de.jstacs.algorithms.optimization.termination

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Interface Summary
Interface Description

TerminationCondition
This interface can be used in any iterative algorithm for determining the end of the algorithm.

Class Summary
Class	Description
AbsoluteValueCondition	Deprecated use of the absolute value condition is not recommended and it may be removed in future releases
AbsoluteValueCondition.AbsoluteValueConditionParameterSet	This class implements the parameter set for a `AbsoluteValueCondition`.
AbstractTerminationCondition	This class is the abstract super class of many `TerminationCondition`s.
AbstractTerminationCondition.AbstractTerminationConditionParameterSet	This class implements the super class of all parameter sets of instances from `AbstractTerminationCondition`.
CombinedCondition	This class allows to use many `TerminationCondition`s at once.
CombinedCondition.CombinedConditionParameterSet	This class implements the parameter set for a `CombinedCondition`.
IterationCondition	This class will stop an optimization if the number of iteration reaches a given number.
IterationCondition.IterationConditionParameterSet	This class implements the parameter set for a `IterationCondition`.
MultipleIterationsCondition	This `TerminationCondition` requires another provided `TerminationCondition` to fail a contiguous specified number of times before the optimization is terminated.
MultipleIterationsCondition.MultipleIterationsConditionParameterSet	This class implements the parameter set for a `MultipleIterationsCondition`.
SmallDifferenceOfFunctionEvaluationsCondition	This class implements a `TerminationCondition` that stops an optimization if the difference of the current and the last function evaluations will be small, i.e., $\|f(\underline{x}_{i-1}) - f(\underline{x}_i)\| < \epsilon$ .
SmallDifferenceOfFunctionEvaluationsCondition.SmallDifferenceOfFunctionEvaluationsConditionParameterSet	This class implements the parameter set for a `SmallDifferenceOfFunctionEvaluationsCondition`.
SmallGradientConditon	This class implements a `TerminationCondition` that allows no further iteration in an optimization if the the gradient becomes small, i.e., $\sum_i \left\|\frac{\partial f(\underline{x})}{\partial x_i}\right\| < \epsilon$ .
SmallGradientConditon.SmallGradientConditonParameterSet	This class implements the parameter set for a `SmallStepCondition`.
SmallStepCondition	This class implements a `TerminationCondition` that allows no further iteration in an optimization if the scalar product of the current and the last values of `x` will be small, i.e., $(\underline{x}_i-\underline{x}_{i-1})^T (\underline{x}_i-\underline{x}_{i-1}) < \epsilon$ .
SmallStepCondition.SmallStepConditionParameterSet	This class implements the parameter set for a `SmallStepCondition`.
TimeCondition	This class implements a `TerminationCondition` that stops the optimization if the elapsed time in seconds is greater than a given value.
TimeCondition.TimeConditionParameterSet	This class implements the parameter set for a `TimeCondition`.

Package de.jstacs.algorithms.optimization.termination Description

Provides classes for termination conditions that can be used in algorithms.

See Also:: Optimizer, AbstractMixtureTrainSM, HigherOrderHMM

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