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https://issues.apache.org/jira/browse/SPARK-8540?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14615596#comment-14615596
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Venkata Vineel commented on SPARK-8540:
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[~josephkb] Yes, I looked there, but there is no clarity on which issues can be
worked upon.(Some are open and unassigned ,but still had people working on
them, please consider helping me pick some thing up).
> KMeans-based outlier detection
> ------------------------------
>
> Key: SPARK-8540
> URL: https://issues.apache.org/jira/browse/SPARK-8540
> Project: Spark
> Issue Type: Sub-task
> Components: ML
> Reporter: Joseph K. Bradley
> Original Estimate: 336h
> Remaining Estimate: 336h
>
> Proposal for K-Means-based outlier detection:
> * Cluster data using K-Means
> * Provide prediction/filtering functionality which returns outliers/anomalies
> ** This can take some threshold parameter which specifies either (a) how far
> off a point needs to be to be considered an outlier or (b) how many outliers
> should be returned.
> Note this will require a bit of API design, which should probably be posted
> and discussed on this JIRA before implementation.
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