org.apache.spark.mllib.optimization

SimpleUpdater

class SimpleUpdater extends Updater

A simple updater that adaptively adjusts the learning rate the square root of the number of iterations. Does not perform any regularization.

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Updater, Serializable, Serializable, AnyRef, Any
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  1. new SimpleUpdater()

Value Members

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  8. 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.

    Definition Classes
    SimpleUpdaterUpdater
  9. final def eq(arg0: AnyRef): Boolean

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Inherited from Updater

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