Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/15593#discussion_r86421340
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -1486,57 +1489,75 @@ private class LogisticAggregator(
var marginOfLabel = 0.0
var maxMargin = Double.NegativeInfinity
- val margins = Array.tabulate(numClasses) { i =>
- var margin = 0.0
- features.foreachActive { (index, value) =>
- if (localFeaturesStd(index) != 0.0 && value != 0.0) {
- margin += localCoefficients(i * numFeaturesPlusIntercept +
index) *
- value / localFeaturesStd(index)
- }
+ val margins = new Array[Double](numClasses)
--- End diff --
It may be good to just add a general comment (perhaps in
LogisticAggregator) about the training being done using col major order, and
that this is converted to row major once training is done, etc? And perhaps a
little detail on why it is (was) necessary.
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