Uses of Enum
net.finmath.optimizer.StochasticLevenbergMarquardt.RegularizationMethod
Package
Description
This package provides classes with numerical algorithm for optimization of
an objective function and a factory to easy construction of the optimizers.
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Uses of StochasticLevenbergMarquardt.RegularizationMethod in net.finmath.optimizer
Modifier and TypeMethodDescriptionReturns the enum constant of this type with the specified name.StochasticLevenbergMarquardt.RegularizationMethod.values()
Returns an array containing the constants of this enum type, in the order they are declared.ModifierConstructorDescriptionStochasticLevenbergMarquardt
(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, int numberOfThreads) Create a Levenberg-Marquardt solver.StochasticLevenbergMarquardt
(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService) Create a Levenberg-Marquardt solver.StochasticLevenbergMarquardtAD
(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService) StochasticLevenbergMarquardtAD
(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService, boolean isGradientValuationParallel) StochasticOptimizerFactoryLevenbergMarquardt
(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, int maxIterations, double errorTolerance, int maxThreads)