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https://issues.apache.org/jira/browse/SPARK-22195?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16193844#comment-16193844
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yuhao yang edited comment on SPARK-22195 at 10/6/17 7:33 AM:
-------------------------------------------------------------
Thanks for the feedback.
I don't see the existing implementation (RowMatrix or in Word2Vec) can fulfill
the two scenarios:
1. Compute cosine similarity between two arbitrary vectors.
2. Compute cosine similarity between one vector and a group of other Vectors
(usually candidates).
And I'm afraid that not everyone using Spark ML knows how to implement cosine
similarity.
was (Author: yuhaoyan):
Thanks for the feedback.
I don't see the existing implementation (RowMatrix or in Word2Vec) can fulfill
the two scenarios:
1. Compute cosine similarity between two arbitrary vectors.
2. Compute cosine similarity between one vector and a group of other Vectors
(usually candidates).
And again, not everyone using Spark ML know how to implement cosine similarity.
> 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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