[SPARK-29381][PYTHON][ML] Add _ before the XXXParams classes
### What changes were proposed in this pull request? Add _ before XXXParams classes to indicate internal usage ### Why are the changes needed? Follow the PEP 8 convention to use _single_leading_underscore to indicate internal use ### Does this PR introduce any user-facing change? No ### How was this patch tested? use existing tests Closes #26103 from huaxingao/spark-29381. Authored-by: Huaxin Gao <huaxing@us.ibm.com> Signed-off-by: Sean Owen <sean.owen@databricks.com>
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Huaxin Gao
Sean Owen
parent
da576a737c
commit
cfcaf528cd
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@ -28,7 +28,7 @@ from pyspark.ml.tree import _DecisionTreeModel, _DecisionTreeParams, \
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from pyspark.ml.regression import DecisionTreeRegressionModel
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from pyspark.ml.util import *
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from pyspark.ml.wrapper import JavaEstimator, JavaModel, JavaParams, \
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JavaPredictor, JavaPredictorParams, JavaPredictionModel, JavaWrapper
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JavaPredictor, _JavaPredictorParams, JavaPredictionModel, JavaWrapper
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from pyspark.ml.common import inherit_doc, _java2py, _py2java
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from pyspark.ml.linalg import Vectors
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from pyspark.sql import DataFrame
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@ -48,15 +48,17 @@ __all__ = ['LinearSVC', 'LinearSVCModel',
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'OneVsRest', 'OneVsRestModel']
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class JavaClassifierParams(HasRawPredictionCol, JavaPredictorParams):
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class _JavaClassifierParams(HasRawPredictionCol, _JavaPredictorParams):
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"""
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(Private) Java Classifier Params for classification tasks.
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Java Classifier Params for classification tasks.
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.. versionadded:: 3.0.0
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"""
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pass
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@inherit_doc
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class JavaClassifier(JavaPredictor, JavaClassifierParams):
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class JavaClassifier(JavaPredictor, _JavaClassifierParams):
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"""
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Java Classifier for classification tasks.
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Classes are indexed {0, 1, ..., numClasses - 1}.
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@ -71,7 +73,7 @@ class JavaClassifier(JavaPredictor, JavaClassifierParams):
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@inherit_doc
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class JavaClassificationModel(JavaPredictionModel, JavaClassifierParams):
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class JavaClassificationModel(JavaPredictionModel, _JavaClassifierParams):
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"""
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Java Model produced by a ``Classifier``.
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Classes are indexed {0, 1, ..., numClasses - 1}.
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@ -94,15 +96,18 @@ class JavaClassificationModel(JavaPredictionModel, JavaClassifierParams):
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return self._call_java("numClasses")
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class JavaProbabilisticClassifierParams(HasProbabilityCol, HasThresholds, JavaClassifierParams):
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class _JavaProbabilisticClassifierParams(HasProbabilityCol, HasThresholds, _JavaClassifierParams):
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"""
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(Private) Java Probabilistic Classifier Params for classification tasks.
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Params for :py:class:`JavaProbabilisticClassifier` and
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:py:class:`JavaProbabilisticClassificationModel`.
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.. versionadded:: 3.0.0
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"""
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pass
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@inherit_doc
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class JavaProbabilisticClassifier(JavaClassifier, JavaProbabilisticClassifierParams):
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class JavaProbabilisticClassifier(JavaClassifier, _JavaProbabilisticClassifierParams):
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"""
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Java Probabilistic Classifier for classification tasks.
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"""
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@ -124,7 +129,7 @@ class JavaProbabilisticClassifier(JavaClassifier, JavaProbabilisticClassifierPar
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@inherit_doc
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class JavaProbabilisticClassificationModel(JavaClassificationModel,
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JavaProbabilisticClassifierParams):
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_JavaProbabilisticClassifierParams):
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"""
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Java Model produced by a ``ProbabilisticClassifier``.
