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## Uses of Class
de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition

Packages that use AbstractTerminationCondition
de.jstacs.algorithms.optimization.termination | Provides classes for termination conditions that can be used in algorithms
de.jstacs.classifiers.differentiableSequenceScoreBased | Provides the classes for `Classifier`s that are based on `SequenceScore`s.
de.jstacs.motifDiscovery | This package provides the framework including the interface for any de novo motif discoverer
de.jstacs.sequenceScores.statisticalModels.trainable | Provides all `TrainableStatisticalModel`s, which can be learned from a single `DataSet`.
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training | The package provides all classes used to determine the training algorithm of a hidden Markov model

Uses of AbstractTerminationCondition in de.jstacs.algorithms.optimization.termination

Subclasses of AbstractTerminationCondition in de.jstacs.algorithms.optimization.termination
`class` | `AbsoluteValueCondition` Deprecated. use of the absolute value condition is not recommended and it may be removed in future releases
`class` | `CombinedCondition` This class allows to use many `TerminationCondition`s at once.
`class` | `IterationCondition` This class will stop an optimization if the number of iteration reaches a given number.
`class` | `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., .
`class` | `SmallGradientConditon` This class implements a `TerminationCondition` that allows no further iteration in an optimization if the the gradient becomes small, i.e., .
`class` | `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., .
`class` | `TimeCondition` This class implements a `TerminationCondition` that stops the optimization if the elapsed time in seconds is greater than a given value.

Methods in de.jstacs.algorithms.optimization.termination that return AbstractTerminationCondition
`AbstractTerminationCondition` | `AbstractTerminationCondition.clone()`

Constructors in de.jstacs.algorithms.optimization.termination with parameters of type AbstractTerminationCondition
`CombinedCondition.CombinedConditionParameterSet(int threshold, AbstractTerminationCondition[] condition)` This constructor creates a filled instance of a parameters set.
`CombinedCondition(int threshold, AbstractTerminationCondition... condition)` This constructor creates an instance that allows to use many `TerminationCondition`s at once.

Constructor parameters in de.jstacs.algorithms.optimization.termination with type arguments of type AbstractTerminationCondition
`AbstractTerminationCondition.AbstractTerminationConditionParameterSet(Class<? extends AbstractTerminationCondition> instanceClass)` Constructs an `AbstractTerminationCondition.AbstractTerminationConditionParameterSet` from the class that can be instantiated using this `AbstractTerminationCondition.AbstractTerminationConditionParameterSet`.

Uses of AbstractTerminationCondition in de.jstacs.classifiers.differentiableSequenceScoreBased

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased that return AbstractTerminationCondition
`AbstractTerminationCondition` | `ScoreClassifierParameterSet.getTerminantionCondition()` This method returns the `AbstractTerminationCondition` for stopping the training, e.g., if the difference of the scores between two iterations is smaller than a given threshold the training is stopped.

Constructors in de.jstacs.classifiers.differentiableSequenceScoreBased with parameters of type AbstractTerminationCondition
`ScoreClassifierParameterSet(Class<? extends ScoreClassifier> instanceClass, AlphabetContainer alphabet, int length, byte algo, AbstractTerminationCondition tc, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind)` The constructor for a simple, instantiated parameter set.

Uses of AbstractTerminationCondition in de.jstacs.motifDiscovery

Methods in de.jstacs.motifDiscovery with parameters of type AbstractTerminationCondition
`static double[][]` | `MutableMotifDiscovererToolbox.optimize(DifferentiableSequenceScore[] funs, DiffSSBasedOptimizableFunction opt, byte algorithm, AbstractTerminationCondition condition, double linEps, StartDistanceForecaster startDistance, SafeOutputStream out, boolean breakOnChanged, History[][] hist, int[][] minimalNewLength, OptimizableFunction.KindOfParameter plugIn, boolean maxPos)` This method tries to optimize the problem at hand as good as possible.
`static double[][]` | `MutableMotifDiscovererToolbox.optimize(DifferentiableSequenceScore[] funs, DiffSSBasedOptimizableFunction opt, byte algorithm, AbstractTerminationCondition condition, double linEps, StartDistanceForecaster startDistance, SafeOutputStream out, boolean breakOnChanged, History template, OptimizableFunction.KindOfParameter plugIn, boolean maxPos)` This method tries to optimize the problem at hand as good as possible.

Uses of AbstractTerminationCondition in de.jstacs.sequenceScores.statisticalModels.trainable

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable with parameters of type AbstractTerminationCondition
`DifferentiableStatisticalModelWrapperTrainSM(DifferentiableStatisticalModel nsf, int threads, byte algo, AbstractTerminationCondition tc, double lineps, double startD)` The main constructor that creates an instance with the user given parameters.

Uses of AbstractTerminationCondition in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training that return AbstractTerminationCondition
`AbstractTerminationCondition` | `MaxHMMTrainingParameterSet.getTerminationCondition()` This method returns the `AbstractTerminationCondition` for stopping the training, e.g., if the difference of the scores between two iterations is smaller than a given threshold the training is stopped.

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training with parameters of type AbstractTerminationCondition
`BaumWelchParameterSet(int starts, AbstractTerminationCondition tc, int threads)` This constructor can be used to create an instance with specified parameters.
`MaxHMMTrainingParameterSet(int starts, AbstractTerminationCondition tc)` This constructor can be used to create an instance with specified parameters.
`MultiThreadedTrainingParameterSet(int starts, AbstractTerminationCondition tc, int threads)` This constructor can be used to create an instance with specified parameters.
`NumericalHMMTrainingParameterSet(int starts, AbstractTerminationCondition tc, int threads, byte algorithm, double lineEps, double startDist)` This constructor can be used to create an instance with specified parameters.
`ViterbiParameterSet(int starts, AbstractTerminationCondition tc, int threads)` This constructor can be used to create an instance with specified parameters.

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