Github user sethah commented on a diff in the pull request: https://github.com/apache/spark/pull/13796#discussion_r74832879 --- Diff: mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala --- @@ -930,10 +942,8 @@ class BinaryLogisticRegressionSummary private[classification] ( } /** - * LogisticAggregator computes the gradient and loss for binary logistic loss function, as used - * in binary classification for instances in sparse or dense vector in an online fashion. - * - * Note that multinomial logistic loss is not supported yet! + * LogisticAggregator computes the gradient and loss for binary or multinomial logistic loss --- End diff -- I agree we have a lot of code in a single file, though linear regression suffers from the same problem. I don't feel too strongly one way or the other. Do you have a specific package location in mind?
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