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| author | Yanbo Liang <ybliang8@gmail.com> | 2016-01-06 10:52:25 -0800 |
|---|---|---|
| committer | Joseph K. Bradley <joseph@databricks.com> | 2016-01-06 10:52:25 -0800 |
| commit | 3aa3488225af12a77da3ba807906bc6a461ef11c (patch) | |
| tree | a817cf07b4cbb89b681d80819a75038610d566a4 /python/pyspark/ml/regression.py | |
| parent | 95eb65163391b9e910277a948b72efccf6136e0c (diff) | |
| download | spark-3aa3488225af12a77da3ba807906bc6a461ef11c.tar.gz spark-3aa3488225af12a77da3ba807906bc6a461ef11c.tar.bz2 spark-3aa3488225af12a77da3ba807906bc6a461ef11c.zip | |
[SPARK-11815][ML][PYSPARK] PySpark DecisionTreeClassifier & DecisionTreeRegressor should support setSeed
PySpark ```DecisionTreeClassifier``` & ```DecisionTreeRegressor``` should support ```setSeed``` like what we do at Scala side.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #9807 from yanboliang/spark-11815.
Diffstat (limited to 'python/pyspark/ml/regression.py')
| -rw-r--r-- | python/pyspark/ml/regression.py | 14 |
1 files changed, 9 insertions, 5 deletions
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py index a0bb8ceed8..401bac0223 100644 --- a/python/pyspark/ml/regression.py +++ b/python/pyspark/ml/regression.py @@ -386,7 +386,8 @@ class GBTParams(TreeEnsembleParams): @inherit_doc class DecisionTreeRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, - DecisionTreeParams, TreeRegressorParams, HasCheckpointInterval): + DecisionTreeParams, TreeRegressorParams, HasCheckpointInterval, + HasSeed): """ `http://en.wikipedia.org/wiki/Decision_tree_learning Decision tree` learning algorithm for regression. @@ -415,11 +416,13 @@ class DecisionTreeRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredi @keyword_only def __init__(self, featuresCol="features", labelCol="label", predictionCol="prediction", maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, - maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity="variance"): + maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity="variance", + seed=None): """ __init__(self, featuresCol="features", labelCol="label", predictionCol="prediction", \ maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, \ - maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity="variance") + maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, \ + impurity="variance", seed=None) """ super(DecisionTreeRegressor, self).__init__() self._java_obj = self._new_java_obj( @@ -435,11 +438,12 @@ class DecisionTreeRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredi def setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction", maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, - impurity="variance"): + impurity="variance", seed=None): """ setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction", \ maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, \ - maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity="variance") + maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, \ + impurity="variance", seed=None) Sets params for the DecisionTreeRegressor. """ kwargs = self.setParams._input_kwargs |