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From jkbrad...@apache.org
Subject spark git commit: [SPARK-21911][ML][FOLLOW-UP] Fix doc for parallel ML Tuning in PySpark
Date Tue, 14 Nov 2017 01:00:55 GMT
Repository: spark
Updated Branches:
  refs/heads/master c8b7f97b8 -> d8741b2b0


[SPARK-21911][ML][FOLLOW-UP] Fix doc for parallel ML Tuning in PySpark

## What changes were proposed in this pull request?

Fix doc issue mentioned here: https://github.com/apache/spark/pull/19122#issuecomment-340111834

## How was this patch tested?

N/A

Author: WeichenXu <weichen.xu@databricks.com>

Closes #19641 from WeichenXu123/fix_doc.


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/d8741b2b
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/d8741b2b
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/d8741b2b

Branch: refs/heads/master
Commit: d8741b2b0fe8b8da74f120859e969326fb170629
Parents: c8b7f97
Author: WeichenXu <weichen.xu@databricks.com>
Authored: Mon Nov 13 17:00:51 2017 -0800
Committer: Joseph K. Bradley <joseph@databricks.com>
Committed: Mon Nov 13 17:00:51 2017 -0800

----------------------------------------------------------------------
 docs/ml-tuning.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/spark/blob/d8741b2b/docs/ml-tuning.md
----------------------------------------------------------------------
diff --git a/docs/ml-tuning.md b/docs/ml-tuning.md
index 64dc46c..54d9cd2 100644
--- a/docs/ml-tuning.md
+++ b/docs/ml-tuning.md
@@ -55,7 +55,7 @@ for multiclass problems. The default metric used to choose the best `ParamMap`
c
 method in each of these evaluators.
 
 To help construct the parameter grid, users can use the [`ParamGridBuilder`](api/scala/index.html#org.apache.spark.ml.tuning.ParamGridBuilder)
utility.
-By default, sets of parameters from the parameter grid are evaluated in serial. Parameter
evaluation can be done in parallel by setting `parallelism` with a value of 2 or more (a value
of 1 will be serial) before running model selection with `CrossValidator` or `TrainValidationSplit`
(NOTE: this is not yet supported in Python).
+By default, sets of parameters from the parameter grid are evaluated in serial. Parameter
evaluation can be done in parallel by setting `parallelism` with a value of 2 or more (a value
of 1 will be serial) before running model selection with `CrossValidator` or `TrainValidationSplit`.
 The value of `parallelism` should be chosen carefully to maximize parallelism without exceeding
cluster resources, and larger values may not always lead to improved performance.  Generally
speaking, a value up to 10 should be sufficient for most clusters.
 
 # Cross-Validation


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