- f - Variable in class de.jstacs.algorithms.optimization.NumericalDifferentiableFunction
-
The function to be differentiated numerically
- factors - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
-
The independent maximum entropy models.
- FALSE - Static variable in class de.jstacs.results.StorableResult
-
The model/classifier has not been trained.
- FalsePositiveRateForFixedSensitivity - Class in de.jstacs.classifiers.performanceMeasures
-
This class implements the false positive rate for a fixed sensitivity.
- FalsePositiveRateForFixedSensitivity() - Constructor for class de.jstacs.classifiers.performanceMeasures.FalsePositiveRateForFixedSensitivity
-
- FalsePositiveRateForFixedSensitivity(double) - Constructor for class de.jstacs.classifiers.performanceMeasures.FalsePositiveRateForFixedSensitivity
-
- FalsePositiveRateForFixedSensitivity(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.FalsePositiveRateForFixedSensitivity
-
The standard constructor for the interface
Storable
.
- FASTA - Static variable in class de.jstacs.io.AbstractStringExtractor
-
The comment character for FastA-formatted files is ">".
- FastDirichletMRGParams - Class in de.jstacs.utils.random
-
The container for parameters of a Dirichlet random generator that uses the
same hyperparameter at all positions.
- FastDirichletMRGParams(double) - Constructor for class de.jstacs.utils.random.FastDirichletMRGParams
-
Creates the hyperparameter for a Dirichlet random generator which is used
at all positions for the hyperparameter vector of the underlying
Dirichlet distribution.
- file - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
-
The file in which the component probabilities are stored.
- FileManager - Class in de.jstacs.io
-
This class is for handling
File
s.
- FileParameter - Class in de.jstacs.parameters
-
Class for a
Parameter
that represents a local file.
- FileParameter(StringBuffer) - Constructor for class de.jstacs.parameters.FileParameter
-
The standard constructor for the interface
Storable
.
- FileParameter(String, String, String, boolean) - Constructor for class de.jstacs.parameters.FileParameter
-
- FileParameter(String, String, String, boolean, ParameterValidator) - Constructor for class de.jstacs.parameters.FileParameter
-
- FileParameter.FileRepresentation - Class in de.jstacs.parameters
-
Class that represents a file.
- filereader - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
-
Reading component probabilities from a file.
- FileRepresentation(String, String) - Constructor for class de.jstacs.parameters.FileParameter.FileRepresentation
-
- FileRepresentation(String) - Constructor for class de.jstacs.parameters.FileParameter.FileRepresentation
-
- FileRepresentation(StringBuffer) - Constructor for class de.jstacs.parameters.FileParameter.FileRepresentation
-
The standard constructor for the interface
Storable
.
- FileResult(String, String, String) - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.FileResult
-
- FileResult(String, String, String, String, String) - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.FileResult
-
- FileResult(StringBuffer) - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.FileResult
-
Creates a new
TextResult
from its XML-representation
- filewriter - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
-
Saving component probabilities in a file.
- fill(FileParameter) - Method in class de.jstacs.results.TextResult
-
- fill(double[], double[][][][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
-
Fills all parameters with the probabilities given in
distribution
.
- fillBwdMatrix(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
This method fills the backward-matrix for a given sequence.
- fillBwdMatrix(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
-
- fillBwdOrViterbiMatrix(HigherOrderHMM.Type, int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
-
This method computes the entries of the backward or the viterbi matrix.
- fillComponentScoreOf(int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
-
This method fills an internal array with the partial scores.
- fillComponentScores(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
-
- fillComponentScores(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
-
- fillComponentScores(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
-
- fillComponentScores(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
-
- fillContainer(float[], int) - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
-
- fillContainer(double[], int) - Method in class de.jstacs.data.sequences.ArbitrarySequence
-
- fillContainer(T, int) - Method in class de.jstacs.data.sequences.CyclicSequenceAdaptor
-
- fillContainer(int[], int) - Method in class de.jstacs.data.sequences.MappedDiscreteSequence
-
- fillContainer(double[], int) - Method in class de.jstacs.data.sequences.MultiDimensionalArbitrarySequence
-
- fillContainer(int[], int) - Method in class de.jstacs.data.sequences.MultiDimensionalDiscreteSequence
-
- fillContainer(T, int) - Method in class de.jstacs.data.sequences.Sequence
-
The method fills the content of a specific position in to the container.
