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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