Github user sethah commented on the issue:
https://github.com/apache/spark/pull/13796
Thanks @dbtsai for the detailed review! I addressed most comments. We still
need to:
* Decide whether to handle numClasses being specified in metadata
* Decide what happens when numClasses == 1 (only label 0.0 is encountered)
Also, one thing I'm concerned about is having separate
`MultinomialLogisticRegression` and `LogisticRegression`. Of course, we do this
mainly because we cannot change the LR API to support a matrix of coefficients
very easily. Still, I think it's quite annoying to have to switch to a
different estimator for multiclass. The multinomial estimator more or less
supercedes the functionality of BLOR, but `LogisticRegression` is a canonical
name and users may gravitate to it. Further, even when/if people realize that
you can use MLOR for both binary and multiclass, it may be confusing what
`LogisticRegression` is used for. I just want to discuss it before we make it
public.
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