A B C D E F G H I J K L M N O P Q R S T U V W X

L

L - Variable in class de.jstacs.algorithms.graphs.tensor.Tensor
The number of nodes minus 1.
lastParameters - Variable in class de.jstacs.classifier.scoringFunctionBased.sampling.SamplingScoreBasedClassifier
The last accepted parameters for all samplings, backup for iterative sampling when checking for BurnInTest
lastScore - Variable in class de.jstacs.classifier.scoringFunctionBased.sampling.SamplingScoreBasedClassifier
The scores yielded for the parameters in lastParameters
LearningPrinciple - Enum in de.jstacs.classifier.scoringFunctionBased.gendismix
This enum can be used to obtain the weights for well-known optimization tasks.
length() - Method in class de.jstacs.data.Alphabet
Returns the length of the Alphabet.
length() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
 
length() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
Returns the number of symbols in the calling alphabet.
length - Variable in class de.jstacs.models.AbstractModel
The length of the sequences the model can classify.
length - Variable in class de.jstacs.parameters.SequenceScoringParameterSet
The length of sequences the model can work on or 0 for arbitrary length
length - Variable in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
The length of the modeled sequences.
length() - Method in class de.jstacs.utils.DoubleList
Returns the number of inserted elements.
length() - Method in class de.jstacs.utils.IntList
Returns the number of inserted elements.
lengths - Variable in class de.jstacs.models.CompositeModel
The length for each component.
LEQ - Static variable in interface de.jstacs.parameters.validation.Constraint
The condition is less or equal
LIKELIHOOD_INDEX - Static variable in enum de.jstacs.classifier.scoringFunctionBased.gendismix.LearningPrinciple
This constant is the array index of the weighting factor for the likelihood.
LimitedMedianStartDistance - Class in de.jstacs.algorithms.optimization
This class implements a StartDistanceForecaster that uses the median of a limited memory over the last values.
LimitedMedianStartDistance(int, double) - Constructor for class de.jstacs.algorithms.optimization.LimitedMedianStartDistance
This constructor creates an instance with slots memory slots that will initially be filled with value.
limitedMemoryBFGS(DifferentiableFunction, double[], byte, TerminationCondition, double, StartDistanceForecaster, OutputStream, Time) - Static method in class de.jstacs.algorithms.optimization.Optimizer
The Broyden-Fletcher-Goldfarb-Shanno version of limited memory quasi-Newton methods.
LimitedStringExtractor - Class in de.jstacs.io
This AbstractStringExtractor allows to read only a limited amount of data.
LimitedStringExtractor(AbstractStringExtractor, int) - Constructor for class de.jstacs.io.LimitedStringExtractor
This constructor creates a new instance based on a given AbstractStringExtractor and a maximal number of Strings to be read.
linearizeParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Extracts the Parameters from the leaves of this tree in left-to-right order (as specified by the order of the alphabet) and returns them as a LinkedList.
list - Variable in class de.jstacs.results.ListResult
The internal list of ResultSets that are part of this ListResult
ListResult - Class in de.jstacs.results
Class for a Result that contains a list or a matrix, respectively, of ResultSets.
ListResult(String, String, ResultSet, ResultSet...) - Constructor for class de.jstacs.results.ListResult
Creates a new ListResult from an array of ResultSets and a ResultSet of annotations, which may provide additional information on this ListResult.
ListResult(StringBuffer) - Constructor for class de.jstacs.results.ListResult
The standard constructor for the interface Storable.
llGrad - Variable in class de.jstacs.classifier.scoringFunctionBased.gendismix.LogGenDisMixFunction
Array for the gradient of the log-likelihood
loadParameters() - Method in class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet
Deprecated.  
loadParameters() - Method in class de.jstacs.algorithms.optimization.termination.CombinedCondition.CombinedConditionParameterSet
 
loadParameters() - Method in class de.jstacs.algorithms.optimization.termination.IterationCondition.IterationConditionParameterSet
 
loadParameters() - Method in class de.jstacs.algorithms.optimization.termination.SmallDifferenceOfFunctionEvaluationsCondition.SmallDifferenceOfFunctionEvaluationsConditionParameterSet
 
loadParameters() - Method in class de.jstacs.algorithms.optimization.termination.SmallGradientConditon.SmallGradientConditonParameterSet
 
