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

["Yanbo Liang (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-13590?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15237022#comment-15237022 ] 

Yanbo Liang commented on SPARK-13590:
-------------------------------------

If there are constant columns and fitIntercept is false, Spark AFTSurvivalRegression output different solution from R survreg. We should also output a warning message and clarify in document. See discussion at https://github.com/apache/spark/pull/11365.

> Document the behavior of spark.ml logistic 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
>
> 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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