- fillContainer(T, int) - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
-
- fillContainer(int[], int) - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
-
- fillCurrentParameter(double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
-
- fillCurrentParameter(double[]) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.DifferentiableEmission
-
Fills the current parameters in the global params
array using the internal offset.
- fillCurrentParameter(double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- fillCurrentParameter(double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
-
- fillCurrentParameter(double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
-
- fillFwdMatrix(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
This method fills the forward-matrix for a given sequence.
- fillFwdMatrix(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
-
- fillInfixScore(int[], int, int, double[]) - Method in interface de.jstacs.sequenceScores.QuickScanningSequenceScore
-
Computes the position-wise scores of an infix of the sequence
seq
(which must be encoded by the
same alphabet as this
QuickScanningSequenceScore
) beginning at
start
and extending for
length
positions.
- fillInfixScore(int[], int, int, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
- fillInfixScore(int[], int, int, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
-
- fillLogStatePosteriorMatrix(double[][], int, int, Sequence, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
This method fills the log state posterior of Sequence seq
in a given matrix.
- fillLogStatePosteriorMatrix(double[][], int, int, Sequence, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
-
- fillParameters(String, String...) - Method in class de.jstacs.parameters.ParameterSetTagger
-
- fillParameters(double[]) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.DifferentiableTransition
-
This method allows to fill the parameters of the transition in a given array.
- fillParameters(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
-
This method fills the current parameters of this
TransitionElement
into the given array
params
starting at position
offset
.
- fillParameters(double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
-
- fillParameters(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
-
This method allows to fill the current parameters using a specific offset.
- fillSamplingGroups(int, LinkedList<int[]>) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
-
- fillSamplingGroups(int, LinkedList<int[]>) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.DifferentiableEmission
-
Adds the groups of indexes of those parameters of this emission that should be sampled
together in one step of a grouped sampling procedure, each as an int[]
, into list
.
- fillSamplingGroups(int, LinkedList<int[]>) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- fillSamplingGroups(int, LinkedList<int[]>) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
-
- fillSamplingGroups(int, LinkedList<int[]>) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
-
- fillSamplingGroups(int, LinkedList<int[]>) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.DifferentiableTransition
-
Adds the groups of indexes of those parameters of this transition that should be sampled
together in one step of a grouped sampling procedure, each as an int[]
, into list
.
- fillSamplingGroups(int, LinkedList<int[]>) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
-
- fillTensor(Tensor, double[][]) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
-
Fills a
Tensor
t
with the weights defined in
weights
.
- fillTensor(Tensor, double[][][]) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
-
Fills a
Tensor
t
with the weights defined in
weights
.
- fillTransitionInformation(int, int, int, int[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
-
- fillTransitionInformation(int, int, int, int[]) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
-
This method fills all relevant information for a specific edge in a given container.
- filter(String, char, AlphabetContainer, int, String) - Static method in class de.jstacs.io.SymbolExtractor
-
This method allows the user to filter the content of a
File
using a given
AlphabetContainer
and a
minimal sequence length.
- filterBySuperclass(Class<S>, LinkedList<Class<? extends T>>) - Static method in class de.jstacs.utils.SubclassFinder
-
Returns a
LinkedList
of the
Class
objects for all classes
in
listToFilter
that are sub-classes of
superClass
.
- filterProperties(String, Boolean, DinucleotideProperty.HowCreated, DinucleotideProperty.Type, String) - Static method in enum de.jstacs.data.DinucleotideProperty
-
- finalize() - Method in class de.jstacs.io.SparseStringExtractor
-
- finalize() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
-
- finalize() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
- finalize() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
-
- finalize() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- finalize() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
-
- finalize() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
-
- finalize() - Method in class de.jstacs.utils.GUIProgressUpdater
-
- finalize() - Method in class de.jstacs.utils.REnvironment
-
- finalize() - Method in class de.jstacs.utils.SafeOutputStream
-
- finalState - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
An array of switches that contains for each state whether is is a final state or not (cf.
- find(int) - Method in class de.jstacs.algorithms.graphs.UnionFind
-
Finds the root of the tree with node n
and does path
contraction.
- find(ParameterSet, String) - Static method in class de.jstacs.tools.DataColumnParameter
-
- find(ComplementableDiscreteAlphabet, double[][], ArrayList<AbstractMap.SimpleEntry<String, double[][]>>, PFMComparator.PFMDistance, int, int, boolean, double) - Static method in class de.jstacs.utils.PFMComparator
-
This methods finds for a user specified PFM pfm
similar PFMs in a list of known PFMs.
