A B C D E F G H I K L M N O P Q R S T U V W X

S

SafeOutputStream - Class in de.jstacs.utils
This class is for any output.
SafeOutputStream(OutputStream) - Constructor for class de.jstacs.utils.SafeOutputStream
Creates a new SafeOutputstream
sameLength() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
 
Sample - Class in de.jstacs.data
This is the class for any sample of sequences.
Sample(AlphabetContainer, StringExtractor) - Constructor for class de.jstacs.data.Sample
Creates a Sample from a StringExctractor using the given AlphabetContainer.
Sample(AlphabetContainer, StringExtractor, int) - Constructor for class de.jstacs.data.Sample
Creates a Sample from a StringExctractor using the given AlphabetContainer and all overlapping windows of subsequenceLength.
Sample(AlphabetContainer, StringExtractor, String) - Constructor for class de.jstacs.data.Sample
Creates a Sample from a StringExctractor using the given AlphabetContainer and delimiter.
Sample(AlphabetContainer, StringExtractor, String, int) - Constructor for class de.jstacs.data.Sample
Creates a Sample from a StringExctractor using the given AlphabetContainer, the given delimiter and all overlapping windows of subsequenceLength.
Sample(Sample, int) - Constructor for class de.jstacs.data.Sample
This constructor enables you to use subsequences of the elements of a sample.
Sample(String, Sequence...) - Constructor for class de.jstacs.data.Sample
This constructor is specially designed for the method Model.emitSample(int, int...).
sample - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The sample that was used in the last training.
Sample.ElementEnumerator - Class in de.jstacs.data
This class can be used to have a fast sequential access to a sample.
Sample.ElementEnumerator(Sample) - Constructor for class de.jstacs.data.Sample.ElementEnumerator
This constructor creates an new ElementEnumerator on the given data
Sample.PartitionMethod - Enum in de.jstacs.data
This enum defines different partition method for a sample.
Sample.WeightedSampleFactory - Class in de.jstacs.data
This class enables you to eliminate sequences that occur more than once in one or more samples.
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation, Sample...) - Constructor for class de.jstacs.data.Sample.WeightedSampleFactory
This constructor creates a Sample.WeightedSampleFactory on the given Sample(s).
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation, Sample, double[]) - Constructor for class de.jstacs.data.Sample.WeightedSampleFactory
This constructor creates a Sample.WeightedSampleFactory on the given Sample and weights.
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation, Sample, double[], int) - Constructor for class de.jstacs.data.Sample.WeightedSampleFactory
This constructor creates a Sample.WeightedSampleFactory on the given Sample and weights.
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation, Sample[], double[][], int) - Constructor for class de.jstacs.data.Sample.WeightedSampleFactory
This constructor creates a Sample.WeightedSampleFactory on the given array of Samples and weights.
Sample.WeightedSampleFactory.SortOperation - Enum in de.jstacs.data
This enum defines the different types of sort operation that can be performed while creating a Sample.WeightedSampleFactory.
Sampled_RepeatedHoldOutAssessParameterSet - Class in de.jstacs.classifier.assessment
 
Sampled_RepeatedHoldOutAssessParameterSet(Class) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
inherited from ClassifierAssessmentAssessParameterSet
Sampled_RepeatedHoldOutAssessParameterSet() - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
inherited from ClassifierAssessmentAssessParameterSet
Sampled_RepeatedHoldOutAssessParameterSet(StringBuffer) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
inherited from ClassifierAssessmentAssessParameterSet
Sampled_RepeatedHoldOutAssessParameterSet(Sample.PartitionMethod, int, boolean, int, int, double, boolean) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
 
Sampled_RepeatedHoldOutExperiment - Class in de.jstacs.classifier.assessment
This class is a special ClassifierAssessment that partitions the data of a reference class and samples non-overlapping for the other classes, so that one get the same number of sequences and the same lengths of the sequences.
Sampled_RepeatedHoldOutExperiment(AbstractClassifier[], Model[][], boolean, boolean) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutExperiment
Creates a new Sampled_RepeatedHoldOutExperiment from an array of AbstractClassifiers and a two-dimensional array of Models, which are combined to additional classifiers.
Sampled_RepeatedHoldOutExperiment(AbstractClassifier...) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutExperiment
Creates a new Sampled_RepeatedHoldOutExperiment from a set of AbstractClassifiers.
Sampled_RepeatedHoldOutExperiment(boolean, Model[]...) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutExperiment
Creates a new Sampled_RepeatedHoldOutExperiment from a set of Models.
Sampled_RepeatedHoldOutExperiment(AbstractClassifier[], boolean, Model[]...) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutExperiment
This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given AbstractModels by a Sampled_RepeatedHoldOutExperiment.
SampleResult - Class in de.jstacs.results
Result that contains a Sample.
SampleResult(String, String, Sample) - Constructor for class de.jstacs.results.SampleResult
Creates a new SampleResult from a Sample with the annotation name and comment.
SampleResult(StringBuffer) - Constructor for class de.jstacs.results.SampleResult
Re-creates a SampleResult from its XML-representation as returned by SampleResult.toXML().
sampleToSequenceIterator(Sample, boolean) - Static method in class de.jstacs.data.bioJava.BioJavaAdapter
Creates a SequenceIterator from sample preserving as much annotation as possible.
samplingIndex - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The current index of the sampling
samplingIndex - Variable in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
The index of the current sampling.
samplingStopped() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method is the opposite of the method initModelForSampling.
samplingStopped() - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
 
