[jira] [Commented] (SPARK-2344) Add Fuzzy C-Means algorithm to MLlib

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-2344?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15083631#comment-15083631 ] 

Joseph K. Bradley commented on SPARK-2344:
------------------------------------------

Hi everyone,  thanks a lot for your work and discussion about this.  However, I think we'll need to postpone this feature because of limited review bandwidth and a need to focus on other items such as language API completeness, etc.  Would you be able to post your implementations as Spark packages?

For a less common algorithm such as this, it will also be important to collect feedback about how much it improves upon existing MLlib algorithms, so if you get feedback or results from users about your package, please post here.  I'll close this JIRA for now but will follow it.

Thanks for your understanding.

> Add Fuzzy C-Means algorithm to MLlib
> ------------------------------------
>
>                 Key: SPARK-2344
>                 URL: https://issues.apache.org/jira/browse/SPARK-2344
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: Alex
>            Priority: Minor
>              Labels: clustering
>   Original Estimate: 1m
>  Remaining Estimate: 1m
>
> I would like to add a FCM (Fuzzy C-Means) algorithm to MLlib.
> FCM is very similar to K - Means which is already implemented, and they differ only in the degree of relationship each point has with each cluster:
> (in FCM the relationship is in a range of [0..1] whether in K - Means its 0/1.
> As part of the implementation I would like:
> - create a base class for K- Means and FCM
> - implement the relationship for each algorithm differently (in its class)
> I'd like this to be assigned to me.



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