org.apache.spark.mllib.optimization

Class SimpleUpdater

Object

org.apache.spark.mllib.optimization.Updater

org.apache.spark.mllib.optimization.SimpleUpdater

All Implemented Interfaces:

java.io.Serializable

public class SimpleUpdater
extends Updater

:: DeveloperApi :: A simple updater for gradient descent *without* any regularization. Uses a step-size decreasing with the square root of the number of iterations.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
SimpleUpdater()

Method Summary

Modifier and Type	Method and Description
scala.Tuple2<Vector,Object>	compute(Vector weightsOld, Vector gradient, double stepSize, int iter, double regParam) Compute an updated value for weights given the gradient, stepSize, iteration number and regularization parameter.

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SimpleUpdater

public SimpleUpdater()

Method Detail

compute

public scala.Tuple2<Vector,Object> compute(Vector weightsOld,
                                           Vector gradient,
                                           double stepSize,
                                           int iter,
                                           double regParam)

Description copied from class: Updater

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.

Specified by:

compute in class Updater

Parameters:

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.