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hasAnySelfTransitions() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
hasAnySelfTransitions() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method answers the question whether the instance models any self transitions.
hasBeenOptimized - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
This boolean indicates whether the classifier has been optimized with the method AbstractClassifier.train(DataSet[]) or the weighted version.
hasBeenOptimized() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
This method indicates if the classifier has been optimized by a train-method.
hasDefault() - Method in class de.jstacs.parameters.AbstractSelectionParameter
Returns true, if this AbstractSelectionParameter has a default value.
hasDefault() - Method in class de.jstacs.parameters.MultiSelectionParameter
 
hasDefault() - Method in class de.jstacs.parameters.SelectionParameter
Returns true, if this SelectionParameter has a default value.
hasDefaultOrIsSet() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
 
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ArrayParameterSet
 
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.FileParameter
 
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.MultiSelectionParameter
 
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.Parameter
Returns true if the parameter either has a default value or the value was set by the user, false otherwise.
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ParameterSet
Returns true if all parameters in this ParameterSet are either set by the user or have default values.
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ParameterSetContainer
 
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ParameterSetTagger
This method allows to check whether all tagged parameters that require a value also have some value.
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.RangeParameter
 
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.SelectionParameter
 
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.SequenceScoringParameterSet
 
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.SimpleParameter
 
hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DGTrainSMParameterSet
 
hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet
 
hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.BaumWelchParameterSet
 
hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.ViterbiParameterSet
 
hashCode() - Method in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotation
 
hashCode() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
 
hashCode() - Method in class de.jstacs.data.sequences.Sequence
 
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
 
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.CyclicSequenceAdaptor
 
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
 
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.Sequence
This method is used in Sequence.hashCode() and the hash code for one specific position.
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
 
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
 
hasMoreElements() - Method in class de.jstacs.data.DataSet.ElementEnumerator
 
hasMoreElements() - Method in class de.jstacs.data.DataSetKMerEnumerator
 
hasMoreElements() - Method in class de.jstacs.data.DiscreteSequenceEnumerator
 
hasMoreElements() - Method in class de.jstacs.data.SequenceEnumeration
 
hasMoreElements() - Method in class de.jstacs.io.InfixStringExtractor
 
hasMoreElements() - Method in class de.jstacs.io.LimitedStringExtractor
 
hasMoreElements() - Method in class de.jstacs.io.SimpleStringExtractor
 
hasMoreElements() - Method in class de.jstacs.io.SparseStringExtractor
 
hasMoreElements() - Method in class de.jstacs.io.StringExtractor
 
hasMoreElements() - Method in class de.jstacs.io.SymbolExtractor
 
hasNext() - Method in class de.jstacs.data.bioJava.SimpleSequenceIterator
 
hasNext() - Method in class de.jstacs.data.DataSet.ElementEnumerator
 
hasSampled - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
This boolean indicates if the parameters for the model were sampled
hasTag(StringBuffer, String, Map<String, String>, Map<String, String>) - Static method in class de.jstacs.io.XMLParser
This method allows to check whether an XML contains a tagged entry.
Hclust<T> - Class in de.jstacs.clustering.hierachical
Class for clustering a set of elements of the same kind (T) hierarchically using agglomerative clustering with different linkage methods.
Hclust(DistanceMetric<T>, Hclust.Linkage) - Constructor for class de.jstacs.clustering.hierachical.Hclust
Creates a new object for clustering using the supplied distance metric and linkage method.
Hclust.Linkage - Enum in de.jstacs.clustering.hierachical
The linkage method for clustering
HeadResult(String, String) - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.HeadResult
Creates a new head result with given name and comment
helpArray - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LogGenDisMixFunction
General temporary array
HiddenMotifMixture - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif
This is the main class that every generative motif discoverer should implement.
HiddenMotifMixture(TrainableStatisticalModel[], boolean[], int, int, boolean, double[], double[], PositionPrior, AbstractMixtureTrainSM.Algorithm, double, TerminationCondition, AbstractMixtureTrainSM.Parameterization, int, int, BurnInTest) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
Creates a new HiddenMotifMixture.
HiddenMotifMixture(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
The standard constructor for the interface Storable.
hiddenParameter - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
This array contains the hidden parameters of the instance.
hiddenPotential - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
This array contains the hidden potentials of the instance.
HigherOrderHMM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models
This class implements a higher order hidden Markov model.
HigherOrderHMM(HMMTrainingParameterSet, String[], Emission[], BasicHigherOrderTransition.AbstractTransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
This is a convenience constructor.
HigherOrderHMM(HMMTrainingParameterSet, String[], int[], boolean[], Emission[], BasicHigherOrderTransition.AbstractTransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
This is the main constructor.
HigherOrderHMM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
The standard constructor for the interface Storable.
HigherOrderHMM.Type - Enum in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models
This enum defined different types of computations that will be done using the backward algorithm.
HigherOrderTransition - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions
This class can be used in any AbstractHMM allowing to use gradient based or sampling training algorithm.
HigherOrderTransition(boolean[], TransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
The main constructor.
HigherOrderTransition(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
The standard constructor for the interface Storable.
History - Interface in de.jstacs.motifDiscovery.history
This interface is used to manage the history of some process.
HMMFactory - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm
This class allows to create some frequently used HMMs.
HMMFactory() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory
 
