[SPARK-7333] [MLLIB] Add BinaryClassificationEvaluator to PySpark

This PR adds `BinaryClassificationEvaluator` to Python ML Pipelines API, which is a simple wrapper of the Scala implementation. oefirouz

Author: Xiangrui Meng <meng@databricks.com>

Closes #5885 from mengxr/SPARK-7333 and squashes the following commits:

25d7451 [Xiangrui Meng] fix tests in python 3
babdde7 [Xiangrui Meng] fix doc
cb51e6a [Xiangrui Meng] add BinaryClassificationEvaluator in PySpark

1 files changed, 22 insertions, 1 deletions

diff --git a/python/pyspark/ml/pipeline.py b/python/pyspark/ml/pipeline.py
index 7c1ec3026d..7b875e4b71 100644
--- a/python/pyspark/ml/pipeline.py
+++ b/python/pyspark/ml/pipeline.py
@@ -22,7 +22,7 @@ from pyspark.ml.util import keyword_only
 from pyspark.mllib.common import inherit_doc
 
 
-__all__ = ['Estimator', 'Transformer', 'Pipeline', 'PipelineModel']
+__all__ = ['Estimator', 'Transformer', 'Pipeline', 'PipelineModel', 'Evaluator']
 
 
 @inherit_doc
@@ -168,3 +168,24 @@ class PipelineModel(Transformer):
         for t in self.transformers:
             dataset = t.transform(dataset, paramMap)
         return dataset
+
+
+class Evaluator(object):
+    """
+    Base class for evaluators that compute metrics from predictions.
+    """
+
+    __metaclass__ = ABCMeta
+
+    @abstractmethod
+    def evaluate(self, dataset, params={}):
+        """
+        Evaluates the output.
+
+        :param dataset: a dataset that contains labels/observations and
+                        predictions
+        :param params: an optional param map that overrides embedded
+                       params
+        :return: metric
+        """
+        raise NotImplementedError()