[SPARK-7382] [MLLIB] Feature Parity in PySpark for ml.classification

The missing pieces in ml.classification for Python!

cc mengxr

Author: Burak Yavuz <brkyvz@gmail.com>

Closes #6106 from brkyvz/ml-class and squashes the following commits:

dd78237 [Burak Yavuz] fix style
1048e29 [Burak Yavuz] ready for PR

1 files changed, 29 insertions, 0 deletions

diff --git a/python/pyspark/ml/param/shared.py b/python/pyspark/ml/param/shared.py
index 779cabe853..b116f05a06 100644
--- a/python/pyspark/ml/param/shared.py
+++ b/python/pyspark/ml/param/shared.py
@@ -165,6 +165,35 @@ class HasPredictionCol(Params):
         return self.getOrDefault(self.predictionCol)
 
 
+class HasProbabilityCol(Params):
+    """
+    Mixin for param probabilityCol: Column name for predicted class conditional probabilities. Note: Not all models output well-calibrated probability estimates! These probabilities should be treated as confidences, not precise probabilities..
+    """
+
+    # a placeholder to make it appear in the generated doc
+    probabilityCol = Param(Params._dummy(), "probabilityCol", "Column name for predicted class conditional probabilities. Note: Not all models output well-calibrated probability estimates! These probabilities should be treated as confidences, not precise probabilities.")
+
+    def __init__(self):
+        super(HasProbabilityCol, self).__init__()
+        #: param for Column name for predicted class conditional probabilities. Note: Not all models output well-calibrated probability estimates! These probabilities should be treated as confidences, not precise probabilities.
+        self.probabilityCol = Param(self, "probabilityCol", "Column name for predicted class conditional probabilities. Note: Not all models output well-calibrated probability estimates! These probabilities should be treated as confidences, not precise probabilities.")
+        if 'probability' is not None:
+            self._setDefault(probabilityCol='probability')
+
+    def setProbabilityCol(self, value):
+        """
+        Sets the value of :py:attr:`probabilityCol`.
+        """
+        self.paramMap[self.probabilityCol] = value
+        return self
+
+    def getProbabilityCol(self):
+        """
+        Gets the value of probabilityCol or its default value.
+        """
+        return self.getOrDefault(self.probabilityCol)
+
+
 class HasRawPredictionCol(Params):
     """
     Mixin for param rawPredictionCol: raw prediction (a.k.a. confidence) column name.