samplingStopped() - Method in interface de.jstacs.models.mixture.gibbssampling.GibbsSamplingComponent
This method is the opposite of the method GibbsSamplingComponent.extendSampling(int, boolean).
satisfiesSpecificConstraint(Sequence, int) - Method in class de.jstacs.models.discrete.Constraint
This method returns the index of the specific constraint that is fullfilled by the sequence beginning at start.
satisfiesSpecificConstraint(Sequence, int) - Method in class de.jstacs.models.discrete.inhomogeneous.InhConstraint
 
satisfiesSpecificConstraint(SequenceIterator) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Returns the index of that constraint that is satiesfied by sequence
save(String, File) - Method in class de.jstacs.data.Sample
This method writes a message msg and the sample to a file f
score - Variable in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
The internally used scoring functions.
ScoreBasedPerformanceMeasureDefinitions - Class in de.jstacs.classifier
This class contains the methods that are needed to evaluate a score based 2-class-classifier.
ScoreBasedPerformanceMeasureDefinitions() - Constructor for class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
 
ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair - Class in de.jstacs.classifier
This class is used as a container that allows to store a threshold and the result of measure together.
ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair(double, double) - Constructor for class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair
This is the constructor that creates a filled instance.
ScoreClassifier - Class in de.jstacs.classifier.scoringFunctionBased
 
ScoreClassifier(ScoreClassifierParameterSet, ScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
The default constructor.
ScoreClassifier(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
This is the constructor for Storable.
ScoreClassifierParameterSet - Class in de.jstacs.classifier.scoringFunctionBased
The parameter set for any CL classifier.
ScoreClassifierParameterSet(boolean, boolean) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet
The default constructor.
ScoreClassifierParameterSet(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet
This is the constructor for Storable.
ScoreClassifierParameterSet(AlphabetContainer, int, byte, double, double, double, boolean, boolean) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet
The constructor for a simple, instantiated parameter set.
ScoringFunction - Interface in de.jstacs.scoringFunctions
This interface is the main part of any ScoreClassifier.
SeparateGaussianLogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
Class for a LogPrior that defines a Gaussian prior on the parameters of a set of NormalizableScoringFunctions and a set of class-parameters.
SeparateGaussianLogPrior(double[], double[], double[]) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateGaussianLogPrior
Creates a new SeparateGaussianLogPrior from a set of base variances vars, a set of class-variances classVars, and a set of class-means classMus.
SeparateGaussianLogPrior(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateGaussianLogPrior
Re-creates a SeparateGaussianLogPrior from its XML-representation as returned by SeparateLogPrior.toXML().
SeparateLaplaceLogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
Class for a LogPrior that defines a Laplace-prior on the parameters of a set of NormalizableScoringFunctions and a set of class-parameters.
SeparateLaplaceLogPrior(double[], double[], double[]) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLaplaceLogPrior
Creates a new SeparateLaplaceLogPrior from a set of base variances vars, a set of class-variances classVars, and a set of class-means classMus.
SeparateLaplaceLogPrior(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLaplaceLogPrior
Re-creates a SeparateLaplaceLogPrior from its XML-representation as returned by SeparateLogPrior.toXML().
SeparateLogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
Abstract class for priors that penalize each parameter value independently and have some variance (and possible mean) as hyper-parameters.
SeparateLogPrior(double[], double[], double[]) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior
Creates a new SeparateLogPrior using the class-specific base variances vars, the variances classVars and the means classMus for the class parameters.
SeparateLogPrior(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior
Re-creates a SeparateLogPrior from its XML-representation as returned by SeparateLogPrior.toXML().
Sequence - Class in de.jstacs.data
This is the main class for all sequences.
Sequence(AlphabetContainer, SequenceAnnotation[]) - Constructor for class de.jstacs.data.Sequence
This constructor creates an instance with the AlphabetContainer and the annotation, but without the content.
Sequence.CompositeSequence - Class in de.jstacs.data
The class handles composite sequences.
Sequence.CompositeSequence(Sequence, int[], int[]) - Constructor for class de.jstacs.data.Sequence.CompositeSequence
This is an very effient way to create a composite sequence for sequences with a simple AlphabetContainer.
Sequence.CompositeSequence(AlphabetContainer, Sequence, int[], int[]) - Constructor for class de.jstacs.data.Sequence.CompositeSequence
This constructor should be used if one wants to create a sample of composite sequences.
Sequence.SubSequence - Class in de.jstacs.data
This class handles subsequences.
Sequence.SubSequence(AlphabetContainer, Sequence, int, int) - Constructor for class de.jstacs.data.Sequence.SubSequence
This constructor should be used if one wants to create a sample of subsequences of defined length.
Sequence.SubSequence(Sequence, int, int) - Constructor for class de.jstacs.data.Sequence.SubSequence
This is an very efficient way to create a subsequence of defined length for sequences with a simple AlphabetContainer.
SequenceAnnotation - Class in de.jstacs.data.sequences.annotation
Class for a general annotation of a Sequence.
SequenceAnnotation(String, String, Result) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
Creates a new SequenceAnnotation of type type, with identifier identifier, and additional annotation (that does not fit the SequenceAnnotation definitions) result.
SequenceAnnotation(String, String, Result[]...) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
Creates a new SequenceAnnotation of type type, with identifier identifier, and additional annotation (that does not fit the SequenceAnnotation definitions) results.
SequenceAnnotation(String, String, SequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
Creates a new SequenceAnnotation of type type, with identifier identifier, and additional annotation (that does not fit the SequenceAnnotation definitions) additionalAnnotation.
SequenceAnnotation(String, String, Collection<? extends Result>) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
Creates a new SequenceAnnotation of type type, with identifier identifier, and additional annotation (that does not fit the SequenceAnnotation definitions) results.
SequenceAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
Re-creates a SequenceAnnotation from its XML-representation as returned by SequenceAnnotation.toXML().
SequenceIterator - Class in de.jstacs.models.discrete.inhomogeneous
This class is used to iterate over a discrete sequence.
SequenceIterator(int) - Constructor for class de.jstacs.models.discrete.inhomogeneous.SequenceIterator
Creates a new SequenceIterator with maximal length.
sequenceIteratorToSample(SequenceIterator, FeatureFilter) - Static method in class de.jstacs.data.bioJava.BioJavaAdapter
This method creates a new Sample from a SequenceIterator.
set(boolean, ScoringFunction...) - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.LogPrior
Resets all pre-computed values to their initial values using the ScoringFunctions funs
set(boolean, ScoringFunction...) - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior
 
