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Packages that use Optimizer.TerminationCondition | |
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de.jstacs.algorithms.optimization | Provides classes for different types of algorithms that are not directly linked to the modelling components of Jstacs: Algorithms on graphs, algorithms for numerical optimization, and a basic alignment algorithm. |
Uses of Optimizer.TerminationCondition in de.jstacs.algorithms.optimization |
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Methods in de.jstacs.algorithms.optimization that return Optimizer.TerminationCondition | |
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static Optimizer.TerminationCondition |
Optimizer.TerminationCondition.valueOf(String name)
Returns the enum constant of this type with the specified name. |
static Optimizer.TerminationCondition[] |
Optimizer.TerminationCondition.values()
Returns an array containing the constants of this enum type, in the order they're declared. |
Methods in de.jstacs.algorithms.optimization with parameters of type Optimizer.TerminationCondition | |
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static int |
Optimizer.conjugateGradientsFR(DifferentiableFunction f,
double[] currentValues,
Optimizer.TerminationCondition terminationMode,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
Time t)
The conjugate gradient algorithm by Fletcher and Reeves. |
static int |
Optimizer.conjugateGradientsPR(DifferentiableFunction f,
double[] currentValues,
Optimizer.TerminationCondition terminationMode,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
Time t)
The conjugate gradient algorithm by Polak and Ribiere. |
static int |
Optimizer.conjugateGradientsPRP(DifferentiableFunction f,
double[] currentValues,
Optimizer.TerminationCondition terminationMode,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
Time t)
The conjugate gradient algorithm by Polak and Ribiere called Polak-Ribiere-Positive. |
static int |
Optimizer.limitedMemoryBFGS(DifferentiableFunction f,
double[] currentValues,
byte m,
Optimizer.TerminationCondition terminationMode,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
Time t)
The Broyden-Fletcher-Goldfarb-Shanno version of limited memory quasi Newton methods. |
static int |
Optimizer.optimize(byte algorithm,
DifferentiableFunction f,
double[] currentValues,
Optimizer.TerminationCondition terminationMode,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out)
This method enables you to use all different implemented optimization algorithms by only one method. |
static int |
Optimizer.optimize(byte algorithm,
DifferentiableFunction f,
double[] currentValues,
Optimizer.TerminationCondition terminationMode,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
Time t)
This method enables you to use all different implemented optimization algorithms by only one method. |
static int |
Optimizer.quasiNewtonBFGS(DifferentiableFunction f,
double[] currentValues,
Optimizer.TerminationCondition terminationMode,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
Time t)
The Broyden-Fletcher-Goldfarb-Shanno version of quasi Newton method. |
static int |
Optimizer.quasiNewtonDFP(DifferentiableFunction f,
double[] currentValues,
Optimizer.TerminationCondition terminationMode,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
Time t)
The Davidon-Fletcher-Powell version of quasi Newton method. |
static int |
Optimizer.steepestDescent(DifferentiableFunction f,
double[] currentValues,
Optimizer.TerminationCondition terminationMode,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
Time t)
The steepest descent. |
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