Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/15211
You have a good point about setting user expectations about speed and
scalability. I don't think that the average user needs to understand the
underlying implementation, but performance expectations are important. Let's
go with what you have (LinearSVC).
Side note: If we wanted to match libsvm/liblinear, then we would not add a
new class but would just add hinge loss support to GeneralizedLinearRegression.
I hesitate to do that since GLMs technically require natural exponential
families and adding hinge loss would make it harder to explain algorithm
behavior (such as which evaluation stats are available).
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