[SPARK-6025] [MLlib] Add helper method evaluateEachIteration to extract learning curve

Added evaluateEachIteration to allow the user to manually extract the error for each iteration of GradientBoosting. The internal optimisation can be dealt with later.

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #4906 from MechCoder/spark-6025 and squashes the following commits:

67146ab [MechCoder] Minor
352001f [MechCoder] Minor
6e8aa10 [MechCoder] Made the following changes Used mapPartition instead of map Refactored computeError and unpersisted broadcast variables
bc99ac6 [MechCoder] Refactor the method and stuff
dbda033 [MechCoder] [SPARK-6025] Add helper method evaluateEachIteration to extract learning curve

1 files changed, 2 insertions, 2 deletions

diff --git a/docs/mllib-ensembles.md b/docs/mllib-ensembles.md
index cbfb682609..7521fb14a7 100644
--- a/docs/mllib-ensembles.md
+++ b/docs/mllib-ensembles.md
@@ -464,8 +464,8 @@ 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 initially and later increases. There might be cases in which the validation error does not change monotonically,
-and the user is advised to set a large enough negative tolerance and examine the validation curve to to tune the number of
-iterations.
+and the user is advised to set a large enough negative tolerance and examine the validation curve using `evaluateEachIteration`
+(which gives the error or loss per iteration) to tune the number of iterations.
 
 ### Examples