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https://issues.apache.org/jira/browse/SPARK-17471?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15477376#comment-15477376
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Yanbo Liang edited comment on SPARK-17471 at 9/9/16 3:46 PM:
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[~sethah] I think this task is duplicated with SPARK-17137 which will add
compressed support for multinomial logistic regression coefficients. I'm
working on that one and have some {{Matrix}} compression performance test
results. I will post them here for discussion as soon as possible. Thanks!
was (Author: yanboliang):
[~sethah] I think this task is duplicated with SPARK-17137 which will add
compressed support for multinomial logistic regression coefficients. I'm
working on that one and have some {{Matrix}} compression performance test
result. I will post them here for discussion as soon as possible. Thanks!
> Add compressed method for Matrix class
> --------------------------------------
>
> Key: SPARK-17471
> URL: https://issues.apache.org/jira/browse/SPARK-17471
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Seth Hendrickson
>
> Vectors in Spark have a {{compressed}} method which selects either sparse or
> dense representation by minimizing storage requirements. Matrices should also
> have this method, which is now explicitly needed in {{LogisticRegression}}
> since we have implemented multiclass regression.
> The compressed method should also give the option to store row major or
> column major, and if nothing is specified should select the lower storage
> representation (for sparse).
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