ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity

[SPARK-28969][PYTHON][ML] OneVsRestParams parity between scala and python

Browse source 
### What changes were proposed in this pull request?
Follow the scala ```OneVsRestParams``` implementation, move ```setClassifier``` from ```OneVsRestParams``` to ```OneVsRest``` in Pyspark

### Why are the changes needed?
1. Maintain the parity between scala and python code.
2. ```Classifier``` can only be set in the estimator.

### Does this PR introduce any user-facing change?
Yes.
Previous behavior: ```OneVsRestModel``` has method ```setClassifier```
Current behavior:  ```setClassifier``` is removed from ```OneVsRestModel```. ```classifier``` can only be set in ```OneVsRest```.

### How was this patch tested?
Use existing tests

Closes #25715 from huaxingao/spark-28969.

Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
This commit is contained in:
Huaxin Gao 2019-09-13 12:29:19 -05:00 committed by Sean Owen
parent fcf9b41b49
commit 77e9b58d4f
1 changed files with 9 additions and 10 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

19
python/pyspark/ml/classification.py
View file

@ -1872,15 +1872,6 @@ class OneVsRestParams(HasFeaturesCol, HasLabelCol, HasWeightCol, HasPredictionCo
classifier = Param(Params._dummy(), "classifier", "base binary classifier")
@since("2.0.0")
def setClassifier(self, value):
"""
Sets the value of :py:attr:`classifier`.
.. note:: Only LogisticRegression and NaiveBayes are supported now.
"""
return self._set(classifier=value)
@since("2.0.0")
def getClassifier(self):
"""
@ -1959,6 +1950,13 @@ class OneVsRest(Estimator, OneVsRestParams, HasParallelism, JavaMLReadable, Java
kwargs = self._input_kwargs
return self._set(**kwargs)
@since("2.0.0")
def setClassifier(self, value):
"""
Sets the value of :py:attr:`classifier`.
"""
return self._set(classifier=value)
def _fit(self, dataset):
labelCol = self.getLabelCol()
featuresCol = self.getFeaturesCol()
@ -2212,7 +2210,8 @@ class OneVsRestModel(Model, OneVsRestParams, JavaMLReadable, JavaMLWritable):
classifier = JavaParams._from_java(java_stage.getClassifier())
models = [JavaParams._from_java(model) for model in java_stage.models()]
py_stage = cls(models=models).setPredictionCol(predictionCol).setLabelCol(labelCol)\
.setFeaturesCol(featuresCol).setClassifier(classifier)
.setFeaturesCol(featuresCol)
py_stage._set(classifier=classifier)
py_stage._resetUid(java_stage.uid())
return py_stage