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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2016/03/01 08:03:18 UTC

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

Xiangrui Meng created SPARK-13590:
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             Summary: 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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