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From yli...@apache.org
Subject spark git commit: [SPARK-18177][ML][PYSPARK] Add missing 'subsamplingRate' of pyspark GBTClassifier
Date Thu, 03 Nov 2016 14:46:13 GMT
Repository: spark
Updated Branches:
  refs/heads/branch-2.1 71104c9c9 -> 99891e56e


[SPARK-18177][ML][PYSPARK] Add missing 'subsamplingRate' of pyspark GBTClassifier

## What changes were proposed in this pull request?
Add missing 'subsamplingRate' of pyspark GBTClassifier

## How was this patch tested?
existing tests

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #15692 from zhengruifeng/gbt_subsamplingRate.

(cherry picked from commit 9dc9f9a5dde37d085808a264cfb9cf4d4f72417d)
Signed-off-by: Yanbo Liang <ybliang8@gmail.com>


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/99891e56
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/99891e56
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/99891e56

Branch: refs/heads/branch-2.1
Commit: 99891e56ea286580323fd82e303064d3c0730d85
Parents: 71104c9
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Authored: Thu Nov 3 07:45:20 2016 -0700
Committer: Yanbo Liang <ybliang8@gmail.com>
Committed: Thu Nov 3 07:45:56 2016 -0700

----------------------------------------------------------------------
 python/pyspark/ml/classification.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/spark/blob/99891e56/python/pyspark/ml/classification.py
----------------------------------------------------------------------
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index d9ff356..56c8c62 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -900,19 +900,19 @@ class GBTClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol
     def __init__(self, featuresCol="features", labelCol="label", predictionCol="prediction",
                  maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0,
                  maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, lossType="logistic",
-                 maxIter=20, stepSize=0.1, seed=None):
+                 maxIter=20, stepSize=0.1, seed=None, subsamplingRate=1.0):
         """
         __init__(self, featuresCol="features", labelCol="label", predictionCol="prediction",
\
                  maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, \
                  maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, \
-                 lossType="logistic", maxIter=20, stepSize=0.1, seed=None)
+                 lossType="logistic", maxIter=20, stepSize=0.1, seed=None, subsamplingRate=1.0)
         """
         super(GBTClassifier, self).__init__()
         self._java_obj = self._new_java_obj(
             "org.apache.spark.ml.classification.GBTClassifier", self.uid)
         self._setDefault(maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0,
                          maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10,
-                         lossType="logistic", maxIter=20, stepSize=0.1)
+                         lossType="logistic", maxIter=20, stepSize=0.1, subsamplingRate=1.0)
         kwargs = self.__init__._input_kwargs
         self.setParams(**kwargs)
 
@@ -921,12 +921,12 @@ class GBTClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol
     def setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction",
                   maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0,
                   maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10,
-                  lossType="logistic", maxIter=20, stepSize=0.1, seed=None):
+                  lossType="logistic", maxIter=20, stepSize=0.1, seed=None, subsamplingRate=1.0):
         """
         setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction",
\
                   maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, \
                   maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, \
-                  lossType="logistic", maxIter=20, stepSize=0.1, seed=None)
+                  lossType="logistic", maxIter=20, stepSize=0.1, seed=None, subsamplingRate=1.0)
         Sets params for Gradient Boosted Tree Classification.
         """
         kwargs = self.setParams._input_kwargs


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