org.apache.spark.mllib.optimization

SquaredL2Updater

class SquaredL2Updater extends Updater

:: DeveloperApi :: Updater for L2 regularized problems. R(w) = 1/2 ||w||^2 Uses a step-size decreasing with the square root of the number of iterations.

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@DeveloperApi()
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Updater, Serializable, Serializable, AnyRef, Any
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  1. new SquaredL2Updater()

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  8. def compute(weightsOld: Vector, gradient: Vector, stepSize: Double, iter: Int, regParam: Double): (Vector, 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 regParam * R(w) computed using the *updated* weights.

    weightsOld

    - Column matrix of size dx1 where d is the number of features.

    gradient

    - Column matrix of size dx1 where d 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
    SquaredL2Updater → Updater

  9. final def eq(arg0: AnyRef): Boolean

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