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## B

backward(ParameterTree[], int[][]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
  Computes 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 ( `StructureLearner.ModelType.BN` ) of fixed order.
BayesianNetworkModel(BayesianNetworkModelParameterSet) - Constructor for class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
  Creates a new `BayesianNetworkModel` from a given `BayesianNetworkModelParameterSet`.
BayesianNetworkModel(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
  The standard constructor for the interface `Storable`.
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 standard constructor for the interface `Storable`.
BayesianNetworkModelParameterSet() - Constructor for class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet
  The simple constructor for an empty `BayesianNetworkModelParameterSet` for 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 `BayesianNetworkModelParameterSet` 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(BayesianNetworkScoringFunctionParameterSet) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
  Creates a new `BayesianNetworkScoringFunction` that has neither been initialized nor trained from a `BayesianNetworkScoringFunctionParameterSet`.
BayesianNetworkScoringFunction(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
  The standard constructor for the interface `Storable`.
BayesianNetworkScoringFunctionParameterSet - Class in de.jstacs.scoringFunctions.directedGraphicalModels
  Class for the parameters of a `BayesianNetworkScoringFunction`.
BayesianNetworkScoringFunctionParameterSet(AlphabetContainer, int, double, boolean, Measure) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunctionParameterSet
  Creates a new `BayesianNetworkScoringFunctionParameterSet` with pre-defined parameter values.
BayesianNetworkScoringFunctionParameterSet() - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunctionParameterSet
  Creates a new `BayesianNetworkScoringFunctionParameterSet` with empty parameter values.
BayesianNetworkScoringFunctionParameterSet(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunctionParameterSet
  Creates a new `BayesianNetworkScoringFunctionParameterSet` from its XML representation as defined by the `Storable` interface.
best - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
beta - Variable in class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier
  The weights that determine a point of the simplex that corresponds to the function that is optimized by this classifier.
beta - Variable in class de.jstacs.classifier.scoringFunctionBased.gendismix.LogGenDisMixFunction
bgMaxMarkovOrder - Variable in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture
  The order of the background model.
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
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(BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
  Creates a new `BTExplainingAwayResidual` from the corresponding `InstanceParameterSet` `parameters`.
BTExplainingAwayResidual(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
  The standard constructor for the interface `Storable`.
BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures
  Class for the parameters of a `BTExplainingAwayResidual` structure `Measure`.
BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet() - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
  Creates a new `BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet` with empty parameter values.
BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet(double[]) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
  Creates a new `BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet` with the parameter for the equivalent sample sizes set to `ess`.
BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
  The standard constructor for the interface `Storable` .
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
  The standard constructor for the interface `Storable`.
BTMutualInformation(BTMutualInformation.DataSource, double[]) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
  Creates a new mutual information Bayesian tree `Measure`.
BTMutualInformation(BTMutualInformation.BTMutualInformationParameterSet) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
  Creates a new `BTMutualInformation` from the corresponding `InstanceParameterSet` `parameters`.
BTMutualInformation.BTMutualInformationParameterSet - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures
  Class for the parameters of a `BTMutualInformation` structure `Measure`.
BTMutualInformation.BTMutualInformationParameterSet() - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
  Creates a new `BTMutualInformation.BTMutualInformationParameterSet` with empty parameter values.
BTMutualInformation.BTMutualInformationParameterSet(BTMutualInformation.DataSource, double[]) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
  Creates a new `BTMutualInformation.BTMutualInformationParameterSet` with the parameter for the `BTMutualInformation.DataSource` set to `clazz` and the parameter for the equivalent sample sizes (ess) set to `ess`.
BTMutualInformation.BTMutualInformationParameterSet(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
  The standard constructor for the interface `Storable` .
BTMutualInformation.DataSource - Enum in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures
  `Enum` defining the possible sources of data to compute the mutual information.
burnInTest - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
  The `BurnInTest` that is used to stop the sampling.
BurnInTest - Interface in de.jstacs.models.mixture.gibbssampling
  This is the abstract super class for any test of the length of the burn-in phase.
ByteSequence - Class in de.jstacs.data.sequences
  This class is for sequences with the alphabet symbols encoded as `byte`s and can therefore be used for discrete `AlphabetContainer`s with alphabets that use only few symbols.
ByteSequence(AlphabetContainer, byte[]) - Constructor for class de.jstacs.data.sequences.ByteSequence
  Creates a new `ByteSequence` from an array of `byte`- encoded alphabet symbols.
ByteSequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.ByteSequence
  Creates a new `ByteSequence` from a `String` representation using the default delimiter.
ByteSequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.ByteSequence
  Creates a new `ByteSequence` from a `String` representation using the delimiter `delim`.
ByteSequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.ByteSequence
  Creates a new `ByteSequence` from a `SymbolExtractor`.

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