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From sro...@apache.org
Subject spark git commit: [SPARK-15823][PYSPARK][ML] Add @property for 'accuracy' in MulticlassMetrics
Date Fri, 10 Jun 2016 09:09:23 GMT
Repository: spark
Updated Branches:
  refs/heads/master 675a73715 -> 16ca32eac


[SPARK-15823][PYSPARK][ML] Add @property for 'accuracy' in MulticlassMetrics

## What changes were proposed in this pull request?
`accuracy` should be decorated with `property` to keep step with other methods in `pyspark.MulticlassMetrics`,
like `weightedPrecision`, `weightedRecall`, etc

## How was this patch tested?
manual tests

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #13560 from zhengruifeng/add_accuracy_property.


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/16ca32ea
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/16ca32ea
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/16ca32ea

Branch: refs/heads/master
Commit: 16ca32eace39c423224b0ec25922038fd45c501a
Parents: 675a737
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Authored: Fri Jun 10 10:09:19 2016 +0100
Committer: Sean Owen <sowen@cloudera.com>
Committed: Fri Jun 10 10:09:19 2016 +0100

----------------------------------------------------------------------
 python/pyspark/mllib/evaluation.py | 7 ++-----
 1 file changed, 2 insertions(+), 5 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/spark/blob/16ca32ea/python/pyspark/mllib/evaluation.py
----------------------------------------------------------------------
diff --git a/python/pyspark/mllib/evaluation.py b/python/pyspark/mllib/evaluation.py
index 2eaac87..fc2a0b3 100644
--- a/python/pyspark/mllib/evaluation.py
+++ b/python/pyspark/mllib/evaluation.py
@@ -179,11 +179,7 @@ class MulticlassMetrics(JavaModelWrapper):
     1.0...
     >>> metrics.fMeasure(0.0, 2.0)
     0.52...
-    >>> metrics.precision()
-    0.66...
-    >>> metrics.recall()
-    0.66...
-    >>> metrics.accuracy()
+    >>> metrics.accuracy
     0.66...
     >>> metrics.weightedFalsePositiveRate
     0.19...
@@ -273,6 +269,7 @@ class MulticlassMetrics(JavaModelWrapper):
             else:
                 return self.call("fMeasure", label, beta)
 
+    @property
     @since('2.0.0')
     def accuracy(self):
         """


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