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From "Xiangrui Meng (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-3189) Add Robust Regression Algorithm with Turkey bisquare weight function (Biweight Estimates)
Date Mon, 24 Nov 2014 19:56:12 GMT

     [ 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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