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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