class SimpleUpdater extends Updater
A simple updater for gradient descent *without* any regularization. Uses a step-size decreasing with the square root of the number of iterations.
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- Updater.scala
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- 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.
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(Since version 9)