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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2014/11/24 20:56:12 UTC
[jira] [Updated] (SPARK-3189) Add Robust Regression Algorithm with
Turkey bisquare weight function (Biweight Estimates)
[ https://issues.apache.org/jira/browse/SPARK-3189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiangrui Meng updated SPARK-3189:
---------------------------------
Fix Version/s: (was: 1.2.0)
(was: 1.1.1)
> Add Robust Regression Algorithm with Turkey bisquare weight function (Biweight Estimates)
> -------------------------------------------------------------------------------------------
>
> Key: SPARK-3189
> URL: https://issues.apache.org/jira/browse/SPARK-3189
> Project: Spark
> Issue Type: Sub-task
> Components: MLlib
> Affects Versions: 1.0.2
> Reporter: Fan Jiang
> Priority: Critical
> Labels: features
> Original Estimate: 0h
> Remaining Estimate: 0h
>
> Linear least square estimates assume the error has normal distribution and can behave badly when the errors are heavy-tailed. In practical we get various types of data. We need to include Robust Regression to employ a fitting criterion that is not as vulnerable as least square.
> The Turkey bisquare weight function, also referred to as the biweight function, produces and M-estimator that is more resistant to regression outliers than the Huber M-estimator ()Andersen 2008: 19).
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