Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/6761#issuecomment-112948888
@acidghost Thanks for the updated PR! I'll try to make a closer pass soon.
In the meantime, unit tests do sound great. I think one of the best ways to
test correctness would be to compare with another library (ideally R or
sklearn) on a tiny dataset. See e.g. the test for LogisticRegression:
[https://github.com/apache/spark/blob/0fc4b96f3e3bf81724ac133a6acc97c1b77271b4/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala]
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