Github user sethah commented on a diff in the pull request: https://github.com/apache/spark/pull/13796#discussion_r67802848 --- Diff: mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala --- @@ -1077,58 +1201,53 @@ private class LogisticCostFun( fitIntercept: Boolean, standardization: Boolean, featuresStd: Array[Double], - featuresMean: Array[Double], - regParamL2: Double) extends DiffFunction[BDV[Double]] { + regParamL2: Double, + multinomial: Boolean, + standardize: Boolean) extends DiffFunction[BDV[Double]] { override def calculate(coefficients: BDV[Double]): (Double, BDV[Double]) = { - val numFeatures = featuresStd.length val coeffs = Vectors.fromBreeze(coefficients) - val n = coeffs.size + val bcCoeffs = instances.context.broadcast(coeffs) --- End diff -- I noticed some (somewhat modest) performance gains when explicitly broadcasting the coefficients when the number of coefficients was large.
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