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https://issues.apache.org/jira/browse/FLINK-3128?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15130259#comment-15130259
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ASF GitHub Bot commented on FLINK-3128:
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Github user f-sander commented on the pull request:
https://github.com/apache/flink/pull/1565#issuecomment-179177999
Thanks for your Feedback!
Yes, scalability is the main issue for us too. We are not aware of any
other parallel implementation
he main issue for us too. We also talked to the original author of Spark's
IR implementation (which is equivalent too ours) about this with the same
result. However, we think we have a theoretical approach to solving this, but
it depends on the self join without duplicates. Remember our discussion on the
user-mailing list with subject `join with no element appearing in multiple
join-pairs`? I need that for this.
I will link a sketch to our algorithm design here in a few days, If we
haven't found a way to solve this. I guess IR won't make it into Flink without
a fully parallelized way?
> Add Isotonic Regression To ML Library
> -------------------------------------
>
> Key: FLINK-3128
> URL: https://issues.apache.org/jira/browse/FLINK-3128
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Fridtjof Sander
> Assignee: Fridtjof Sander
> Priority: Minor
>
> Isotonic Regression fits a monotonically increasing function (also called
> isotonic function) to a plane of datapoints.
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