Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/6346#discussion_r32670018
--- Diff: python/pyspark/mllib/feature.py ---
@@ -525,6 +526,41 @@ def fit(self, data):
return Word2VecModel(jmodel)
+class ElementwiseProduct(VectorTransformer):
+ """
+ .. note:: Experimental
+
+ Scales each column of the vector, with the supplied weight vector.
+ i.e the elementwise product.
+
+ >>> weight = Vectors.dense([1.0, 2.0, 3.0])
+ >>> eprod = ElementwiseProduct(weight)
+ >>> a = Vectors.dense([2.0, 1.0, 3.0])
+ >>> eprod.transform(a)
+ DenseVector([2.0, 2.0, 9.0])
+ >>> b = Vectors.dense([9.0, 3.0, 4.0])
+ >>> rdd = sc.parallelize([a, b])
+ >>> eprod.transform(rdd).collect()
+ [DenseVector([2.0, 2.0, 9.0]), DenseVector([9.0, 6.0, 12.0])]
+ """
+ def __init__(self, vector):
+ if not isinstance(vector, Vector):
--- End diff --
It will be good to support list and np.array
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