diff options
Diffstat (limited to 'python/pyspark/ml/regression.py')
| -rw-r--r-- | python/pyspark/ml/regression.py | 13 |
1 files changed, 7 insertions, 6 deletions
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py index 898260879d..59d4fe3cf4 100644 --- a/python/pyspark/ml/regression.py +++ b/python/pyspark/ml/regression.py @@ -641,7 +641,7 @@ class GBTRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, >>> df = sqlContext.createDataFrame([ ... (1.0, Vectors.dense(1.0)), ... (0.0, Vectors.sparse(1, [], []))], ["label", "features"]) - >>> gbt = GBTRegressor(maxIter=5, maxDepth=2) + >>> gbt = GBTRegressor(maxIter=5, maxDepth=2, seed=42) >>> model = gbt.fit(df) >>> allclose(model.treeWeights, [1.0, 0.1, 0.1, 0.1, 0.1]) True @@ -664,18 +664,19 @@ class GBTRegressor(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, subsamplingRate=1.0, - checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1): + checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1, seed=None): """ __init__(self, featuresCol="features", labelCol="label", predictionCol="prediction", \ maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, \ maxMemoryInMB=256, cacheNodeIds=False, subsamplingRate=1.0, \ - checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1) + checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1, seed=None) """ super(GBTRegressor, self).__init__() self._java_obj = self._new_java_obj("org.apache.spark.ml.regression.GBTRegressor", self.uid) self._setDefault(maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, subsamplingRate=1.0, - checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1) + checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1, + seed=None) kwargs = self.__init__._input_kwargs self.setParams(**kwargs) @@ -684,12 +685,12 @@ class GBTRegressor(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, subsamplingRate=1.0, - checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1): + checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1, seed=None): """ setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction", \ maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, \ maxMemoryInMB=256, cacheNodeIds=False, subsamplingRate=1.0, \ - checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1) + checkpointInterval=10, lossType="squared", maxIter=20, stepSize=0.1, seed=None) Sets params for Gradient Boosted Tree Regression. """ kwargs = self.setParams._input_kwargs |