- findBracket(OneDimensionalFunction, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
-
This method returns a bracket containing a minimum.
- findBracket(OneDimensionalFunction, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
-
This method returns a bracket containing a minimum.
- findColumn(String) - Method in class de.jstacs.results.ResultSet
-
This method enables you to search for a column.
- findInstantiableSubclasses(Class<T>, String) - Static method in class de.jstacs.utils.SubclassFinder
-
Returns all sub-classes of T
that can be instantiated, i.e.
- findMax() - Method in class de.jstacs.algorithms.optimization.QuadraticFunction
-
- findMin(double, double, double, double) - Method in class de.jstacs.algorithms.optimization.OneDimensionalFunction
-
This method returns a minimum x
and the value
f(x)
, starting the search at lower
.
- findMin() - Method in class de.jstacs.algorithms.optimization.QuadraticFunction
-
- findModification(int, int, MutableMotifDiscoverer, DifferentiableSequenceScore[], DataSet[], double[][], DiffSSBasedOptimizableFunction, DifferentiableFunction, byte, double, StartDistanceForecaster, SafeOutputStream, History, int, boolean) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
-
This method tries to find a modification, i.e.
- findOneDimensionalMin(double[], double[], double, double, double, double) - Method in class de.jstacs.algorithms.optimization.DifferentiableFunction
-
This method is used to find an approximation of an one-dimensional
subfunction.
- findSignificantMotifOccurrences(int, Sequence, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
-
This method finds the significant motif occurrences in the sequence.
- findSignificantMotifOccurrences(int, Sequence, int, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
-
This method finds the significant motif occurrences in the sequence.
- findSplitIndex(double[], double) - Static method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure
-
Returns the index in sortedScores
with value greater or equal to t
.
- findSubclasses(Class<T>, String) - Static method in class de.jstacs.utils.SubclassFinder
-
Returns all sub-classes of T
including interfaces and
abstract classes that are located in a package below
startPackage
.
- findThreshold(double[], double[], double[], double, boolean) - Static method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure
-
Determines the threshold for a given percentage on the reference weights using the scores in
sortedReferenceScores
and sortedMeasureScores
.
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.ArbitrarySequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.ByteSequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.CyclicSequenceAdaptor
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.IntSequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.MappedDiscreteSequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.PermutedSequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.Sequence.CompositeSequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.Sequence
-
Works in analogy to
Object.clone()
, but does not clone the
annotation.
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.Sequence.SubSequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.ShortSequence
-
- flatCloneWithoutAnnotation() - Method in class de.jstacs.data.sequences.SparseSequence
-
- flush() - Method in class de.jstacs.tools.ui.cli.CLI.SysProtocol
-
- flush() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.Protocol
-
- flush() - Method in class de.jstacs.utils.SafeOutputStream
-
- forward(BNDiffSMParameterTree[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
-
- forward - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
An array of switches that contains for each state whether the emission is forward or the reverse strand.
- forward - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleState
-
A switch that decides whether to use the forward or the reverse complementary strand of a sequence.
- freeParameters - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLogPrior
-
Indicates, if only free parameters shall be used and hence penalized.
- freeParams - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction
-
Indicates whether only the free parameters or all should be used.
- freeParams - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
-
This boolean
indicates whether free parameterization or all
parameters are used.
- freq - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
-
The frequencies estimated from the counts.
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.ExpandableParameterSet
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.FileParameter
-
- fromGalaxy(String, StringBuffer) - Method in interface de.jstacs.parameters.GalaxyConvertible
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.MultiSelectionParameter
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.ParameterSet
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.ParameterSetContainer
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.RangeParameter
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.SelectionParameter
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.SimpleParameter
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.validation.NumberValidator
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.parameters.validation.RegExpValidator
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.tools.DataColumnParameter
-
- fromGalaxy(String, StringBuffer) - Method in class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter
-
- fromGalaxyConfig(String) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor
-
Parses the values of the parameters from a galaxy script file
- fromXML(StringBuffer) - Method in class de.jstacs.algorithms.alignment.PairwiseStringAlignment
-
- fromXML(StringBuffer) - Method in class de.jstacs.algorithms.alignment.StringAlignment
-
Parses the XML representation.
