- backward(BNDiffSMParameterTree[], int[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.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.
- 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.
- 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
-
- 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.
- BayesianNetworkDiffSM(AlphabetContainer, int, double, boolean, Measure) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
- BayesianNetworkDiffSM(BayesianNetworkDiffSMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
- 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
-
- BayesianNetworkDiffSMParameterSet(AlphabetContainer, int, double, boolean, Measure) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
-
- BayesianNetworkDiffSMParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
-
- BayesianNetworkDiffSMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
-
- BayesianNetworkTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
-
- BayesianNetworkTrainSM(BayesianNetworkTrainSMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
-
- 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
-
- 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
-
- BayesianNetworkTrainSMParameterSet(AlphabetContainer, int, double, String, StructureLearner.ModelType, byte, StructureLearner.LearningType) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.BayesianNetworkTrainSMParameterSet
-
- 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
- BGIS - Static variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMTools
-
This constant can be used to specify that the model should use the blockwise iterative scaling
for training.
- BGIS_P - Static variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMTools
-
This constant can be used to specify that the model should use the blockwise iterative scaling
for training.
- bgMaxMarkovOrder - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
-
The order of the background model.
- binarySearch(int, int, int) - Method in class de.jstacs.utils.IntList
-
- BioJavaAdapter - Class in de.jstacs.data.bioJava
-
- BioJavaAdapter() - Constructor for class de.jstacs.data.bioJava.BioJavaAdapter
-
- BNDiffSMParameter - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
-
- BNDiffSMParameter(int, byte, int, double, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
-
- BNDiffSMParameter(int, byte, int, int[][], double, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
-
- 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
-
- 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
-
- BNDiffSMParameterTree.TreeElement - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
-
- 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
-
- 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
-
- BTExplainingAwayResidualParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
-
- BTExplainingAwayResidualParameterSet(double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
-
- 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
-
- BTMutualInformation.BTMutualInformationParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures
-
- 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.
- BTMutualInformationParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
-
- BTMutualInformationParameterSet(BTMutualInformation.DataSource, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
-
- BTMutualInformationParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
-
The standard constructor for the interface
Storable
.
- burnInLength - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
-
- burnInTest - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
-
- 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
-
- 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},...,x_L | (s_{l-order+1},...,s_l)=c , parameter)
- 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
-
- ByteSequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.ByteSequence
-
- ByteSequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.ByteSequence
-