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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 `Sample`s 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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