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https://issues.apache.org/jira/browse/SPARK-19313?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-19313:
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Assignee: Apache Spark
> GaussianMixture throws cryptic error when number of features is too high
> ------------------------------------------------------------------------
>
> Key: SPARK-19313
> URL: https://issues.apache.org/jira/browse/SPARK-19313
> Project: Spark
> Issue Type: Bug
> Components: ML, MLlib
> Reporter: Seth Hendrickson
> Assignee: Apache Spark
> Priority: Minor
>
> The following fails
> {code}
> val df = Seq(
> Vectors.sparse(46400, Array(0, 4), Array(3.0, 8.0)),
> Vectors.sparse(46400, Array(1, 5), Array(4.0, 9.0)))
> .map(Tuple1.apply).toDF("features")
> val gm = new GaussianMixture()
> gm.fit(df)
> {code}
> It fails because GMMs allocate an array of size {{numFeatures * numFeatures}}
> and in this case we'll get integer overflow. We should limit the number of
> features appropriately.
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