Github user manishamde commented on a diff in the pull request:
https://github.com/apache/spark/pull/2063#discussion_r16504941
--- Diff: docs/mllib-decision-tree.md ---
@@ -7,20 +7,26 @@ displayTitle: <a href="mllib-guide.html">MLlib</a> -
Decision Tree
* Table of contents
{:toc}
-Decision trees and their ensembles are popular methods for the machine
learning tasks of
+[Decision trees](http://en.wikipedia.org/wiki/Decision_tree_learning)
+and their ensembles are popular methods for the machine learning tasks of
classification and regression. Decision trees are widely used since they
are easy to interpret,
-handle categorical variables, extend to the multiclass classification
setting, do not require
+handle categorical features, extend to the multiclass classification
setting, do not require
feature scaling and are able to capture nonlinearities and feature
interactions. Tree ensemble
-algorithms such as decision forest and boosting are among the top
performers for classification and
+algorithms such as decision forests and boosting are among the top
performers for classification and
--- End diff --
should we just call them random forests instead? :-)
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