[GitHub] spark pull request: [SPARK-6580] [MLLIB] Optimize LogisticRegressi...

[yanboliang <gi...@git.apache.org>]

Github user yanboliang commented on a diff in the pull request:

    https://github.com/apache/spark/pull/5249#discussion_r27545988
  
    --- Diff: mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala ---
    @@ -145,13 +135,20 @@ class LogisticRegressionModel (
            */
           var bestClass = 0
           var maxMargin = 0.0
    -      var i = 0
    -      while(i < margins.size) {
    -        if (margins(i) > maxMargin) {
    -          maxMargin = margins(i)
    +      val withBias = if (dataMatrix.size + 1 == dataWithBiasSize) true else false
    +      (0 until numClasses - 1).map { i =>
    +        var margin = 0.0
    +        dataMatrix.foreachActive { (index, value) =>
    +          if (value != 0.0) margin += value * weightsArray((i * dataWithBiasSize) + index)
    --- End diff --
    
    @srowen  Thank you for your comments. I'm not sure that it will make a measurable difference, what I made for this PR is just want to clean code and reduce redundant. This optimization is inspired by #5137 which implements the prediction for Python API and it concerned mainly on code clean rather than performance issue.
    I agree the real optimization may be not computing the weights array every time  prediction is made,  but just like you said it seems like small improvements. I think we should resolve it when we encounter some performance issues and file another ticket.
     


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