Skip to content

[SPARK-14374] [ML] [PySpark] PySpark ml GBTClassifier, Regressor support export/import #12383

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
yanboliang wants to merge 1 commit into from
Closed

[SPARK-14374] [ML] [PySpark] PySpark ml GBTClassifier, Regressor support export/import #12383

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
17 changes: 15 additions & 2 deletions python/pyspark/ml/classification.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -739,7 +739,8 @@ def featureImportances(self):

@inherit_doc
class GBTClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasMaxIter,
GBTParams, HasCheckpointInterval, HasStepSize, HasSeed):
GBTParams, HasCheckpointInterval, HasStepSize, HasSeed, JavaMLWritable,
JavaMLReadable):
"""
`http://en.wikipedia.org/wiki/Gradient_boosting Gradient-Boosted Trees (GBTs)`
learning algorithm for classification.
Expand Down Expand Up @@ -767,6 +768,18 @@ class GBTClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol
>>> test1 = sqlContext.createDataFrame([(Vectors.sparse(1, [0], [1.0]),)], ["features"])
>>> model.transform(test1).head().prediction
1.0
>>> gbtc_path = temp_path + "gbtc"
>>> gbt.save(gbtc_path)
>>> gbt2 = GBTClassifier.load(gbtc_path)
>>> gbt2.getMaxDepth()
2
>>> model_path = temp_path + "gbtc_model"
>>> model.save(model_path)
>>> model2 = GBTClassificationModel.load(model_path)
>>> model.featureImportances == model2.featureImportances
True
>>> model.treeWeights == model2.treeWeights
True

.. versionadded:: 1.4.0
"""
Expand Down Expand Up @@ -831,7 +844,7 @@ def getLossType(self):
return self.getOrDefault(self.lossType)


class GBTClassificationModel(TreeEnsembleModels):
class GBTClassificationModel(TreeEnsembleModels, JavaMLWritable, JavaMLReadable):
"""
Model fitted by GBTClassifier.

Expand Down
17 changes: 15 additions & 2 deletions python/pyspark/ml/regression.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -902,7 +902,8 @@ def featureImportances(self):

@inherit_doc
class GBTRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasMaxIter,
GBTParams, HasCheckpointInterval, HasStepSize, HasSeed):
GBTParams, HasCheckpointInterval, HasStepSize, HasSeed, JavaMLWritable,
JavaMLReadable):
"""
`http://en.wikipedia.org/wiki/Gradient_boosting Gradient-Boosted Trees (GBTs)`
learning algorithm for regression.
Expand All @@ -925,6 +926,18 @@ class GBTRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol,
>>> test1 = sqlContext.createDataFrame([(Vectors.sparse(1, [0], [1.0]),)], ["features"])
>>> model.transform(test1).head().prediction
1.0
>>> gbtr_path = temp_path + "gbtr"
>>> gbt.save(gbtr_path)
>>> gbt2 = GBTRegressor.load(gbtr_path)
>>> gbt2.getMaxDepth()
2
>>> model_path = temp_path + "gbtr_model"
>>> model.save(model_path)
>>> model2 = GBTRegressionModel.load(model_path)
>>> model.featureImportances == model2.featureImportances
True
>>> model.treeWeights == model2.treeWeights
True

.. versionadded:: 1.4.0
"""
Expand Down Expand Up @@ -989,7 +1002,7 @@ def getLossType(self):
return self.getOrDefault(self.lossType)


class GBTRegressionModel(TreeEnsembleModels):
class GBTRegressionModel(TreeEnsembleModels, JavaMLWritable, JavaMLReadable):
"""
Model fitted by GBTRegressor.

Expand Down