Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/18305#discussion_r125026593
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/optim/loss/RDDLossFunction.scala ---
@@ -62,8 +62,8 @@ private[ml] class RDDLossFunction[
val newAgg = instances.treeAggregate(thisAgg)(seqOp, combOp,
aggregationDepth)
val gradient = newAgg.gradient
val regLoss = regularization.map { regFun =>
- val (regLoss, regGradient) = regFun.calculate(coefficients.data)
- BLAS.axpy(1.0, Vectors.dense(regGradient), gradient)
+ val (regLoss, regGradient) =
regFun.calculate(Vectors.fromBreeze(coefficients))
--- End diff --
Yeah, more or less - see how Breeze does L2 reg in
`DiffFunction.withL2Regularization`
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