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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 Classifiers that are based on SequenceScores. 
de.jstacs.motifDiscovery This package provides the framework including the interface for any de novo motif discoverer 
de.jstacs.sequenceScores.statisticalModels.trainable Provides all TrainableStatisticalModels, 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 TerminationConditions 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., $|f(\underline{x}_{i-1}) - f(\underline{x}_i)| < \epsilon$.
 class SmallGradientConditon
          This class implements a TerminationCondition that allows no further iteration in an optimization if the the gradient becomes small, i.e., $\sum_i \left|\frac{\partial f(\underline{x})}{\partial x_i}\right| < \epsilon$.
 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., $(\underline{x}_i-\underline{x}_{i-1})^T (\underline{x}_i-\underline{x}_{i-1}) < \epsilon$.
 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 TerminationConditions 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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