Package gov.sandia.cognition.learning.algorithm.minimization

Provides minimization algorithms.

See:
          Description

Interface Summary
FunctionMinimizer<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>> Interface for unconstrained minimization of nonlinear functions.
 

Class Summary
AbstractAnytimeFunctionMinimizer<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>> A partial implementation of a minimization algorithm that is iterative, stoppable, and approximate.
FunctionMinimizerBFGS Implementation of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) Quasi-Newton nonlinear minimization algorithm.
FunctionMinimizerConjugateGradient Conjugate gradient method is a class of algorithms for finding the unconstrained local minimum of a nonlinear function.
FunctionMinimizerDFP Implementation of the Davidon-Fletcher-Powell (DFP) formula for a Quasi-Newton minimization update.
FunctionMinimizerDirectionSetPowell Implementation of the derivative-free unconstrained nonlinear direction-set minimization algorithm called "Powell's Method" by Numerical Recipes.
FunctionMinimizerFletcherReeves This is an implementation of the Fletcher-Reeves conjugate gradient minimization procedure.
FunctionMinimizerGradientDescent This is an implementation of the classic Gradient Descent algorithm, also known as Steepest Descent, Backpropagation (for neural nets), or Hill Climbing.
FunctionMinimizerLiuStorey This is an implementation of the Liu-Storey conjugate gradient minimization procedure.
FunctionMinimizerNelderMead Implementation of the Downhill Simplex minimization algorithm, also known as the Nelder-Mead method.
FunctionMinimizerPolakRibiere This is an implementation of the Polack-Ribiere conjugate gradient minimization procedure.
FunctionMinimizerQuasiNewton This is an abstract implementation of the Quasi-Newton minimization method, sometimes called "Variable-Metric methods." This family of minimization algorithms uses first-order gradient information to find a locally minimum to a scalar function.
MinimizationStoppingCriterion Implementation of almost zero-gradient convergence test for function minimizers.
 

Package gov.sandia.cognition.learning.algorithm.minimization Description

Provides minimization algorithms.

Since:
2.0
Author:
Justin Basilico