[jira] [Created] (SPARK-8540) KMeans-based outlier detection

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

Joseph K. Bradley created SPARK-8540:
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             Summary: 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


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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