[ https://issues.apache.org/jira/browse/SPARK-17017?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-17017. ------------------------------- Resolution: Fixed Fix Version/s: 2.1.0 Issue resolved by pull request 14597 [https://github.com/apache/spark/pull/14597] > 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 > 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 -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org