set(AlphabetContainer) - Method in class de.jstacs.models.AbstractModel
This method should only be invoked by the method setNewAlphabetContainerInstance( AlphabetContainer ) and not be made public.
set(AlphabetContainer) - Method in class de.jstacs.models.CompositeModel
 
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
Sets the parameters as internal parameters and does some essential computations.
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
 
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel
 
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
 
set(AlphabetContainer) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
 
setAlpha(double) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
Sets the parameter of the Dirichlet which is used when you invoke train to init the gammas.
setAlternativeInstanceClass(Class) - Method in class de.jstacs.parameters.ParameterSet
Sets the class of the instances that can be constructed using this set.
setBounds(int[]) - Method in class de.jstacs.models.discrete.inhomogeneous.SequenceIterator
This method sets the bounds for each position.
setClassWeights(boolean, double...) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
Sets new class weights.
setCurrentLength(int) - Method in class de.jstacs.models.discrete.inhomogeneous.CombinationIterator
This method sets the current used number of selected elements.
setCurrentSamplingIndex(int) - Method in class de.jstacs.models.mixture.gibbssampling.BurnInTest
This method sets the value of the current sampling. this allows to assign th evalues form BurnInTest.setValue(double) to a sampling.
setCurrentSamplingIndex(int) - Method in class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
 
setDefault(Object) - Method in class de.jstacs.parameters.CollectionParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.EnumParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.FileParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.Parameter
Sets the default value of the parameter to defaultValue
setDefault(Object) - Method in class de.jstacs.parameters.ParameterSetContainer
 
setDefault(Object) - Method in class de.jstacs.parameters.RangeParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.SimpleParameter
 
setEss(double) - Method in class de.jstacs.models.discrete.DGMParameterSet
This method can be used to set the ess of this parameter set.
setESS(double) - Method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner
This method sets the ESS of the StructureLearner.
setExpLambda(int, double) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Sets the value of exp(\lambda_{index})
setFreqs(String[], int) - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb
This method is used to restore the values of a Gibbs Sampling run.
setFurtherModelInfos(StringBuffer) - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
This method replaces the internal model infos with those from the StringBuffer.
setFurtherModelInfos(StringBuffer) - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
 
setFurtherModelInfos(StringBuffer) - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
In this method the reader is set to null
setHiddenParameters(double[], int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method set the hidden parameters of the model
setLambda(int, double) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Sets the value of \lambda_{index}
setLastDistance(double) - Method in class de.jstacs.algorithms.optimization.ConstantStartDistance
 
setLastDistance(double) - Method in class de.jstacs.algorithms.optimization.LimitedMedianStartDistance
 
setLastDistance(double) - Method in interface de.jstacs.algorithms.optimization.StartDistanceForecaster
Sets the last used distance.
setMax(int) - Method in class de.jstacs.utils.DefaultProgressUpdater
 
setMax(int) - Method in class de.jstacs.utils.GUIProgressUpdater
 
setMax(int) - Method in class de.jstacs.utils.NullProgressUpdater
sets the maximal value that will be set by setValue(), so a value of max indicates the end of the supervised method call.
setMax(int) - Method in interface de.jstacs.utils.ProgressUpdater
sets the maximal value that will be set by setValue(), so a value of max indicates the end of the supervised method call.
setModelType(String) - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet
This method allows a simple change of the model type.
setNeededReference(ParameterSet) - Method in class de.jstacs.parameters.Parameter
Sets an internal reference to a ParameterSet whose validity depends on the value of this Parameter.
setNeededReference(ParameterSet) - Method in class de.jstacs.parameters.RangeParameter
 
