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## B

backward(BNDiffSMParameterTree[], int[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
  Computes the backward-part of the normalization constant starting from this `BNDiffSMParameterTree`.
backwardIntermediate - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
  Helper variable = only for internal use.
BasicHigherOrderTransition - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions
  This class implements the basic transition that allows to be trained using the viterbi or the Baum-Welch algorithm.
BasicHigherOrderTransition(boolean[], BasicHigherOrderTransition.AbstractTransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
  The main constructor.
BasicHigherOrderTransition(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
  The standard constructor for the interface `Storable`.
BasicHigherOrderTransition.AbstractTransitionElement - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions
  This class declares the probability distribution for a given context, i.e. it contains all possible transition and the corresponding probabilities for a given set offset previously visited states.
BasicHigherOrderTransition.AbstractTransitionElement(int[], int[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  This is the main constructor creating a new instance with given context, descendant states, and hyper parameters.
BasicHigherOrderTransition.AbstractTransitionElement(int[], int[], double[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  This is the main constructor creating a new instance with given context, descendant states, and hyper parameters.
BasicHigherOrderTransition.AbstractTransitionElement(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  The standard constructor for the interface `Storable`.
BasicPluginTransitionElement - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements
  Basic transition element without random initialization of parameters.
BasicPluginTransitionElement(int[], int[], double[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicPluginTransitionElement
  Constructor creating a new instance with given context, descendant states, and hyper parameters.
BasicPluginTransitionElement(int[], int[], double[], double[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicPluginTransitionElement
  Constructor creating a new instance with given context, descendant states, and hyper parameters.
BasicPluginTransitionElement(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicPluginTransitionElement
  The standard constructor for the interface `Storable`.
BasicTransitionElement - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements
  This class implements the probability distribution for a given context, i.e. it contains all possible transition and the corresponding probabilities for a given set of previously visited states.
BasicTransitionElement(int[], int[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicTransitionElement
  This is the main constructor creating a new instance with given context, descendant states, and hyper parameters.
BasicTransitionElement(int[], int[], double[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicTransitionElement
  This is the main constructor creating a new instance with given context, descendant states, and hyper parameters.
BasicTransitionElement(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicTransitionElement
  The standard constructor for the interface `Storable`.
baumWelch(int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
  This method computes the likelihood and modifies the sufficient statistics according to the Baum-Welch algorithm.
BaumWelchParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training
  This class implements an `HMMTrainingParameterSet` for the Baum-Welch training of an `AbstractHMM`.
BaumWelchParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.BaumWelchParameterSet
  This is the empty constructor that can be used to fill the parameters after creation.
BaumWelchParameterSet(int, AbstractTerminationCondition, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.BaumWelchParameterSet
  This constructor can be used to create an instance with specified parameters.
BaumWelchParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.BaumWelchParameterSet
  The standard constructor for the interface `Storable`.
BayesianNetworkDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
  This class implements a scoring function that is a moral directed graphical model, i.e. a moral Bayesian network.
BayesianNetworkDiffSM(AlphabetContainer, int, double, boolean, Measure) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
  Creates a new `BayesianNetworkDiffSM` that has neither been initialized nor trained.
BayesianNetworkDiffSM(BayesianNetworkDiffSMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
  Creates a new `BayesianNetworkDiffSM` that has neither been initialized nor trained from a `BayesianNetworkDiffSMParameterSet`.
BayesianNetworkDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
  The standard constructor for the interface `Storable`.
BayesianNetworkDiffSMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
  Class for the parameters of a `BayesianNetworkDiffSM`.
BayesianNetworkDiffSMParameterSet(AlphabetContainer, int, double, boolean, Measure) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
  Creates a new `BayesianNetworkDiffSMParameterSet` with pre-defined parameter values.
BayesianNetworkDiffSMParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
  Creates a new `BayesianNetworkDiffSMParameterSet` with empty parameter values.
BayesianNetworkDiffSMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
  Creates a new `BayesianNetworkDiffSMParameterSet` from its XML representation as defined by the `Storable` interface.
BayesianNetworkTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
  The class implements a Bayesian network ( `StructureLearner.ModelType.BN` ) of fixed order.
BayesianNetworkTrainSM(BayesianNetworkTrainSMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
  Creates a new `BayesianNetworkTrainSM` from a given `BayesianNetworkTrainSMParameterSet`.
BayesianNetworkTrainSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
  The standard constructor for the interface `Storable`.
BayesianNetworkTrainSMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters
  The `ParameterSet` for the class `BayesianNetworkTrainSM`.
BayesianNetworkTrainSMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.BayesianNetworkTrainSMParameterSet
  The standard constructor for the interface `Storable`.
BayesianNetworkTrainSMParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.BayesianNetworkTrainSMParameterSet
  The simple constructor for an empty `BayesianNetworkTrainSMParameterSet` for a `BayesianNetworkTrainSM`.
BayesianNetworkTrainSMParameterSet(AlphabetContainer, int, double, String, StructureLearner.ModelType, byte, StructureLearner.LearningType) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.BayesianNetworkTrainSMParameterSet
  This is the constructor of a filled `BayesianNetworkTrainSMParameterSet` for a `BayesianNetworkTrainSM`.
best - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  This field contains the value of objective function of the best start of the training.
beta - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.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.classifiers.differentiableSequenceScoreBased.gendismix.LogGenDisMixFunction
  The mixture parameters of the GenDisMix
bgMaxMarkovOrder - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
  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 `DataSet`s and vice versa.
BioJavaAdapter() - Constructor for class de.jstacs.data.bioJava.BioJavaAdapter
BNDiffSMParameter - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
  Class for the parameters of a `BayesianNetworkDiffSM`.
BNDiffSMParameter(int, byte, int, double, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
  Creates a new `BNDiffSMParameter`, that is `BNDiffSMParameter` no `index` in the list of `BNDiffSMParameter`s of the `BayesianNetworkDiffSM` and responsible for `symbol` at position `position` and pseudo count `pseudoCount`.
BNDiffSMParameter(int, byte, int, int[][], double, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
  Creates a new `BNDiffSMParameter`, that is `BNDiffSMParameter` no `index` in the list of `BNDiffSMParameter`s of the `BayesianNetworkDiffSM` and responsible for `symbol` at position `position` having context `context` and pseudocount `pseudoCount`.
BNDiffSMParameter(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
  The standard constructor for the interface `Storable`.
BNDiffSMParameterTree - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
  Class for the tree that represents the context of a `BNDiffSMParameter` in a `BayesianNetworkDiffSM`.
BNDiffSMParameterTree(int, int[], AlphabetContainer, int, int[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
  Creates a new `BNDiffSMParameterTree` for the parameters at position `pos` using the parent positions in `contextPoss`.
BNDiffSMParameterTree(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
  Recreates a `BNDiffSMParameterTree` from its XML representation as returned by `BNDiffSMParameterTree.toXML()`.
BNDiffSMParameterTree.TreeElement - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
  Class for the nodes of a `BNDiffSMParameterTree`
BNDiffSMParameterTree.TreeElement(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree.TreeElement
  Constructor for the `Storable` interface.
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.sequenceScores.statisticalModels.differentiable.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 `BayesianNetworkDiffSM` .
BTExplainingAwayResidual(double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
  Creates a new explaining away residual Bayesian tree `Measure`.
BTExplainingAwayResidual(BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
  Creates a new `BTExplainingAwayResidual` from the corresponding `InstanceParameterSet` `parameters`.
BTExplainingAwayResidual(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
  The standard constructor for the interface `Storable`.
BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures
  Class for the parameters of a `BTExplainingAwayResidual` structure `Measure`.
BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
  Creates a new `BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet` with empty parameter values.
BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet(double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.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.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
  The standard constructor for the interface `Storable` .
BTMutualInformation - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.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 `BayesianNetworkDiffSM` .
BTMutualInformation(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
  The standard constructor for the interface `Storable`.
BTMutualInformation(BTMutualInformation.DataSource, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
  Creates a new mutual information Bayesian tree `Measure`.
BTMutualInformation(BTMutualInformation.BTMutualInformationParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
  Creates a new `BTMutualInformation` from the corresponding `InstanceParameterSet` `parameters`.
BTMutualInformation.BTMutualInformationParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures
  Class for the parameters of a `BTMutualInformation` structure `Measure`.
BTMutualInformation.BTMutualInformationParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.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.sequenceScores.statisticalModels.differentiable.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.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
  The standard constructor for the interface `Storable` .
BTMutualInformation.DataSource - Enum in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures
  `Enum` defining the possible sources of data to compute the mutual information.
burnInTest - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
  The `BurnInTest`, may be null for no test
BurnInTest - Interface in de.jstacs.sampling
  This is the abstract super class for any test of the length of the burn-in phase.
burnInTest - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
  This variable holds the BurnInTest used for training the model
burnInTest - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  The `BurnInTest` that is used to stop the sampling.
bwdMatrix - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
  matrix for all backward-computed variables; bwdMatrix[l][c] = log P(x_{l+1},...
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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