Package org.apache.spark.mllib.optimization


package org.apache.spark.mllib.optimization
  • Class
    Description
    Class used to compute the gradient for a loss function, given a single data point.
    Class used to solve an optimization problem using Gradient Descent.
    Compute gradient and loss for a Hinge loss function, as used in SVM binary classification.
    Updater for L1 regularized problems.
    Class used to solve an optimization problem using Limited-memory BFGS.
    Compute gradient and loss for a Least-squared loss function, as used in linear regression.
    Compute gradient and loss for a multinomial logistic loss function, as used in multi-class classification (it is also used in binary logistic regression).
    Object used to solve nonnegative least squares problems using a modified projected gradient method.
     
    Trait for optimization problem solvers.
    A simple updater for gradient descent *without* any regularization.
    Updater for L2 regularized problems.
    Class used to perform steps (weight update) using Gradient Descent methods.