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[SPARK-30533][ML][PYSPARK] Add classes to represent Java Regressors and RegressionModels #27241

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[SPARK-30533][ML][PYSPARK] Add classes to represent Java Regressors and RegressionModels #27241

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8c5988a
Add classes to represent Java Regressors and RegressionModels
zero323 Jan 16, 2020
b8127b9
Fix style
zero323 Jan 16, 2020
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58 changes: 42 additions & 16 deletions python/pyspark/ml/regression.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,25 @@
'FMRegressor', 'FMRegressionModel']


class JavaRegressor(JavaPredictor, _JavaPredictorParams):
"""
Java Regressor for regression tasks.

.. versionadded:: 3.0.0
"""
pass


class JavaRegressionModel(JavaPredictionModel, _JavaPredictorParams):
"""
Java Model produced by a ``_JavaRegressor``.
To be mixed in with class:`pyspark.ml.JavaModel`

.. versionadded:: 3.0.0
"""
pass


class _LinearRegressionParams(_JavaPredictorParams, HasRegParam, HasElasticNetParam, HasMaxIter,
HasTol, HasFitIntercept, HasStandardization, HasWeightCol, HasSolver,
HasAggregationDepth, HasLoss):
Expand Down Expand Up @@ -69,7 +88,7 @@ def getEpsilon(self):


@inherit_doc
class LinearRegression(JavaPredictor, _LinearRegressionParams, JavaMLWritable, JavaMLReadable):
class LinearRegression(JavaRegressor, _LinearRegressionParams, JavaMLWritable, JavaMLReadable):
"""
Linear regression.

Expand Down Expand Up @@ -251,7 +270,7 @@ def setLoss(self, value):
return self._set(lossType=value)


class LinearRegressionModel(JavaPredictionModel, _LinearRegressionParams, GeneralJavaMLWritable,
class LinearRegressionModel(JavaRegressionModel, _LinearRegressionParams, GeneralJavaMLWritable,
JavaMLReadable, HasTrainingSummary):
"""
Model fitted by :class:`LinearRegression`.
Expand Down Expand Up @@ -758,7 +777,7 @@ class _DecisionTreeRegressorParams(_DecisionTreeParams, _TreeRegressorParams, Ha


@inherit_doc
class DecisionTreeRegressor(JavaPredictor, _DecisionTreeRegressorParams, JavaMLWritable,
class DecisionTreeRegressor(JavaRegressor, _DecisionTreeRegressorParams, JavaMLWritable,
JavaMLReadable):
"""
`Decision tree <http://en.wikipedia.org/wiki/Decision_tree_learning>`_
Expand Down Expand Up @@ -953,8 +972,10 @@ def setVarianceCol(self, value):


@inherit_doc
class DecisionTreeRegressionModel(_DecisionTreeModel, _DecisionTreeRegressorParams,
JavaMLWritable, JavaMLReadable):
class DecisionTreeRegressionModel(
JavaRegressionModel, _DecisionTreeModel, _DecisionTreeRegressorParams,
JavaMLWritable, JavaMLReadable
):
"""
Model fitted by :class:`DecisionTreeRegressor`.

Expand Down Expand Up @@ -1000,7 +1021,7 @@ class _RandomForestRegressorParams(_RandomForestParams, _TreeRegressorParams):


@inherit_doc
class RandomForestRegressor(JavaPredictor, _RandomForestRegressorParams, JavaMLWritable,
class RandomForestRegressor(JavaRegressor, _RandomForestRegressorParams, JavaMLWritable,
JavaMLReadable):
"""
`Random Forest <http://en.wikipedia.org/wiki/Random_forest>`_
Expand Down Expand Up @@ -1198,8 +1219,10 @@ def setMinWeightFractionPerNode(self, value):
return self._set(minWeightFractionPerNode=value)


class RandomForestRegressionModel(_TreeEnsembleModel, _RandomForestRegressorParams,
JavaMLWritable, JavaMLReadable):
class RandomForestRegressionModel(
JavaRegressionModel, _TreeEnsembleModel, _RandomForestRegressorParams,
JavaMLWritable, JavaMLReadable
):
"""
Model fitted by :class:`RandomForestRegressor`.

