diff --git a/python/pyspark/mllib/feature.py b/python/pyspark/mllib/feature.py
index f00bb93b7bf40ee36672512bb76e2a8183d121ae..b5138773fd61b276578bb21d8ef85dcf5a0bcc49 100644
--- a/python/pyspark/mllib/feature.py
+++ b/python/pyspark/mllib/feature.py
@@ -111,6 +111,15 @@ class JavaVectorTransformer(JavaModelWrapper, VectorTransformer):
     """
 
     def transform(self, vector):
+        """
+        Applies transformation on a vector or an RDD[Vector].
+
+        Note: In Python, transform cannot currently be used within
+              an RDD transformation or action.
+              Call transform directly on the RDD instead.
+
+        :param vector: Vector or RDD of Vector to be transformed.
+        """
         if isinstance(vector, RDD):
             vector = vector.map(_convert_to_vector)
         else:
@@ -191,7 +200,7 @@ class StandardScaler(object):
         Computes the mean and variance and stores as a model to be used
         for later scaling.
 
-        :param data: The data used to compute the mean and variance
+        :param dataset: The data used to compute the mean and variance
                      to build the transformation model.
         :return: a StandardScalarModel
         """
@@ -346,10 +355,6 @@ class IDFModel(JavaVectorTransformer):
                   vector
         :return: an RDD of TF-IDF vectors or a TF-IDF vector
         """
-        if isinstance(x, RDD):
-            return JavaVectorTransformer.transform(self, x)
-
-        x = _convert_to_vector(x)
         return JavaVectorTransformer.transform(self, x)
 
     def idf(self):