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https://issues.apache.org/jira/browse/SPARK-15130?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15271531#comment-15271531
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Xin Ren commented on SPARK-15130:
---------------------------------
Hi I just found in class DecisionTreeClassifier of pyspark, there is a
setParams method which sort of matches what is in scala ones.
do you mean to create a separate class "Param"?
{code}
@keyword_only
@since("1.4.0")
def setParams(self, featuresCol="features", labelCol="label",
predictionCol="prediction",
probabilityCol="probability",
rawPredictionCol="rawPrediction",
maxDepth=5, maxBins=32, minInstancesPerNode=1,
minInfoGain=0.0,
maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10,
impurity="gini", seed=None):
"""
setParams(self, featuresCol="features", labelCol="label",
predictionCol="prediction", \
probabilityCol="probability",
rawPredictionCol="rawPrediction", \
maxDepth=5, maxBins=32, minInstancesPerNode=1,
minInfoGain=0.0, \
maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10,
impurity="gini", \
seed=None)
Sets params for the DecisionTreeClassifier.
"""
kwargs = self.setParams._input_kwargs
return self._set(**kwargs)
{code}
> PySpark decision tree params should include default values to match Scala
> -------------------------------------------------------------------------
>
> Key: SPARK-15130
> URL: https://issues.apache.org/jira/browse/SPARK-15130
> Project: Spark
> Issue Type: Improvement
> Components: Documentation, ML, PySpark
> Reporter: holdenk
> Priority: Minor
>
> As part of checking the documentation in SPARK-14813, PySpark decision tree
> params do not include the default values (unlike the Scala ones). While the
> existing Scala default values will have been used, this information is likely
> worth exposing in the docs.
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