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M

mapDataSet(DataSet[]) - Method in class de.jstacs.classifiers.MappingClassifier
This method maps the given DataSets to the internal classes.
MappedDiscreteSequence - Class in de.jstacs.data.sequences
This class allows to map a discrete Sequence to an new Sequence using some DiscreteAlphabetMappings.
MappedDiscreteSequence(AlphabetContainer, SequenceAnnotation[], DiscreteAlphabetMapping...) - Constructor for class de.jstacs.data.sequences.MappedDiscreteSequence
This method allows to create an empty MappedDiscreteSequence.
MappedDiscreteSequence(SimpleDiscreteSequence, DiscreteAlphabetMapping...) - Constructor for class de.jstacs.data.sequences.MappedDiscreteSequence
This method allows to create a MappedDiscreteSequence from a given Sequence and some given DiscreteAlphabetMappings.
MappingClassifier - Class in de.jstacs.classifiers
This class allows the user to train the classifier on a given number of classes and to evaluate the classifier on a smaller number of classes by mapping classes together.
MappingClassifier(AbstractScoreBasedClassifier, int...) - Constructor for class de.jstacs.classifiers.MappingClassifier
Creates a new MappingClassifier from a given classifier and a class mapping.
MappingClassifier(StringBuffer) - Constructor for class de.jstacs.classifiers.MappingClassifier
The standard constructor for the interface Storable.
MappingDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable
This class implements a DifferentiableStatisticalModel that works on mapped Sequences.
MappingDiffSM(AlphabetContainer, DifferentiableStatisticalModel, DiscreteAlphabetMapping...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
The main constructor creating a MappingDiffSM.
MappingDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
This is the constructor for Storable.
mapWeights(double[][]) - Method in class de.jstacs.classifiers.MappingClassifier
This method maps the given Sequence weights to the internal classes.
MarkovModelDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
This class implements a AbstractDifferentiableStatisticalModel for an inhomogeneous Markov model.
MarkovModelDiffSM(AlphabetContainer, int, double, boolean, int, DurationDiffSM) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
This constructor creates an instance with an prior for the modeled length.
MarkovModelDiffSM(AlphabetContainer, int, double, boolean, InhomogeneousMarkov) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
This constructor creates an instance without any prior for the modeled length.
MarkovModelDiffSM(AlphabetContainer, int, double, boolean, InhomogeneousMarkov, DurationDiffSM) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
This constructor creates an instance with an prior for the modeled length.
MarkovModelDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
The standard constructor for the interface Storable.
MarkovRandomFieldDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable
This class implements the scoring function for any MRF (Markov Random Field).
MarkovRandomFieldDiffSM(AlphabetContainer, int, String) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
This constructor creates an instance of a MarkovRandomFieldDiffSM with equivalent sample size (ess) 0.
MarkovRandomFieldDiffSM(AlphabetContainer, int, double, String) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
This is the main constructor that creates an instance of a MarkovRandomFieldDiffSM.
MarkovRandomFieldDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
This is the constructor for the interface Storable.
matches(int, Sequence) - Method in class de.jstacs.data.sequences.Sequence
This method allows to answer the question whether there is a similar pattern find a match with a given maximal number of mismatches.
MatrixCosts - Class in de.jstacs.algorithms.alignment.cost
Class for matrix costs, i.e., the cost of any match/mismatch is stored in a matrix allowing a huge degree of freedom.
MatrixCosts(double[][], double, double) - Constructor for class de.jstacs.algorithms.alignment.cost.MatrixCosts
Creates a new instance of MatrixCosts where the costs for mismatch and match are given in matrix.
MatrixCosts(double[][], double) - Constructor for class de.jstacs.algorithms.alignment.cost.MatrixCosts
Creates a new instance of MatrixCosts where the costs for mismatch and match are given in matrix.
