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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2015/05/07 23:51:00 UTC
[jira] [Resolved] (SPARK-5726) Hadamard Vector Product Transformer
[ https://issues.apache.org/jira/browse/SPARK-5726?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley resolved SPARK-5726.
--------------------------------------
Resolution: Fixed
Fix Version/s: 1.4.0
Issue resolved by pull request 4580
[https://github.com/apache/spark/pull/4580]
> Hadamard Vector Product Transformer
> -----------------------------------
>
> Key: SPARK-5726
> URL: https://issues.apache.org/jira/browse/SPARK-5726
> Project: Spark
> Issue Type: Improvement
> Components: ML, MLlib
> Reporter: Octavian Geagla
> Assignee: Octavian Geagla
> Fix For: 1.4.0
>
>
> I originally posted my idea here: http://apache-spark-developers-list.1001551.n3.nabble.com/Any-interest-in-weighting-VectorTransformer-which-does-component-wise-scaling-td10265.html
> A draft of this feature is implemented, documented, and tested already. Code is on a branch on my fork here: https://github.com/ogeagla/spark/compare/spark-mllib-weighting
> I'm curious if there is any interest in this feature, in which case I'd appreciate some feedback. One thing that might be useful is an example/test case using the transformer within the ML pipeline, since there are not any examples which use Vectors.
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