- fromXML(StringBuffer) - Method in class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.data.AlphabetContainerParameterSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
-
- fromXML(StringBuffer) - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
-
- fromXML(StringBuffer) - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
-
- fromXML(StringBuffer) - Method in class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
-
- fromXML(StringBuffer) - Method in class de.jstacs.parameters.ArrayParameterSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.parameters.ExpandableParameterSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.parameters.InstanceParameterSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.parameters.ParameterSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.parameters.SequenceScoringParameterSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.parameters.validation.ConstraintValidator
-
- fromXML(StringBuffer) - Method in class de.jstacs.parameters.validation.NumberValidator
-
- fromXML(StringBuffer) - Method in class de.jstacs.parameters.validation.SimpleStaticConstraint
-
- fromXML(StringBuffer) - Method in class de.jstacs.parameters.validation.StorableValidator
-
- fromXML(StringBuffer) - Method in class de.jstacs.results.MeanResultSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.results.ResultSet
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
-
This method is called in the constructor for the
Storable
interface to create a scoring function from a
StringBuffer
.
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
-
Parses this
Measure
from its XML representation.
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
-
This method should only be used by the constructor that works on a
StringBuffer
.
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureMixture
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
-
Parses the XML representation.
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.PluginGaussianEmission
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
-
- fromXML(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
-
- FSDAGModelForGibbsSampling - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
-
This is the class for a fixed structure directed acyclic graphical model (see
FSDAGTrainSM
) that can be used in a Gibbs sampling.
- FSDAGModelForGibbsSampling(FSDAGModelForGibbsSamplingParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
-
The default constructor.
- FSDAGModelForGibbsSampling(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
-
This is the constructor for the
Storable
interface.
- FSDAGModelForGibbsSamplingParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters
-
- FSDAGModelForGibbsSamplingParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGModelForGibbsSamplingParameterSet
-
The constructor for the
Storable
interface.
- FSDAGModelForGibbsSamplingParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGModelForGibbsSamplingParameterSet
-
- FSDAGModelForGibbsSamplingParameterSet(AlphabetContainer, int, double, String, String) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGModelForGibbsSamplingParameterSet
-
This is the constructor that creates a filled parameter set.
- FSDAGTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
-
This class can be used for any discrete
fixed
structure
directed
acyclic
graphical model (
FSDAGTrainSM
).
- FSDAGTrainSM(FSDAGTrainSMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
-
This is the main constructor.
- FSDAGTrainSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
-
The standard constructor for the interface
Storable
.
- FSDAGTrainSMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters
-
The class for the parameters of a
FSDAGTrainSM
(
fixed
structure
directed
acyclic
graphical
model).
- FSDAGTrainSMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGTrainSMParameterSet
-
The standard constructor for the interface
Storable
.
- FSDAGTrainSMParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGTrainSMParameterSet
-
- FSDAGTrainSMParameterSet(AlphabetContainer, int, double, String, String) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGTrainSMParameterSet
-
- FSDAGTrainSMParameterSet(Class<? extends FSDAGTrainSM>) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGTrainSMParameterSet
-
- FSDAGTrainSMParameterSet(Class<? extends FSDAGTrainSM>, AlphabetContainer, int, double, String, String) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGTrainSMParameterSet
-
- FSMEManager - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
-
This class can be used for any discrete fixed structure maximum entropy model (FSMEM).
- FSMEManager(FSMEMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSMEManager
-
- FSMEManager(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSMEManager
-
The standard constructor for the interface
Storable
.
- FSMEMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters
-
The ParameterSet for a FSMEManager.
- FSMEMParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSMEMParameterSet
-
The simple constructor.
- FSMEMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSMEMParameterSet
-
The constructor for the
Storable
interface.
- FSMEMParameterSet(AlphabetContainer, int, double, String, ConstraintManager.Decomposition, boolean, byte, double, String) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSMEMParameterSet
-
The fast constructor.
- Function - Interface in de.jstacs.algorithms.optimization
-
This interface is the framework for any mathematical function
.
- function - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
-
The function that is optimized in this classifier.
- function - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
-
- funs - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLogPrior
-
- furtherInits(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
-
This method allows the implementation of further initializations
- fwdMatrix - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
matrix for all forward-computed variables;
fwdMatrix[l][c] = log P(x_1,...,x_l,(s_{l-order+1},...,s_l)=c | parameter)