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  1. Spark
  2. SPARK-7085

Inconsistent default miniBatchFraction parameters in the train methods of RidgeRegression

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Details

    • Bug
    • Status: Resolved
    • Minor
    • Resolution: Fixed
    • 1.3.1
    • 1.4.0
    • MLlib
    • None

    Description

      The miniBatchFraction parameter in the train method called with 4 arguments is 0.01, that is,

      RidgeRegression.scala
      def train(
            input: RDD[LabeledPoint],
            numIterations: Int,
            stepSize: Double,
            regParam: Double): RidgeRegressionModel = {
          train(input, numIterations, stepSize, regParam, 0.01)
        }
      

      but, the parameter is 1.0 in the other train methods. For example,

      RidgeRegression.scala
        def train(
            input: RDD[LabeledPoint],
            numIterations: Int): RidgeRegressionModel = {
          train(input, numIterations, 1.0, 0.01, 1.0)
        }
      

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            Kuromatsu kuromt
            Kuromatsu kuromt
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              Updated:
              Resolved:

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