setNewAlphabetContainerInstance(AlphabetContainer) - Method in class de.jstacs.classifier.AbstractClassifier
This method tries to set a new instance of an AlphabetConatiner for the current model.
setNewAlphabetContainerInstance(AlphabetContainer) - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
 
setNewAlphabetContainerInstance(AlphabetContainer) - Method in class de.jstacs.models.AbstractModel
 
setNewAlphabetContainerInstance(AlphabetContainer) - Method in interface de.jstacs.models.Model
This method tries to set a new instance of an AlphabetContainer for the current model.
setOffset() - Method in class de.jstacs.utils.NullProgressUpdater
after setOffset() is called the current value will be added to every value set by setValue()
setOutputStream(OutputStream) - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
Sets the OutputStream that is used e.g. for writing information while training.
setOutputStream(OutputStream) - Method in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
Sets the output stream for the model.
setOutputStream(OutputStream) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
Sets the OutputStream that is used e.g. for writing information while training.
setParameterFor(int, int[][], Parameter) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Sets the instance of the parameter for symbol symbol and context context to parameter par.
setParameterOptimization(boolean) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
This method allows the user specify whether the parameters should be optimized or not.
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
 
setParameters(double[], int) - Method in interface de.jstacs.scoringFunctions.ScoringFunction
This method sets the internal parameters to the values of params between start and start + this.getNumberOfParameters() - 1
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
 
setParametersForFunction(int, double[], int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method allows to set the parameters for specific functions.
setParams(double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.cll.NormConditionalLogLikelihood
 
setParams(double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.OptimizableFunction
Sets the current values as parameters
setParent(ParameterSet) - Method in class de.jstacs.parameters.Parameter
Sets the reference of the enclosing ParameterSet of this Parameter to parent.
setParent(ParameterSetContainer) - Method in class de.jstacs.parameters.ParameterSet
Sets the enclosing ParameterSetContainer of this ParameterSet to parent.
setPlugInParameters(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
Computes and sets the plug-in parameters (MAP estimated parameters) from data using weights.
setPrior(LogPrior) - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
This method set a new prior that should be used for optimization.
setRangeable(boolean) - Method in class de.jstacs.parameters.CollectionParameter
Sets the value returned by isRangeable() to rangeable
setRangeable(boolean) - Method in class de.jstacs.parameters.SimpleParameter
Sets the value returned by isRangeable() to rangeable
setRootValue(int, double) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
setRootValue(int, double) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
setRootValue(int, double) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Sets the value val for the root node child.
setSeed(long) - Method in class de.jstacs.utils.random.RandomNumberGenerator
 
setSelected(MeasureParameters.Measure, boolean) - Method in class de.jstacs.classifier.MeasureParameters
Selects or de-selects the option sel depending on b.
setSelected(String, boolean) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
Sets the selection of the option key to the value of selected
setSelected(int, boolean) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
Sets the selection of option no.
setShallBeRanged(RangeParameter.RangeType) - Method in class de.jstacs.parameters.RangeParameter
Sets the type of this RangeParameter to one of LIST, RANGE, or NO.
setStatisticForHyperparameters(int[], double[]) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
 
setStatisticForHyperparameters(int[], double[]) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
 
setStatisticForHyperparameters(int[], double[]) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
 
setStatisticForHyperparameters(int[], double[]) - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
This method sets the hyperparameters for the model parameters by evaluating the given statistic.
setStringToBeParsed(String) - Method in class de.jstacs.io.SymbolExtractor
Sets a new string to be parsed.
setThreshold(double) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
Sets the threshold for terminating the train algorithm.
setThresholdClassWeights(boolean, double) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
Sets a new threshold for 2-class-classifiers.
setTrainData(Sample) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method is invoked by the train method and set for a given sample the sample that should be used for train.
setTrainData(Sample) - Method in class de.jstacs.models.mixture.MixtureModel
 
setTrainData(Sample) - Method in class de.jstacs.models.mixture.StrandModel
 
setValidator(ParameterValidator) - Method in class de.jstacs.parameters.SimpleParameter
Sets a new ParameterValidator for this SimpleParameter.
setValue(byte, double, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
setValue(byte, double, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
Sets the value if it is bigger than the current value and keeps the parents information
setValue(byte, double, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Sets the value for the edge parents[0],...
setValue(double) - Method in class de.jstacs.models.mixture.gibbssampling.BurnInTest
This method can be used to fill the internal memory with the values that will be used to determine the length of the burn-in phase.
setValue(double) - Method in class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
 
setValue(Object) - Method in class de.jstacs.parameters.CollectionParameter
Sets the selected value to the one that is specified by the key value
setValue(Object) - Method in class de.jstacs.parameters.EnumParameter
 
setValue(Object) - Method in class de.jstacs.parameters.FileParameter
 
setValue(Object) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
setValue(Object) - Method in class de.jstacs.parameters.Parameter
Sets the value of this parameter to value.
setValue(Object) - Method in class de.jstacs.parameters.ParameterSetContainer
 
