Github user ygcao commented on a diff in the pull request:
https://github.com/apache/spark/pull/10152#discussion_r47739429
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -534,8 +577,15 @@ class Word2VecModel private[spark] (
// Need not divide with the norm of the given vector since it is
constant.
val cosVec = cosineVec.map(_.toDouble)
var ind = 0
+ var vecNorm = 1f
+ if (norm) {
--- End diff --
OK. Let me pull back the changes about normalization then. we can use the
other pull request for follow up of normalization.
As @srowen mentioned, normalization can be done after getting top K in the
application as well.
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