[
https://issues.apache.org/jira/browse/SPARK-2344?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Beniamino updated SPARK-2344:
-----------------------------
Comment: was deleted
(was: Yeah, sure!
I took a look at your implementation and I don't think that's a good idea to
store the membership degree matrix because it could be very huge.
My algorithm works without store the matrix. I've tested it on Iris dataset and
it seems to already work. Now I'm adding the computation of the Fukuyama-Sugeno
validity index.
I'll be available for anything.
)
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
