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https://issues.apache.org/jira/browse/SPARK-22195?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16191037#comment-16191037
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Sean Owen commented on SPARK-22195:
-----------------------------------
When I've heard this, it's been in the context of supporting this similarity
in other implementations. For example RowMatrix already does all-pairs cosine
similarity. And here's an item for supporting it in k-means:
https://issues.apache.org/jira/browse/SPARK-22119
I'm skeptical it's worth providing this as a stand-alone utility method but I
can't feel strongly about it.
> Add cosine similarity to org.apache.spark.ml.linalg.Vectors
> -----------------------------------------------------------
>
> Key: SPARK-22195
> URL: https://issues.apache.org/jira/browse/SPARK-22195
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Affects Versions: 2.2.0
> Reporter: yuhao yang
> Priority: Minor
>
> https://en.wikipedia.org/wiki/Cosine_similarity:
> As the most important measure of similarity, I found it quite useful in some
> image and NLP applications according to personal experience.
> Suggest to add function for cosine similarity in
> org.apache.spark.ml.linalg.Vectors.
> Interface:
> def cosineSimilarity(v1: Vector, v2: Vector): Double = ...
> def cosineSimilarity(v1: Vector, v2: Vector, norm1: Double, norm2: Double):
> Double = ...
> Appreciate suggestions and need green light from committers.
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