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Posted to issues@spark.apache.org by "Peng Meng (JIRA)" <ji...@apache.org> on 2016/08/11 07:59:20 UTC
[jira] [Updated] (SPARK-17017) Add a chiSquare Selector based on
False Positive Rate (FPR) test
[ https://issues.apache.org/jira/browse/SPARK-17017?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Peng Meng updated SPARK-17017:
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Affects Version/s: (was: 2.0.0)
> 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
> 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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