loadParameters() - Method in class de.jstacs.algorithms.optimization.termination.SmallStepCondition.SmallStepConditionParameterSet
 
loadParameters() - Method in class de.jstacs.algorithms.optimization.termination.TimeCondition.TimeConditionParameterSet
 
loadParameters() - Method in class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
 
loadParameters() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
 
loadParameters() - Method in class de.jstacs.classifier.assessment.RepeatedHoldOutAssessParameterSet
 
loadParameters() - Method in class de.jstacs.classifier.assessment.RepeatedSubSamplingAssessParameterSet
 
loadParameters() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
 
loadParameters() - Method in class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifierParameterSet
 
loadParameters() - Method in class de.jstacs.classifier.scoringFunctionBased.sampling.SamplingGenDisMixClassifierParameterSet
 
loadParameters() - Method in class de.jstacs.classifier.scoringFunctionBased.sampling.SamplingScoreBasedClassifierParameterSet
 
loadParameters() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet
 
loadParameters() - Method in class de.jstacs.data.AlphabetContainerParameterSet
 
loadParameters() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
 
loadParameters() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet.ContinuousAlphabetParameterSet
 
loadParameters() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet.DiscreteAlphabetParameterSet
 
loadParameters() - Method in class de.jstacs.data.alphabets.DNAAlphabet.DNAAlphabetParameterSet
 
loadParameters() - Method in class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet
 
loadParameters() - Method in class de.jstacs.models.discrete.DGMParameterSet
 
loadParameters() - Method in class de.jstacs.models.discrete.homogeneous.parameters.HomogeneousModelParameterSet
 
loadParameters() - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet
 
loadParameters() - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.FSDAGMParameterSet
 
loadParameters() - Method in class de.jstacs.models.hmm.HMMTrainingParameterSet
 
loadParameters() - Method in class de.jstacs.models.hmm.training.MaxHMMTrainingParameterSet
 
loadParameters() - Method in class de.jstacs.models.hmm.training.NumericalHMMTrainingParameterSet
 
loadParameters() - Method in class de.jstacs.models.hmm.training.SamplingHMMTrainingParameterSet
 
loadParameters() - Method in class de.jstacs.parameters.ArrayParameterSet
 
loadParameters() - Method in class de.jstacs.parameters.ExpandableParameterSet
 
loadParameters() - Method in class de.jstacs.parameters.ParameterSet
Loads the parameters for this ParameterSet.
loadParameters() - Method in class de.jstacs.parameters.SimpleParameterSet
 
loadParameters() - Method in class de.jstacs.sampling.AbstractBurnInTestParameterSet
 
loadParameters() - Method in class de.jstacs.sampling.VarianceRatioBurnInTestParameterSet
 
loadParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunctionParameterSet
 
loadParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
 
loadParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
 
loadParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov.InhomogeneousMarkovParameterSet
 
loadParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
 
loadParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
 
LocatedSequenceAnnotation - Class in de.jstacs.data.sequences.annotation
Class for a SequenceAnnotation that has a position on the sequence, e.g for transcription start sites or intron-exon junctions.
LocatedSequenceAnnotation(int, String, String, Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
Creates a new LocatedSequenceAnnotation of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results result.
LocatedSequenceAnnotation(int, String, String, Collection<Result>) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
Creates a new LocatedSequenceAnnotation of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as a Collection of Results result.
LocatedSequenceAnnotation(int, String, String, SequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
Creates a new LocatedSequenceAnnotation of type type with identifier identifier, additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotation and sub-annotations annotations.
LocatedSequenceAnnotation(String, String, LocatedSequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
Creates a new LocatedSequenceAnnotation of type type with identifier identifier, additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotation and sub-annotations annotations.
LocatedSequenceAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
The standard constructor for the interface Storable.
LocatedSequenceAnnotationWithLength - Class in de.jstacs.data.sequences.annotation
Class for a SequenceAnnotation that has a position on the sequence and a length, e.g. for donor splice sites, exons or genes.
LocatedSequenceAnnotationWithLength(int, int, String, String, Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
Creates a new LocatedSequenceAnnotationWithLength of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results result.
LocatedSequenceAnnotationWithLength(int, int, String, String, Collection<Result>) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
Creates a new LocatedSequenceAnnotationWithLength of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as a Collection of Results result.
LocatedSequenceAnnotationWithLength(int, int, String, String, SequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
Creates a new LocatedSequenceAnnotationWithLength of type type with identifier identifier, additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotations and sub-annotations annotations.
LocatedSequenceAnnotationWithLength(String, String, LocatedSequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
Creates a new LocatedSequenceAnnotationWithLength of type type with identifier identifier, additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotations and sub-annotations annotations.
LocatedSequenceAnnotationWithLength(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
The standard constructor for the interface Storable.
logClazz - Variable in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction
The logarithm of the class parameters.
logEmission - Variable in class de.jstacs.models.hmm.models.HigherOrderHMM
Helper variable = only for internal use.
logGammaSum - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This double contains the sum of the logarithm of the gamma functions used in the prior.
LogGenDisMixFunction - Class in de.jstacs.classifier.scoringFunctionBased.gendismix
This class implements the the following function
\[f(\underline{\lambda}|C,D,\underline{\alpha},\underline{\beta})
The weights $\beta_i$ have to sum to 1.
LogGenDisMixFunction(int, ScoringFunction[], Sample[], double[][], LogPrior, double[], boolean, boolean) - Constructor for class de.jstacs.classifier.scoringFunctionBased.gendismix.LogGenDisMixFunction
The constructor for creating an instance that can be used in an Optimizer.
logHiddenNorm - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This double contains the logarithm of the normalization constant of hidden parameters of the instance.
logHiddenPotential - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This array contains the logarithm of the hidden potentials of the instance.
logNorm - Variable in class de.jstacs.models.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
The log-normalization constants for each condition
logNorm - Variable in class de.jstacs.models.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
The log normalization constant based on the parameters.
logNormalizationConstant - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
Normalization constant to obtain normalized probabilities.
LogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
The abstract class for any log-prior used e.g. for maximum supervised posterior optimization.
LogPrior() - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.LogPrior
 
logProb(int, int, Sequence) - Method in class de.jstacs.models.hmm.AbstractHMM
This method computes the logarithm of the probability of the corresponding subsequences.
logProb(int, int, Sequence) - Method in class de.jstacs.models.hmm.models.SamplingHigherOrderHMM
 
logProbFor(Sequence, int, int) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM
 
logProbFor(Sequence, int, int) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel
This method computes the logarithm of the probability of the given Sequence in the given interval.
logSumNormalisation(double[]) - Static method in class de.jstacs.utils.Normalisation
The method does a log-sum-normalisation on d with the values of d given as d[i] = Math.log( val[i] ).
logSumNormalisation(double[], int, int) - Static method in class de.jstacs.utils.Normalisation
The method does a log-sum-normalisation on d between start index startD and end index endD with the values of d given as d[i] = Math.log( val[i] ).
logSumNormalisation(double[], int, int, double[]) - Static method in class de.jstacs.utils.Normalisation
The method does a log-sum-normalisation on d within start index startD and end index endD with the values of d given as d[i] = Math.log( val[i] ).
logSumNormalisation(double[], int, int, double[], int) - Static method in class de.jstacs.utils.Normalisation
The method does a log-sum-normalisation on d between start index startD and end index endD with the values of d given as d[i] = Math.log( val[i] ).
logSumNormalisation(double[], int, int, double[], double[], int) - Static method in class de.jstacs.utils.Normalisation
The method does a log-sum-normalisation on d within start index startD and end index endD with the values of d given logarithmised: d[i] = Math.log( val[i] ).
logSumNormalisation(double[], double) - Static method in class de.jstacs.utils.Normalisation
The method does a log-sum-normalisation on d with the values of d given as d[i] = Math.log( val[i] ) using offset offset.
logSumNormalisation(double[], int, int, double, double[], int) - Static method in class de.jstacs.utils.Normalisation
The method does a log-sum-normalisation on d between start index startD and end index endD with the values of d given as d[i] = Math.log( val[i] ) using offset offset.
logSumNormalisation(double[], int, int, double, double[], double[], int) - Static method in class de.jstacs.utils.Normalisation
The method does a log-sum-normalisation on d between start index startD and end index endD with the values of d given as d[i] = Math.log( val[i] ) using offset offset.
logWeights - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The log probabilities for each component.
lookup - Variable in class de.jstacs.models.hmm.transitions.BasicHigherOrderTransition
The lookup table for spare context en- and decoding.
LT - Static variable in interface de.jstacs.parameters.validation.Constraint
The condition is less than

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