Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4677#discussion_r25138910
--- Diff: docs/mllib-ensembles.md ---
@@ -427,6 +427,18 @@ We omit some decision tree parameters since those are
covered in the [decision t
* **`algo`**: The algorithm or task (classification vs. regression) is set
using the tree [Strategy] parameter.
+#### Validation while training
+
+Gradient boosting can overfit when trained with more number of trees. In
order to prevent overfitting, it might
+be useful to validate while training. The method **`runWithValidation`**
has been provided to make use of this
+option. It takes a pair of RDD's as arguments, the first one being the
training dataset and the second being the validation dataset.
+
+The training is stopped when the improvement in the validation error is
not more than a certain tolerance
+(supplied by the **`validationTol`** argument in **`BoostingStrategy`**).
In practice, the validation error
+decreases with the increase in number of trees and then increases as the
model starts to overfit. There might
--- End diff --
"decreases with the increase in number of trees and then increases" -->
"decreases initially and later increases"
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