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https://issues.apache.org/jira/browse/SPARK-5992?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14575002#comment-14575002
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Karl Higley commented on SPARK-5992:
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To make it easier to define a common interface, it might help to restrict
consideration to methods that produce hash signatures. For cosine similarity,
sign-random-projection LSH would probably fit the bill. See Section 3 of
"Similarity Estimation Techniques from Rounding
Algorithms"
http://www.cs.princeton.edu/courses/archive/spr04/cos598B/bib/CharikarEstim.pdf
> Locality Sensitive Hashing (LSH) for MLlib
> ------------------------------------------
>
> Key: SPARK-5992
> URL: https://issues.apache.org/jira/browse/SPARK-5992
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Affects Versions: 1.4.0
> Reporter: Joseph K. Bradley
>
> Locality Sensitive Hashing (LSH) would be very useful for ML. It would be
> great to discuss some possible algorithms here, choose an API, and make a PR
> for an initial algorithm.
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