MatrixCosts(StringBuffer) - Constructor for class de.jstacs.algorithms.alignment.cost.MatrixCosts
Restores MatrixCosts object from its XML representation.
matrixToString(double[][]) - Static method in class de.jstacs.utils.PFMComparator
Returns a string representation of the matrix, where each row of the matrix is printed on one line and columns are separated by tabstops.
max - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
The maximal value.
max(double[], int, int) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
This method returns the index of a maximal entry in the array w between index start and end.
max - Variable in class de.jstacs.utils.DefaultProgressUpdater
The maximal number of steps.
max(int, int) - Method in class de.jstacs.utils.DoubleList
This method computes the maximum of a part of the list.
max(double...) - Static method in class de.jstacs.utils.ToolBox
This method returns the maximum of the elements of an array.
max(int, int, double[]) - Static method in class de.jstacs.utils.ToolBox
This method returns the maximum of the elements of an array between start and end.
MaxHMMTrainingParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training
This class is the super class for any HMMTrainingParameterSet that is used for a maximizing training algorithm of a hidden Markov model.
MaxHMMTrainingParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MaxHMMTrainingParameterSet
This is the empty constructor that can be used to fill the parameters after creation.
MaxHMMTrainingParameterSet(int, AbstractTerminationCondition) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MaxHMMTrainingParameterSet
This constructor can be used to create an instance with specified parameters.
MaxHMMTrainingParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MaxHMMTrainingParameterSet
The standard constructor for the interface Storable.
MAXIMALBRANCHING - Static variable in class de.jstacs.algorithms.graphs.Chu_Liu_Edmonds
Compute the branching yielding the maximum sum of weights.
maximalMarkovOrder - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
The maximal Markov order of the transition.
MaximumCorrelationCoefficient - Class in de.jstacs.classifiers.performanceMeasures
This class implements the maximum of the correlation coefficient $\frac{ TP*TN - FN*FP }{ \sqrt{ (TP+FN)*(TN+FP)*(TP+FP)*(TN+FN) } }$.
MaximumCorrelationCoefficient() - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient
Constructs a new instance of the performance measure MaximumCorrelationCoefficient.
MaximumCorrelationCoefficient(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient
The standard constructor for the interface Storable.
MaximumFMeasure - Class in de.jstacs.classifiers.performanceMeasures
Computes the maximum of the general F-measure given a positive real parameter $\beta$.
MaximumFMeasure() - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure
Constructs a new instance of the performance measure MaximumFMeasure with empty parameters.
MaximumFMeasure(double) - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure
Constructs a new instance of the performance measure MaximumFMeasure with given beta.
MaximumFMeasure(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure
The standard constructor for the interface Storable.
MaximumNumericalTwoClassMeasure - Class in de.jstacs.classifiers.performanceMeasures
This class prepares everything for an easy implementation of a maximum of any numerical performance measure.
MaximumNumericalTwoClassMeasure() - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure
Constructs a new instance of the performance measure MaximumNumericalTwoClassMeasure.
MaximumNumericalTwoClassMeasure(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure
The standard constructor for the interface Storable.
maxInDegree - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
The maximal in-degree of any state.
mean(int, int) - Method in class de.jstacs.utils.DoubleList
This method computes the mean of a part of the list.
mean(int, int, double[]) - Static method in class de.jstacs.utils.ToolBox
This method returns the mean of the elements of an array between start and end.
MeanResultSet - Class in de.jstacs.results
Class that computes the mean and the standard error of a series of NumericalResultSets.
MeanResultSet(boolean, SimpleResult...) - Constructor for class de.jstacs.results.MeanResultSet
Constructs a new MeanResultSet with an empty set of NumericalResultSets and allows to collect all values via the switch aggregateAll.
MeanResultSet(SimpleResult...) - Constructor for class de.jstacs.results.MeanResultSet
Constructs a new MeanResultSet with an empty set of NumericalResultSets.
MeanResultSet() - Constructor for class de.jstacs.results.MeanResultSet
Constructs a new MeanResultSet with an empty set of NumericalResultSets and no further information.
MeanResultSet(StringBuffer) - Constructor for class de.jstacs.results.MeanResultSet
The standard constructor for the interface Storable.