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"""
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@ -1368,9 +1373,9 @@ class RandomForestClassificationModel(_TreeEnsembleModel, JavaProbabilisticClass
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return [DecisionTreeClassificationModel(m) for m in list(self._call_java("trees"))]
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class GBTClassifierParams(_GBTParams, _HasVarianceImpurity):
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class _GBTClassifierParams(_GBTParams, _HasVarianceImpurity):
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"""
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Private class to track supported GBTClassifier params.
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Params for :py:class:`GBTClassifier` and :py:class:`GBTClassifierModel`.
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.. versionadded:: 3.0.0
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"""
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@ -1391,7 +1396,7 @@ class GBTClassifierParams(_GBTParams, _HasVarianceImpurity):
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@inherit_doc
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class GBTClassifier(JavaProbabilisticClassifier, GBTClassifierParams,
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class GBTClassifier(JavaProbabilisticClassifier, _GBTClassifierParams,
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JavaMLWritable, JavaMLReadable):
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"""
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`Gradient-Boosted Trees (GBTs) <http://en.wikipedia.org/wiki/Gradient_boosting>`_
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@ -1602,7 +1607,7 @@ class GBTClassifier(JavaProbabilisticClassifier, GBTClassifierParams,
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class GBTClassificationModel(_TreeEnsembleModel, JavaProbabilisticClassificationModel,
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GBTClassifierParams, JavaMLWritable, JavaMLReadable):
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_GBTClassifierParams, JavaMLWritable, JavaMLReadable):
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"""
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Model fitted by GBTClassifier.
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@ -1990,9 +1995,9 @@ class MultilayerPerceptronClassificationModel(JavaProbabilisticClassificationMod
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return self._call_java("weights")
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class OneVsRestParams(JavaClassifierParams, HasWeightCol):
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class _OneVsRestParams(_JavaClassifierParams, HasWeightCol):
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"""
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Parameters for OneVsRest and OneVsRestModel.
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Params for :py:class:`OneVsRest` and :py:class:`OneVsRestModelModel`.
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"""
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classifier = Param(Params._dummy(), "classifier", "base binary classifier")
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@ -2006,7 +2011,7 @@ class OneVsRestParams(JavaClassifierParams, HasWeightCol):
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@inherit_doc
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class OneVsRest(Estimator, OneVsRestParams, HasParallelism, JavaMLReadable, JavaMLWritable):
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class OneVsRest(Estimator, _OneVsRestParams, HasParallelism, JavaMLReadable, JavaMLWritable):
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"""
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Reduction of Multiclass Classification to Binary Classification.
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Performs reduction using one against all strategy.
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@ -2227,7 +2232,7 @@ class OneVsRest(Estimator, OneVsRestParams, HasParallelism, JavaMLReadable, Java
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return paramMap
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class OneVsRestModel(Model, OneVsRestParams, JavaMLReadable, JavaMLWritable):
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class OneVsRestModel(Model, _OneVsRestParams, JavaMLReadable, JavaMLWritable):
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"""
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Model fitted by OneVsRest.
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This stores the models resulting from training k binary classifiers: one for each class.
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@ -366,15 +366,17 @@ class JavaModel(JavaTransformer, Model):
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@inherit_doc
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class JavaPredictorParams(HasLabelCol, HasFeaturesCol, HasPredictionCol):
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class _JavaPredictorParams(HasLabelCol, HasFeaturesCol, HasPredictionCol):
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"""
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(Private) Trait for parameters for prediction (regression and classification)
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Params for :py:class:`JavaPredictor` and :py:class:`JavaPredictorModel`.
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.. versionadded:: 3.0.0
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"""
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pass
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@inherit_doc
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class JavaPredictor(JavaEstimator, JavaPredictorParams):
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class JavaPredictor(JavaEstimator, _JavaPredictorParams):
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"""
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(Private) Java Estimator for prediction tasks (regression and classification).
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"""
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@ -402,7 +404,7 @@ class JavaPredictor(JavaEstimator, JavaPredictorParams):
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@inherit_doc
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class JavaPredictionModel(JavaModel, JavaPredictorParams):
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class JavaPredictionModel(JavaModel, _JavaPredictorParams):
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"""
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(Private) Java Model for prediction tasks (regression and classification).
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"""
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