the class in a 
+leaf::
 
     >>> clf.predict_proba([[2., 2.]])
     array([[0., 1.]])
@@ -377,7 +382,6 @@ Tips on practical use
     most of the samples.
 
 
-
 .. _tree_algorithms:
 
 Tree algorithms: ID3, C4.5, C5.0 and CART
diff --git a/sklearn/tree/_classes.py b/sklearn/tree/_classes.py
@@ -783,6 +783,11 @@ class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree):
     reduce memory consumption, the complexity and size of the trees should be
     controlled by setting those parameter values.
 
+    The :meth:`predict` method operates using the :func:`numpy.argmax`
+    function on the outputs of :meth:`predict_proba`. This means that in
+    case the highest predicted probabilities are tied, the classifier will
+    predict the tied class with the lowest index in :term:`classes_`.
+
     References
     ----------
 
