Github user harsha2010 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/6403#discussion_r31079398
  
    --- Diff: python/pyspark/ml/classification.py ---
    @@ -564,6 +564,92 @@ class GBTClassificationModel(JavaModel):
         """
     
     
    +@inherit_doc
    +class OneVsRest(JavaEstimator, HasFeaturesCol, HasLabelCol, 
HasPredictionCol):
    +    """
    +    `http://en.wikipedia.org/wiki/Multiclass_classification#One-vs.-rest`
    +    Reduction of Multiclass Classification to Binary Classification.
    +
    +    >>> from pyspark.sql import Row
    +    >>> from pyspark.mllib.linalg import Vectors
    +    >>> df = sc.parallelize([
    +    ...     Row(label=1.0, features=Vectors.dense(1.0)),
    +    ...     Row(label=0.0, features=Vectors.sparse(1, [], []))]).toDF()
    +    >>> lr = LogisticRegression(maxIter=5, regParam=0.01)
    +    >>> ovr = OneVsRest(classifier=lr).setPredictionCol("indexed")
    +    >>> model = ovr.fit(df)
    +    >>> test0 = sc.parallelize([Row(features=Vectors.dense(-1.0))]).toDF()
    +    >>> model.transform(test0).head().indexed
    +    0.0
    +    >>> test1 = sc.parallelize([Row(features=Vectors.sparse(1, [0], 
[1.0]))]).toDF()
    +    >>> model.transform(test1).head().indexed
    +    1.0
    +    """
    +
    +    # a placeholder to make it appear in the generated doc
    +    classifier = Param(Params._dummy(), "classifier", "base binary 
classifier")
    +
    +    @keyword_only
    +    def __init__(self, featuresCol="features", labelCol="label",
    +                 predictionCol="prediction", classifier=None):
    +        """
    +        __init__(self, featuresCol="features", labelCol="label", \
    +                 predictionCol="prediction", classifier=None)
    +        """
    +        super(OneVsRest, self).__init__()
    +        self._java_obj = self._new_java_obj(
    +            "org.apache.spark.ml.classification.OneVsRest", self.uid)
    +        #: param for base binary classifier
    +        self.classifier = Param(self, "classifier", "base binary 
classifier")
    +        kwargs = self.__init__._input_kwargs
    +        self._set(**kwargs)
    +
    +    @keyword_only
    +    def setParams(self, featuresCol="features", labelCol="label",
    +                  predictionCol="prediction", classifier=None):
    +        """
    +        setParams(self, featuresCol="features", labelCol="label", \
    +                  predictionCol="prediction", classifier=None):
    +        Sets params for OneVsRest.
    +        """
    +        kwargs = self.setParams._input_kwargs
    +        return self._set(**kwargs)
    +
    +    def setClassifier(self, value):
    +        """
    +        Sets the value of :py:attr:`estimator`.
    +        """
    +        self._paramMap[self.classifier] = value
    +        return self
    +
    +    def getClassifier(self):
    +        """
    +        Gets the value of classifier or its default value.
    +        """
    +        return self.getOrDefault(self.classifier)
    +
    +    def _create_model(self, java_model):
    +        return OneVsRestModel(java_model)
    +
    +    def _make_java_param_pair(self, param, value):
    --- End diff --
    
    @mengxr  good point, I didn't realize copying parameters needs to be done 
for pure python implementations as well. I can try to fix this and make it work 
for pure python implementation as well. 


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