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B

backward(ParameterTree[], int[][]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Starts the computation of the backward-part of the normalization constant starting from this ParameterTree.
BayesianNetworkModel - Class in de.jstacs.models.discrete.inhomogeneous
The class implements a Bayesian network of fixed order.
BayesianNetworkModel(BayesianNetworkModelParameterSet) - Constructor for class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
The default constructor.
BayesianNetworkModel(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
The constructor for a model in xml format.
BayesianNetworkModelParameterSet - Class in de.jstacs.models.discrete.inhomogeneous.parameters
The ParameterSet for the class BayesianNetworkModel.
BayesianNetworkModelParameterSet(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet
The constructor for the Storable interface.
BayesianNetworkModelParameterSet() - Constructor for class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet
The simple constructor for an empty parameter set of a BayesianNetworkModel.
BayesianNetworkModelParameterSet(AlphabetContainer, int, double, String, StructureLearner.ModelType, byte, StructureLearner.LearningType) - Constructor for class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet
This is the constructor of a filled parameter set for a BayesianNetworkModel.
BayesianNetworkScoringFunction - Class in de.jstacs.scoringFunctions.directedGraphicalModels
This class implements a scoring function that is a moral directed graphical model, i.e. a moral Bayesian network.
BayesianNetworkScoringFunction(AlphabetContainer, int, double, boolean, Measure) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
Creates a new BayesianNetworkScoringFunction that has neither been initialized nor trained.
BayesianNetworkScoringFunction(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
Re-creates a BayesianNetworkScoringFunction from its XML-representation, as saved by the BayesianNetworkScoringFunction.toXML()} method.
BG - Static variable in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
Compute mutual information only from background data
BG - Static variable in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
Compute mutual information only from background data
BioJavaAdapter - Class in de.jstacs.data.bioJava
This class provides static methods to convert BioJava datatypes (SequenceIterator, Sequence) to Samples and vice versa.
BioJavaAdapter() - Constructor for class de.jstacs.data.bioJava.BioJavaAdapter
 
BooleanArrayWithTags(boolean[]) - Static method in class de.jstacs.io.XMLParser
Encodes a boolean array.
BOTH - Static variable in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
Use both data sets to compute the mutual information
BOTH - Static variable in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
Use both data sets to compute the mutual information
brentsMethod(OneDimensionalFunction, double, double, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
Approximates a minimum (not necessary the global) in the interval [lower,upper].
brentsMethod(OneDimensionalFunction, double, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
Approximates a minimum (not necessary the global) in the interval [lower,upper].
BTExplainingAwayResidual - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures
Structure learning Measure that computes a maximum spanning tree based on the explaining away residual and uses the resulting tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a BayesianNetworkScoringFunction.
BTExplainingAwayResidual(double[]) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
Creates a new explaining away residual Bayesian tree Measure.
BTExplainingAwayResidual(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
Re-creates a BTExplainingAwayResidual from is XML-representation as returned by BTExplainingAwayResidual.toXML().
BTMutualInformation - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures
Structure learning Measure that computes a maximum spanning tree based on mutual information and uses the resulting tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a BayesianNetworkScoringFunction.
BTMutualInformation(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
Re-creates a BTMutualInformation from is XML-representation as returned by BTMutualInformation.toXML().
BTMutualInformation(int, double[]) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
Creates a new mutual information Bayesian tree Measure.
burnInTest - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The BurnInTest that is used to stop the sampling
BurnInTest - Class in de.jstacs.models.mixture.gibbssampling
This is the abstract super class for any test of the length of the burn-in phase.
BurnInTest() - Constructor for class de.jstacs.models.mixture.gibbssampling.BurnInTest
 
ByteArrayWithTags(byte[]) - Static method in class de.jstacs.io.XMLParser
Encodes a byte array.
ByteSequence - Class in de.jstacs.data.sequences
This class can be used for discrete AlphabetContainer with alphabets that use only few symbols.
ByteSequence(AlphabetContainer, byte[]) - Constructor for class de.jstacs.data.sequences.ByteSequence
This constructor is designed for the emitSample( int n ) of AbstractModel.
ByteSequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.ByteSequence
Creates a new sequence from a string representation using the default delimiter.
ByteSequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.ByteSequence
Creates a new sequence from a string representation using the delimiter delim.
ByteSequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.ByteSequence
Creates a new sequence from a SymbolExctractor.

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