setValue(Object) - Method in class de.jstacs.parameters.RangeParameter
 
setValue(Object) - Method in class de.jstacs.parameters.SimpleParameter
 
setValue(double) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
Sets the current value of this parameter.
setValue(int) - Method in class de.jstacs.utils.DefaultProgressUpdater
 
setValue(int) - Method in class de.jstacs.utils.GUIProgressUpdater
 
setValue(int) - Method in class de.jstacs.utils.NullProgressUpdater
sets the current value the supervised process has reached.
setValue(int) - Method in interface de.jstacs.utils.ProgressUpdater
sets the current value the supervised process has reached.
setValue(int) - Method in class de.jstacs.utils.TimeLimitedProgressUpdater
 
setValues(String) - Method in class de.jstacs.parameters.RangeParameter
Sets a list of values from a String containing a space separated list of values.
setValues(Object, int, Object, RangeParameter.Scale) - Method in class de.jstacs.parameters.RangeParameter
Sets the values of this RangeParameter as a range of values, specified by a start values, a last value, a number of steps between these values (without the last value), and a scale in that the values between the first and the last value are chosen.
setValuesInLogScale(boolean, double, Object, int, Object) - Method in class de.jstacs.parameters.RangeParameter
This method enables you to set a list of values in an easy manner.
setWeights(double...) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
Sets the weights.
shallBeRanged() - Method in class de.jstacs.parameters.RangeParameter
Returns one of LIST, RANGE, or NO depending on the input used to specify this RangeParameter
SharedStructureClassifier - Class in de.jstacs.models.discrete.inhomogeneous.shared
This class enables you to learn the structure on all classes together.
SharedStructureClassifier(int, StructureLearner.ModelType, byte, StructureLearner.LearningType, FSDAGModel...) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier
The main constructor.
SharedStructureClassifier(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier
The constructor for the Storable interface.
SharedStructureMixture - Class in de.jstacs.models.discrete.inhomogeneous.shared
This class handles a mixture of models with the same structure that are learned via EM.
SharedStructureMixture(FSDAGModel[], StructureLearner.ModelType, byte, int, double, double) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
This main constructor creates an instance which estimates the component probabilities.
SharedStructureMixture(FSDAGModel[], StructureLearner.ModelType, byte, int, double[], double, double) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
This main constructor creates an instance with fixed component weights.
SharedStructureMixture(FSDAGModel[], StructureLearner.ModelType, byte, int, boolean, double[], double, double) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
This constructor is used from the other main constructors.
SharedStructureMixture(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
The constructor for the Storable interface.
ShortSequence - Class in de.jstacs.data.sequences
This class can be used for discrete AlphabetContainer with alphabets that use many different symbols.
ShortSequence(AlphabetContainer, short[]) - Constructor for class de.jstacs.data.sequences.ShortSequence
This constructor is designed for the emitSample( int n ) of AbstractModel.
ShortSequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.ShortSequence
Creates a new sequence from a string representation using the default delimiter.
ShortSequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.ShortSequence
Creates a new sequence from a string representation using the delimiter delim.
ShortSequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.ShortSequence
Creates a new sequence from a SymbolExctractor.
shouldBeNormalized() - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifierParameterSet
This method true if a normalization shall be used while optimization.
showImage(String, BufferedImage) - Static method in class de.jstacs.utils.REnvironment
Enables you to show an image.
showImage(String, BufferedImage, int) - Static method in class de.jstacs.utils.REnvironment
Enables you to show an image.
SimpleBurnInTest - Class in de.jstacs.models.mixture.gibbssampling
This is a very simple test for the length of the burn-in phase.
SimpleBurnInTest(int) - Constructor for class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
This is the main constructor that creates an instance of fixed burn-in length.
SimpleBurnInTest(StringBuffer) - Constructor for class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
The standard constructor for the interface Storable.
SimpleGaussianSumLogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
This class implements a prior that is a product of Gaussian distributions with mean 0 and equal variance for each parameter.
SimpleGaussianSumLogPrior(double) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior
Creates a new SimpleGaussianSumLogPrior with mean 0 and variance sigma for all parameters, including the class parameters.
SimpleGaussianSumLogPrior(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior
Re-creates a SimpleGaussianSumLogPrior from its XML-representation as returned by SimpleGaussianSumLogPrior.toXML().
SimpleParameter - Class in de.jstacs.parameters
Class for a "simple" parameter.
SimpleParameter(StringBuffer) - Constructor for class de.jstacs.parameters.SimpleParameter
Constructs a SimpleParameter out of an XML representation
SimpleParameter(DataType, String, String, boolean) - Constructor for class de.jstacs.parameters.SimpleParameter
Constructor for a SimpleParameter without validator
SimpleParameter(DataType, String, String, boolean, Object) - Constructor for class de.jstacs.parameters.SimpleParameter
Constructor for a SimpleParameter without ParameterValidator but with a default value
SimpleParameter(DataType, String, String, boolean, ParameterValidator) - Constructor for class de.jstacs.parameters.SimpleParameter
Constructor for a SimpleParameter with a ParameterValidator.
SimpleParameter(DataType, String, String, boolean, ParameterValidator, Object) - Constructor for class de.jstacs.parameters.SimpleParameter
Constructor for a SimpleParameter with validator and default value.
SimpleParameter.DatatypeNotValidException - Exception in de.jstacs.parameters
Class for an Exception that can be thrown if the provided int-value that represents a datatype is not one of the values defined in the Parameter-interface.
SimpleParameter.DatatypeNotValidException(String) - Constructor for exception de.jstacs.parameters.SimpleParameter.DatatypeNotValidException
Creates a new DatatypeNotValidException from an error-message.
SimpleParameter.IllegalValueException - Exception in de.jstacs.parameters
This exception is thrown if a parameter is not valid.
SimpleParameter.IllegalValueException(String) - Constructor for exception de.jstacs.parameters.SimpleParameter.IllegalValueException
Creates a new IllegalValueException with the reason of the exception reason
SimpleParameterSet - Class in de.jstacs.parameters
Class for a ParameterSet that is constructed from an array of Parameters and thus does nothing in the loadParameters()-method.
SimpleParameterSet(Parameter[]) - Constructor for class de.jstacs.parameters.SimpleParameterSet
Creates a new SimpleParameterSet from an array of Parameters.
SimpleParameterSet(StringBuffer) - Constructor for class de.jstacs.parameters.SimpleParameterSet
Constructs a SimpleParameterSet from its XML-representation
SimpleReferenceConstraint - Class in de.jstacs.parameters.validation
Class for a ReferenceConstraint that checks for "simple" conditions as defined in the Constraint-interface.
SimpleReferenceConstraint(SimpleParameter, int) - Constructor for class de.jstacs.parameters.validation.SimpleReferenceConstraint
Creates a new SimpleReferenceConstraint from a reference SimpleParameter and a comparison operator, which is one of the values defined in the Constraint-interface.
SimpleReferenceConstraint(StringBuffer) - Constructor for class de.jstacs.parameters.validation.SimpleReferenceConstraint
Creates a new SimpleReferenceConstraint from its XML-representation.
SimpleResult - Class in de.jstacs.results
Abstract class for a Result with a value of a primitive data type or String.
SimpleResult(String, String, DataType) - Constructor for class de.jstacs.results.SimpleResult
The main constructor which takes the main information of a result.
SimpleResult(StringBuffer) - Constructor for class de.jstacs.results.SimpleResult
This is the constructor for Storable.
SimpleSequenceIterator - Class in de.jstacs.data.bioJava
Class that implements the SequenceIterator interface of BioJava in a simple way, backed by an array of Sequences.
SimpleSequenceIterator(Sequence...) - Constructor for class de.jstacs.data.bioJava.SimpleSequenceIterator
Creates a new SimpleSequenceIterator from an array of Sequences.
SimpleStaticConstraint - Class in de.jstacs.parameters.validation
Class for a Constraint that checks values against static values using the comparison operators defined in the Constraint-interface.
SimpleStaticConstraint(Number, int) - Constructor for class de.jstacs.parameters.validation.SimpleStaticConstraint
Creates a new SimpleStaticConstraint from a Number-reference and a comparisonOperator as defined in Constraint.
SimpleStaticConstraint(String, int) - Constructor for class de.jstacs.parameters.validation.SimpleStaticConstraint
Creates a new SimpleStaticConstraint from a String-reference and a comparisonOperator as defined in Constraint.
SimpleStaticConstraint(StringBuffer) - Constructor for class de.jstacs.parameters.validation.SimpleStaticConstraint
Creates a new SimpleStaticConstraint from its XML-representation
simplify() - Method in class de.jstacs.parameters.CollectionParameter
 
