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subsequenceLength
.
subsequenceLength
.
Model.emitSample(int, int...)
.
data
Sample.WeightedSampleFactory
on the given Sample
(s).
Sample.WeightedSampleFactory
on the given Sample
and weights
.
Sample.WeightedSampleFactory
on the given Sample
and weights
.
Sample.WeightedSampleFactory
on the given array of Sample
s and weights
.
Sample.WeightedSampleFactory
.ClassifierAssessmentAssessParameterSet
ClassifierAssessmentAssessParameterSet
ClassifierAssessmentAssessParameterSet
Sampled_RepeatedHoldOutExperiment
from an array of AbstractClassifier
s and a two-dimensional array
of Model
s, which are combined to additional classifiers.
Sampled_RepeatedHoldOutExperiment
from a set of AbstractClassifier
s.
Sampled_RepeatedHoldOutExperiment
from a set of Model
s.
AbstractClassifier
s and those constructed
using the given AbstractModel
s by a Sampled_RepeatedHoldOutExperiment
.
Sample
.SampleResult
from a Sample
with the annotation name
and comment
.
SampleResult
from its XML-representation as returned by SampleResult.toXML()
.
SequenceIterator
from sample
preserving
as much annotation as possible.
initModelForSampling
.
GibbsSamplingComponent.extendSampling(int, boolean)
.
start
.
sequence
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 NormalizableScoringFunction
s 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 NormalizableScoringFunction
s 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
ScoringFunction
s 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 Parameter
s.
- 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 Sequence
s. - SimpleSequenceIterator(Sequence...) -
Constructor for class de.jstacs.data.bioJava.SimpleSequenceIterator
- Creates a new
SimpleSequenceIterator
from an array of Sequence
s.
- 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
Storable
s. - 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
-
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