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

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## 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.
This commit is contained in:
Zheng RuiFeng 2016-11-03 07:45:20 -07:00 committed by Yanbo Liang
parent 0ea5d5b24c
commit 9dc9f9a5dd
1 changed files with 5 additions and 5 deletions
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10
python/pyspark/ml/classification.py
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@ -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