simplify() - Method in class de.jstacs.parameters.FileParameter
 
simplify() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
simplify() - Method in class de.jstacs.parameters.Parameter
Simplifies the Parameter and its contents to the relevant information.
simplify() - Method in class de.jstacs.parameters.ParameterSet
Simplifies all parameters in this ParameterSet
simplify() - Method in class de.jstacs.parameters.ParameterSetContainer
 
simplify() - Method in class de.jstacs.parameters.RangeParameter
 
simplify() - Method in class de.jstacs.parameters.SimpleParameter
 
SinglePositionSequenceAnnotation - Class in de.jstacs.data.sequences.annotation
Class for some annotations that consist mainly of one position on a sequence.
SinglePositionSequenceAnnotation(SinglePositionSequenceAnnotation.Type, String, int) - Constructor for class de.jstacs.data.sequences.annotation.SinglePositionSequenceAnnotation
Creates a new SinglePositionSequenceAnnotation of type type, with identifier identifier and position position.
SinglePositionSequenceAnnotation(SinglePositionSequenceAnnotation.Type, String, int, Result...) - Constructor for class de.jstacs.data.sequences.annotation.SinglePositionSequenceAnnotation
Creates a new SinglePositionSequenceAnnotation of type type, with identifier identifier, position position, and additional annotations additionalAnnotation.
SinglePositionSequenceAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.SinglePositionSequenceAnnotation
Re-creates a SinglePositionSequenceAnnotation from its XML-representation as returned by LocatedSequenceAnnotation.toXML().
SinglePositionSequenceAnnotation.Type - Enum in de.jstacs.data.sequences.annotation
The possible types of a SinglePositionSequenceAnnotation.
skip(int) - Method in class de.jstacs.models.discrete.inhomogeneous.SequenceIterator
This method skips some position.
skipLastClassifiersDuringClassifierTraining - Variable in class de.jstacs.classifier.assessment.ClassifierAssessment
 
