diff options
Diffstat (limited to 'python')
-rw-r--r-- | python/pyspark/ml/classification.py | 13 | ||||
-rw-r--r-- | python/pyspark/ml/regression.py | 14 |
2 files changed, 17 insertions, 10 deletions
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py index 5599b8f3ec..265c6a14f1 100644 --- a/python/pyspark/ml/classification.py +++ b/python/pyspark/ml/classification.py @@ -273,7 +273,7 @@ class GBTParams(TreeEnsembleParams): @inherit_doc class DecisionTreeClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasProbabilityCol, HasRawPredictionCol, DecisionTreeParams, - TreeClassifierParams, HasCheckpointInterval): + TreeClassifierParams, HasCheckpointInterval, HasSeed): """ `http://en.wikipedia.org/wiki/Decision_tree_learning Decision tree` learning algorithm for classification. @@ -313,12 +313,14 @@ class DecisionTreeClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPred def __init__(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"): + maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity="gini", + seed=None): """ __init__(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") + maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity="gini", \ + seed=None) """ super(DecisionTreeClassifier, self).__init__() self._java_obj = self._new_java_obj( @@ -335,12 +337,13 @@ class DecisionTreeClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPred probabilityCol="probability", rawPredictionCol="rawPrediction", maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, - impurity="gini"): + 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") + maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity="gini", \ + seed=None) Sets params for the DecisionTreeClassifier. """ kwargs = self.setParams._input_kwargs 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 |