org.apache.spark.mllib

optimization

package optimization

Visibility
  1. Public
  2. All

Type Members

  1. abstract class Gradient extends Serializable

    Class used to compute the gradient for a loss function, given a single data point.

  2. class GradientDescent extends Optimizer with Logging

    Class used to solve an optimization problem using Gradient Descent.

  3. class HingeGradient extends Gradient

    Compute gradient and loss for a Hinge loss function.

  4. class L1Updater extends Updater

    Updater that adjusts learning rate and performs L1 regularization.

  5. class LogisticGradient extends Gradient

    Compute gradient and loss for a logistic loss function.

  6. trait Optimizer extends AnyRef

  7. class SimpleUpdater extends Updater

    A simple updater that adaptively adjusts the learning rate the square root of the number of iterations.

  8. class SquaredGradient extends Gradient

    Compute gradient and loss for a Least-squared loss function.

  9. class SquaredL2Updater extends Updater

    Updater that adjusts the learning rate and performs L2 regularization

  10. abstract class Updater extends Serializable

    Class used to update weights used in Gradient Descent.

Value Members

  1. object GradientDescent extends Logging

Ungrouped