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https://issues.apache.org/jira/browse/SPARK-14516?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15240434#comment-15240434
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zhengruifeng commented on SPARK-14516:
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[~akamal] In my opinion, both supervised and unsupervised metrics shoud be
added. And in unsupervised metrics, silhouette should be add first. I will
create a online document. Thanks.
> Clustering evaluator
> --------------------
>
> Key: SPARK-14516
> URL: https://issues.apache.org/jira/browse/SPARK-14516
> Project: Spark
> Issue Type: Brainstorming
> Components: ML
> Reporter: zhengruifeng
> Priority: Minor
>
> MLlib does not have any general purposed clustering metrics with a ground
> truth.
> In
> [Scikit-Learn](http://scikit-learn.org/stable/modules/classes.html#clustering-metrics),
> there are several kinds of metrics for this.
> It may be meaningful to add some clustering metrics into MLlib.
> This should be added as a {{ClusteringEvaluator}} class of extending
> {{Evaluator}} in spark.ml.
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