Expand Down Expand Up @@ -1251,7 +1274,7 @@ def getLossType(self):


@inherit_doc
class GBTRegressor(JavaPredictor, _GBTRegressorParams, JavaMLWritable, JavaMLReadable):
class GBTRegressor(JavaRegressor, _GBTRegressorParams, JavaMLWritable, JavaMLReadable):
"""
`Gradient-Boosted Trees (GBTs) <http://en.wikipedia.org/wiki/Gradient_boosting>`_
learning algorithm for regression.
Expand Down Expand Up @@ -1492,7 +1515,10 @@ def setMinWeightFractionPerNode(self, value):
return self._set(minWeightFractionPerNode=value)


class GBTRegressionModel(_TreeEnsembleModel, _GBTRegressorParams, JavaMLWritable, JavaMLReadable):
class GBTRegressionModel(
JavaRegressionModel, _TreeEnsembleModel, _GBTRegressorParams,
JavaMLWritable, JavaMLReadable
):
"""
Model fitted by :class:`GBTRegressor`.

Expand Down Expand Up @@ -1582,7 +1608,7 @@ def getQuantilesCol(self):


@inherit_doc
class AFTSurvivalRegression(JavaPredictor, _AFTSurvivalRegressionParams,
class AFTSurvivalRegression(JavaRegressor, _AFTSurvivalRegressionParams,
JavaMLWritable, JavaMLReadable):
"""
Accelerated Failure Time (AFT) Model Survival Regression
Expand Down Expand Up @@ -1723,7 +1749,7 @@ def setAggregationDepth(self, value):
return self._set(aggregationDepth=value)


class AFTSurvivalRegressionModel(JavaPredictionModel, _AFTSurvivalRegressionParams,
class AFTSurvivalRegressionModel(JavaRegressionModel, _AFTSurvivalRegressionParams,
JavaMLWritable, JavaMLReadable):
"""
Model fitted by :class:`AFTSurvivalRegression`.
Expand Down Expand Up @@ -1855,7 +1881,7 @@ def getOffsetCol(self):


@inherit_doc
class GeneralizedLinearRegression(JavaPredictor, _GeneralizedLinearRegressionParams,
class GeneralizedLinearRegression(JavaRegressor, _GeneralizedLinearRegressionParams,
JavaMLWritable, JavaMLReadable):
"""
Generalized Linear Regression.
Expand Down Expand Up @@ -2060,7 +2086,7 @@ def setAggregationDepth(self, value):
return self._set(aggregationDepth=value)


class GeneralizedLinearRegressionModel(JavaPredictionModel, _GeneralizedLinearRegressionParams,
class GeneralizedLinearRegressionModel(JavaRegressionModel, _GeneralizedLinearRegressionParams,
JavaMLWritable, JavaMLReadable, HasTrainingSummary):
"""
Model fitted by :class:`GeneralizedLinearRegression`.
Expand Down Expand Up @@ -2348,7 +2374,7 @@ def getInitStd(self):


@inherit_doc
class FMRegressor(JavaPredictor, _FactorizationMachinesParams, JavaMLWritable, JavaMLReadable):
class FMRegressor(JavaRegressor, _FactorizationMachinesParams, JavaMLWritable, JavaMLReadable):
"""
Factorization Machines learning algorithm for regression.

Expand Down Expand Up @@ -2512,7 +2538,7 @@ def setRegParam(self, value):
return self._set(regParam=value)


class FMRegressionModel(JavaPredictionModel, _FactorizationMachinesParams, JavaMLWritable,
class FMRegressionModel(JavaRegressionModel, _FactorizationMachinesParams, JavaMLWritable,
JavaMLReadable):
"""
Model fitted by :class:`FMRegressor`.
Expand Down