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https://issues.apache.org/jira/browse/SPARK-17017?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen updated SPARK-17017:
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    Assignee: Peng Meng

> Add a chiSquare Selector based on False Positive Rate (FPR) test
> ----------------------------------------------------------------
>
>                 Key: SPARK-17017
>                 URL: https://issues.apache.org/jira/browse/SPARK-17017
>             Project: Spark
>          Issue Type: New Feature
>            Reporter: Peng Meng
>            Assignee: Peng Meng
>            Priority: Minor
>             Fix For: 2.1.0
>
>   Original Estimate: 24h
>  Remaining Estimate: 24h
>
> Univariate feature selection works by selecting the best features based on 
> univariate statistical tests. False Positive Rate (FPR) is a popular 
> univariate statistical test for feature selection. Is it necessary to add a 
> chiSquare Selector based on False Positive Rate (FPR) test, like it is 
> implemented in scikit-learn. 
> http://scikit-learn.org/stable/modules/feature_selection.html#univariate-feature-selection



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