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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2016/04/06 21:52:25 UTC
[jira] [Updated] (SPARK-8986) GaussianMixture should take smoothing
param
[ https://issues.apache.org/jira/browse/SPARK-8986?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley updated SPARK-8986:
-------------------------------------
Component/s: (was: MLlib)
ML
> GaussianMixture should take smoothing param
> -------------------------------------------
>
> Key: SPARK-8986
> URL: https://issues.apache.org/jira/browse/SPARK-8986
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Joseph K. Bradley
> Original Estimate: 144h
> Remaining Estimate: 144h
>
> Gaussian mixture models should take a smoothing parameter which makes the algorithm robust against degenerate data or bad initializations.
> Whomever takes this JIRA should look at other libraries (sklearn, R packages, Weka, etc.) to see how they do smoothing and what their API looks like. Please summarize your findings here.
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