Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/10152#discussion_r47547211
--- 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 --
I think we should make it return proper cosine similarity. @jkbradley
thoughts?
Note that there is an outstanding JIRA SPARK-7617 and PR #6245 that
addresses the normalization, as well as caching the normalized vectors. Though
it is a bit stale now - if @ezli will be updating that PR soon we can make
those changes there, otherwise leave them for a follow-up PR?
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