SoftOneOfN - Class in de.jstacs.utils.random
This random generator returns 1-epsilon for one and equal parts for the rest.
SoftOneOfN(double) - Constructor for class de.jstacs.utils.random.SoftOneOfN
This constructor can be used for (soft) sampling one of n.
SoftOneOfN() - Constructor for class de.jstacs.utils.random.SoftOneOfN
This constructor can be used for (hard) sampling one of n.
sort(String) - Method in class de.jstacs.results.ListResult
This method enables you to sort the entrys of this container by a specified column.
sostream - Variable in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
This stream is used for comments, ... while the training, ... .
sostream - Variable in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
This stream is used for comments, ... while the training, ... .
sostream - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
This is the stream for writing information while training.
source - Variable in class de.jstacs.algorithms.graphs.Edge
The source node.
SparseSequence - Class in de.jstacs.data.sequences
This class is an implementation for sequence on one alphabet with length 4.
SparseSequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.SparseSequence
This constructor creates an instance from a String.
SparseSequence(AlphabetContainer, SymbolExtractor) - Constructor for class de.jstacs.data.sequences.SparseSequence
This constructor creates an instance from a SymbolExtractor.
StartDistanceForecaster - Interface in de.jstacs.algorithms.optimization
This Interface is used to determine the next start distance that will be used in a line search
starts - Variable in class de.jstacs.models.CompositeModel
The start indices.
starts - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The number of starts
StationaryDistribution - Class in de.jstacs.models.utils
This class can be used to determine the stationary distribution.
StationaryDistribution() - Constructor for class de.jstacs.models.utils.StationaryDistribution
 
stationaryIteration - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The number of iterations of the Gibbs Sampler
StatisticalTest - Class in de.jstacs.models.utils
This class enables the user to compute some divergences.
StatisticalTest() - Constructor for class de.jstacs.models.utils.StatisticalTest
 