HMMFactory.HMMType - Enum in de.jstacs.sequenceScores.statisticalModels.trainable.hmm
This enum defines some standard architecture of profile HMMs.
HMMFactory.PseudoTransitionElement - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm
This class is used as place holder for a later BasicHigherOrderTransition.AbstractTransitionElement.
HMMTrainingParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training
This class implements an abstract ParameterSet that is used for the training of an AbstractHMM.
HMMTrainingParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet
This is the empty constructor that can be used to fill the parameters after creation.
HMMTrainingParameterSet(int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet
This constructor can be used to create an instance with a specified number of starts.
HMMTrainingParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet
The standard constructor for the interface Storable.
HomCondProb(int[], int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
The main constructor.
HomCondProb(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
The standard constructor for the interface Storable .
HomCondProb(HomogeneousTrainSM.HomCondProb) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
Creates a new HomogeneousTrainSM.HomCondProb instance from a given one.
HomMMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters
This class implements a container for all parameters of a homogeneous Markov model.
HomMMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet
The standard constructor for the interface Storable.
HomMMParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet
An empty constructor.
HomMMParameterSet(AlphabetContainer, double, String, byte) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet
Creates a new HomMMParameterSet with AlphabetContainer, ess (equivalent sample size), description and order of the homogeneous Markov model.
HomogeneousDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
This is the main class for all homogeneous DifferentiableSequenceScores.
HomogeneousDiffSM(AlphabetContainer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM
This is the main constructor that creates an instance of a HomogeneousDiffSM that models sequences of arbitrary length.
HomogeneousDiffSM(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM
This is the main constructor that creates an instance of a HomogeneousDiffSM that models sequences of a given length.
HomogeneousDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM
This is the constructor for Storable.
HomogeneousMM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous
This class implements homogeneous Markov models (hMM) of arbitrary order.
HomogeneousMM(HomMMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
Creates a new homogeneous Markov model from a parameter set.
HomogeneousMM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
The standard constructor for the interface Storable.
HomogeneousMM0DiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.
HomogeneousMM0DiffSM(AlphabetContainer, int, double, boolean, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
The main constructor that creates an instance of a homogeneous Markov model of order 0.
HomogeneousMM0DiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
This is the constructor for Storable.
HomogeneousMMDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.
HomogeneousMMDiffSM(AlphabetContainer, int, double, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
This is a convenience constructor for creating an instance of a homogeneous Markov model of arbitrary order.
HomogeneousMMDiffSM(AlphabetContainer, int, double, double[], boolean, boolean, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
This is the main constructor that creates an instance of a homogeneous Markov model of arbitrary order.
HomogeneousMMDiffSM(AlphabetContainer, int, double, double[][], boolean, boolean, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
This is the main constructor that creates an instance of a homogeneous Markov model of arbitrary order with given hyper-parameters for the prior.
HomogeneousMMDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
This is the constructor for Storable.
HomogeneousTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous
This class implements homogeneous models of arbitrary order.
HomogeneousTrainSM(HomogeneousTrainSMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
Creates a homogeneous model from a parameter set.
HomogeneousTrainSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
The standard constructor for the interface Storable.
HomogeneousTrainSM.HomCondProb - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous
This class handles the (conditional) probabilities of a homogeneous model in a fast way.
HomogeneousTrainSMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters
This class implements a container for all parameters of any homogeneous model.
HomogeneousTrainSMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet
The standard constructor for the interface Storable.
HomogeneousTrainSMParameterSet(Class<? extends HomogeneousTrainSM>) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet
This is the constructor that creates an empty HomogeneousTrainSMParameterSet from the class that can be instantiated using this HomogeneousTrainSMParameterSet.
HomogeneousTrainSMParameterSet(Class<? extends HomogeneousTrainSM>, AlphabetContainer, double, String, byte) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet
Creates a new HomogeneousTrainSMParameterSet with AlphabetContainer, ess (equivalent sample size), description and order of the homogeneous Markov model.
hyperParameters - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
The hyperparameters of the prior over the parameters.
hyperParams - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
The hyper-parameters for the prior on the parameters
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