MeanResultSet.AdditionImpossibleException - Exception in de.jstacs.results
Class for the exception that is thrown if two MeanResultSets should be added that do not match.
MeanResultSet.InconsistentResultNumberException - Exception in de.jstacs.results
Class for the exception that is thrown if a NumericalResultSet is added to the MeanResultSet that has a number of results which is not equal to the number of results of the previously added results.
MeanSmoothing(int) - Constructor for class de.jstacs.data.DinucleotideProperty.MeanSmoothing
Creates a new DinucleotideProperty.MeanSmoothing that averages over windows of width width.
meanValue - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.PluginGaussianEmission
Initial mean value.
Measure - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures
Class for structure measures that derive an optimal structure with respect to some criterion within a class of possible structures from data.
Measure(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Creates a new Measure from its XML-representation.
Measure(Measure.MeasureParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Creates a new Measure from its Measure.MeasureParameterSet.
Measure() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Default constructor.
Measure.MeasureParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures
This class is the super class of any ParameterSet that can be used to instantiate a Measure.
MeasureParameterSet(Class<? extends Measure>) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure.MeasureParameterSet
Creates a new empty Measure.MeasureParameterSet for the given sub-class of Measure,
MeasureParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure.MeasureParameterSet
The standard constructor for the interface Storable.
median(int, int) - Method in class de.jstacs.utils.DoubleList
This method computes the median of a part of the list.
median(double...) - Static method in class de.jstacs.utils.ToolBox
This method returns the median of the elements of array.
median(int, int, double[]) - Static method in class de.jstacs.utils.ToolBox
This method returns the median of the elements of an array between start and end.
MedianSmoothing(int) - Constructor for class de.jstacs.data.DinucleotideProperty.MedianSmoothing
Creates a new DinucleotideProperty.MedianSmoothing that computes the median over windows of width width.
MEM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
This class represents a maximum entropy model.
MEM(AbstractList<int[]>, int[], int[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM
The main constructor of a MEM.
MEM(int[], int[], int[][]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM
The main constructor of a MEM.
MEM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM
The constructor for the Storable interface.
MEManager - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
This class is the super class for all maximum entropy models
MEManager(MEManagerParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
Creates a new MEManager from a given MEManagerParameterSet.
MEManager(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
The standard constructor for the interface Storable.
MEManagerParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters
The ParameterSet for any MEManager.
MEManagerParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.MEManagerParameterSet
The constructor for the Storable interface.
MEManagerParameterSet(Class<? extends MEManager>) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.MEManagerParameterSet
The constructor an empty constructor of extended class.
MEManagerParameterSet(Class<? extends MEManager>, AlphabetContainer, int, double, String, ConstraintManager.Decomposition, boolean, byte, double) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.MEManagerParameterSet
The fast constructor.
MEMConstraint - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
This constraint can be used for any maximum entropy model (MEM) application.
MEMConstraint(int[], int[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
Creates a MEMConstraint as part of a (whole) model.
MEMConstraint(int[], int[], int[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
Creates a MEMConstraint as part of a model.
MEMConstraint(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
The standard constructor for the interface Storable.
MEMTools - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
 
MEMTools() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMTools
 
MEMTools.DualFunction - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
The dual function to the constraint problem of learning MEM's.
merge(Hashtable<Sequence, BitSet[]>, int, boolean) - Static method in class de.jstacs.motifDiscovery.KMereStatistic
This method allows to merge the statistics of k-mers by allowing mismatches.
min - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
The minimal value.
min(int, int) - Method in class de.jstacs.utils.DoubleList
This method computes the minimum of a part of the list.
min(double...) - Static method in class de.jstacs.utils.ToolBox
This method returns the minimum of the elements of an array.
min(int, int, double[]) - Static method in class de.jstacs.utils.ToolBox
This method returns the minimum of the elements of an array between start and end.
