org.apache.spark.mllib.optimization

Updater

abstract class Updater extends Serializable

Class used to update weights used in Gradient Descent.

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Known Subclasses
L1Updater, SimpleUpdater, SquaredL2Updater
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  1. Updater
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  1. new Updater()

Abstract Value Members

  1. abstract def compute(weightsOld: DoubleMatrix, gradient: DoubleMatrix, stepSize: Double, iter: Int, regParam: Double): (DoubleMatrix, Double)

    Compute an updated value for weights given the gradient, stepSize, iteration number and regularization parameter.

    Compute an updated value for weights given the gradient, stepSize, iteration number and regularization parameter. Also returns the regularization value computed using the *updated* weights.

    weightsOld

    - Column matrix of size nx1 where n is the number of features.

    gradient

    - Column matrix of size nx1 where n is the number of features.

    stepSize

    - step size across iterations

    iter

    - Iteration number

    regParam

    - Regularization parameter

    returns

    A tuple of 2 elements. The first element is a column matrix containing updated weights, and the second element is the regularization value computed using updated weights.

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