[jira] [Commented] (SPARK-13590) Document the behavior of spark.ml logistic regression and AFT survival regression when there are constant features

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-13590?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15259878#comment-15259878 ] 

Apache Spark commented on SPARK-13590:
--------------------------------------

User 'yanboliang' has created a pull request for this issue:
https://github.com/apache/spark/pull/12731

> Document the behavior of spark.ml logistic regression and AFT survival regression when there are constant features
> ------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-13590
>                 URL: https://issues.apache.org/jira/browse/SPARK-13590
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 2.0.0
>            Reporter: Xiangrui Meng
>            Assignee: Yanbo Liang
>
> As discussed in SPARK-13029, we decided to keep the current behavior that sets all coefficients associated with constant feature columns to zero, regardless of intercept, regularization, and standardization settings. This is the same behavior as in glmnet. Since this is different from LIBSVM, we should document the behavior correctly, add tests, and generate warning messages if there are constant columns and `addIntercept` is false.
> cc [~coderxiang] [~dbtsai]



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