[
https://issues.apache.org/jira/browse/SPARK-14022?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-14022.
-------------------------------
Resolution: Invalid
Let's start questions on user@.
Read
https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark#ContributingtoSpark-MLlib-specificContributionGuidelines
first
> What about adding RandomProjection to ML/MLLIB as a new dimensionality
> reduction algorithm?
> -------------------------------------------------------------------------------------------
>
> Key: SPARK-14022
> URL: https://issues.apache.org/jira/browse/SPARK-14022
> Project: Spark
> Issue Type: Question
> Reporter: zhengruifeng
> Priority: Minor
>
> What about adding RandomProjection to ML/MLLIB as a new dimensionality
> reduction algorithm?
> RandomProjection (https://en.wikipedia.org/wiki/Random_projection) reduces
> the dimensionality by projecting the original input space on a randomly
> generated matrix.
> It is fully scalable, and runs fast (maybe fastest).
> It was implemented in sklearn
> (http://scikit-learn.org/stable/modules/random_projection.html)
> I am be willing to do this, if needed.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
