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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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Apache Spark reassigned SPARK-17017:
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Assignee: Apache Spark
> 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
> Affects Versions: 2.0.0
> Reporter: Peng Meng
> Assignee: Apache Spark
> Priority: Minor
> 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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