STEEPEST_DESCENT - Static variable in class de.jstacs.algorithms.optimization.Optimizer
This constant can be used to specify that steepest descent should be used in the optimize-method.
steepestDescent(DifferentiableFunction, double[], Optimizer.TerminationCondition, double, double, StartDistanceForecaster, SafeOutputStream, Time) - Static method in class de.jstacs.algorithms.optimization.Optimizer
The steepest descent.
Storable - Interface in de.jstacs
This is the root interface for all immutable objects that must be stored in e.g. a file or a database.
StorableArrayWithTags(Storable[]) - Static method in class de.jstacs.io.XMLParser
Encodes a Storable array.
StorableResult - Class in de.jstacs.results
Class for results that are Storables.
StorableResult(String, String, Storable) - Constructor for class de.jstacs.results.StorableResult
Creates a result for an XML-representation of an object.
StorableResult(StringBuffer) - Constructor for class de.jstacs.results.StorableResult
Constructs a new ObjectResult from its XML-representation
StorableValidator - Class in de.jstacs.parameters.validation
Class for a validator that validates instances and XML-representations for the correct class types (e.g.
StorableValidator(Class<? extends Storable>, boolean) - Constructor for class de.jstacs.parameters.validation.StorableValidator
Creates a new ObjectValidator for a subclass of AbstractModel or AbstractClassifier.
StorableValidator(Class<? extends Storable>) - Constructor for class de.jstacs.parameters.validation.StorableValidator
Creates a new ObjectValidator for a subclass of Storable.
StorableValidator(StringBuffer) - Constructor for class de.jstacs.parameters.validation.StorableValidator
Constructs an ObjectValidator from its XML-representation
StrandedLocatedSequenceAnnotationWithLength - Class in de.jstacs.data.sequences.annotation
Class for a SequenceAnnotation that has a position, a length, and an orientation on the strand of a Sequence.
StrandedLocatedSequenceAnnotationWithLength(int, int, StrandedLocatedSequenceAnnotationWithLength.Strand, String, String, Result...) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Creates a new StrandedLocatedSequenceAnnotationWithLength of type type, with identifier identifier, and additional annotation (that does not fit the SequenceAnnotation definitions) result.
StrandedLocatedSequenceAnnotationWithLength(int, int, StrandedLocatedSequenceAnnotationWithLength.Strand, String, String, Collection<Result>) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Creates a new StrandedLocatedSequenceAnnotationWithLength of type type, with identifier identifier, and additional annotation (that does not fit the SequenceAnnotation definitions) result.
StrandedLocatedSequenceAnnotationWithLength(int, int, StrandedLocatedSequenceAnnotationWithLength.Strand, String, String, SequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Creates a new StrandedLocatedSequenceAnnotationWithLength of type type, with identifier identifier, and additional annotation (that does not fit the SequenceAnnotation definitions) additionalAnnotations, and sub-annotations.
StrandedLocatedSequenceAnnotationWithLength(String, String, StrandedLocatedSequenceAnnotationWithLength.Strand, LocatedSequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Creates a new StrandedLocatedSequenceAnnotationWithLength of type type, with identifier identifier, and additional annotation (that does not fit the SequenceAnnotation definitions) additionalAnnotations, and sub-annotations.
StrandedLocatedSequenceAnnotationWithLength(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Re-creates a StrandedLocatedSequenceAnnotationWithLength from its XML-representation as returned by StrandedLocatedSequenceAnnotationWithLength.toXML().
StrandedLocatedSequenceAnnotationWithLength.Strand - Enum in de.jstacs.data.sequences.annotation
The possible orientations on the strands.
strandedness() - Method in enum de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength.Strand
Returns the strandedness as a String
StrandModel - Class in de.jstacs.models.mixture
This model handles sequences that can either lie on the forward strand or on the backward strand.
StrandModel(Model, int, boolean, double[], double, AbstractMixtureModel.Algorithm, double, double, AbstractMixtureModel.Parameterization, int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates a new StrandModel.
StrandModel(Model, int, double[], double, double, AbstractMixtureModel.Parameterization) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates an instance using EM and estimating the component probabilities.
StrandModel(Model, int, double, double, double, AbstractMixtureModel.Parameterization) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates an instance using EM and fixed component probabilities.
StrandModel(Model, int, double[], int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates an instance using Gibbs Sampling and sampling the component probabilities.
StrandModel(Model, int, double, int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates an instance using Gibbs Sampling and fixed component probabilities.
StrandModel(StringBuffer) - Constructor for class de.jstacs.models.mixture.StrandModel
This constructor can be used for loading a StrandModel form a StringBuffer;
StringArrayWithTags(String[]) - Static method in class de.jstacs.io.XMLParser
Encodes a String array.
StringExtractor - Class in de.jstacs.io
This class implements the reader that extracts strings from either a file or a string.
StringExtractor(File, int) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from file.
StringExtractor(File, int, char) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from file and ignores those starting with ignore.
StringExtractor(File, int, String) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from file .
StringExtractor(File, int, char, String) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from file and ignores those starting with ignore.
StringExtractor(String, int, String) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from a String content.
StringExtractor(String, int, char, String) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from a String content and ignores those starting with ignore
StructureLearner - Class in de.jstacs.models.discrete.inhomogeneous
This class can be used to learn the structure of any discrete model.
StructureLearner(AlphabetContainer, int, double) - Constructor for class de.jstacs.models.discrete.inhomogeneous.StructureLearner
Creates a StructureLearner
StructureLearner(AlphabetContainer, int) - Constructor for class de.jstacs.models.discrete.inhomogeneous.StructureLearner
Creates a StructureLearner with ess = 0.
StructureLearner.LearningType - Enum in de.jstacs.models.discrete.inhomogeneous
This enum defines the different types of learning that are possible with the StructureLearner.
StructureLearner.ModelType - Enum in de.jstacs.models.discrete.inhomogeneous
This enum defines the different types of models that can be learned with the StructureLearner.
structureMeasure - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
Measure that defines the network structure
subSampling(int) - Method in class de.jstacs.data.Sample
Randomly samples elements (sequences) from the set of all elements (sequences) contained in this Sample.
SubstringFilenameFilter - Class in de.jstacs.io
A simple filter on files.
SubstringFilenameFilter(SubstringFilenameFilter.PartOfName, String, boolean, boolean, String...) - Constructor for class de.jstacs.io.SubstringFilenameFilter
A simple constructor.
SubstringFilenameFilter.PartOfName - Enum in de.jstacs.io
This enum defines the different types a string can be part of a other string.
sum(double[]) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
Computes the sum of all elements in ar.
sumNormalisation(double[]) - Static method in class de.jstacs.utils.Normalisation
sum normailsation on d
sumNormalisation(double[], double[], int) - Static method in class de.jstacs.utils.Normalisation
sum normalisation on d, writing the result in dest starting at position start
swap() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method swaps the current component models with the alternative model.
symbol - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
The symbol (out of some Alphabet) this parameter is responsible for.
SymbolExtractor - Class in de.jstacs.io
This class enables you to extract elements form a given string similar to an StringTokenizer.
SymbolExtractor(String) - Constructor for class de.jstacs.io.SymbolExtractor
Creates a new instance using delim as delimiter.
SymbolExtractor(String, String) - Constructor for class de.jstacs.io.SymbolExtractor
Creates a new instance using delim as delimiter and string as string to be parsed.
SymmetricTensor - Class in de.jstacs.algorithms.graphs.tensor
This class can be used for Tensors with a special symmetry property.
SymmetricTensor(int, byte) - Constructor for class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
SymmetricTensor(SymmetricTensor[], double[]) - Constructor for class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
The constructor can be used creating a new SymmetricTensor as weighted sum of SymmetricTensors
SymmetricTensor(AsymmetricTensor) - Constructor for class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
SymmetricTensor(double[][][], int, byte) - Constructor for class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 

A B C D E F G H I K L M N O P Q R S T U V W X