MINIMALBRANCHING - Static variable in class de.jstacs.algorithms.graphs.Chu_Liu_Edmonds
Compute the branching yielding the minimum sum of weights.
minStepSize - Static variable in class de.jstacs.classifiers.performanceMeasures.PRCurve
The minimum step size between supporting points
MixtureDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture
This class implements a real mixture model.
MixtureDiffSM(int, boolean, DifferentiableStatisticalModel...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
This constructor creates a new MixtureDiffSM.
MixtureDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
This is the constructor for the interface Storable.
MixtureDurationDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif
This class implements a mixture of DurationDiffSMs.
MixtureDurationDiffSM(int, DurationDiffSM...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
The main constructor of a MixtureDurationDiffSM.
MixtureDurationDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
This is the constructor for Storable.
MixtureEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions
This class implements a mixture of Emissions.
MixtureEmission(Emission[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
The main constructor creating a MixtureEmission from a set of emissions.
MixtureEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
The standard constructor for the interface Storable.
MixtureTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture
The class for a mixture model of any TrainableStatisticalModels.
MixtureTrainSM(int, TrainableStatisticalModel[], int, boolean, double[], double[], AbstractMixtureTrainSM.Algorithm, double, TerminationCondition, AbstractMixtureTrainSM.Parameterization, int, int, BurnInTest) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
Creates a new MixtureTrainSM.
MixtureTrainSM(int, TrainableStatisticalModel[], int, double[], double, TerminationCondition, AbstractMixtureTrainSM.Parameterization) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
Creates an instance using EM and estimating the component probabilities.
MixtureTrainSM(int, TrainableStatisticalModel[], double[], int, double, TerminationCondition, AbstractMixtureTrainSM.Parameterization) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
Creates an instance using EM and fixed component probabilities.
MixtureTrainSM(int, TrainableStatisticalModel[], int, double[], int, int, BurnInTest) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
Creates an instance using Gibbs Sampling and sampling the component probabilities.
MixtureTrainSM(int, TrainableStatisticalModel[], double[], int, int, int, BurnInTest) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
Creates an instance using Gibbs Sampling and fixed component probabilities.
MixtureTrainSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
The constructor for the interface Storable.
model - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
The model for the sequences.
models - Variable in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
models - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
The models for the components
modify(int, int) - Method in interface de.jstacs.motifDiscovery.Mutable
Manually modifies the model.
modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
 
modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
modify(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
This method modifies the underlying AlphabetContainer.
modify(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
modify(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
modify(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
modify(double[], double[], int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
This method modifies the computed weights for one sequence and returns the score.
modifyFunctionValue(double) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier
 
modifyFunctionValue(double) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
Allows for a modification of the value returned by the function obtained by SamplingScoreBasedClassifier.getFunction(DataSet[], double[][]).
modifyMotif(int, int, int) - Method in interface de.jstacs.motifDiscovery.MutableMotifDiscoverer
Manually modifies the motif model with index motifIndex.
modifyMotif(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
modifyMotif(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
modifyMotif(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
modifyMotif(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
modifyWeights(double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
This method modifies the computed weights for one sequence and returns the score.
MotifAnnotation - Class in de.jstacs.data.sequences.annotation
Class for a StrandedLocatedSequenceAnnotationWithLength that is a motif.
MotifAnnotation(String, int, int, StrandedLocatedSequenceAnnotationWithLength.Strand, Result...) - Constructor for class de.jstacs.data.sequences.annotation.MotifAnnotation
Creates a new MotifAnnotation of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotation.
MotifAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.MotifAnnotation
The standard constructor for the interface Storable.
MotifAnnotationParser - Class in de.jstacs.data.sequences.annotation
Annotation parser for MotifAnnotations.
MotifAnnotationParser() - Constructor for class de.jstacs.data.sequences.annotation.MotifAnnotationParser
Creates a new MotifAnnotationParser with default delimiters.
MotifAnnotationParser(String, String) - Constructor for class de.jstacs.data.sequences.annotation.MotifAnnotationParser
Creates a new MotifAnnotationParser with the supplied delimiters
MotifDiscoverer - Interface in de.jstacs.motifDiscovery
This is the interface that any tool for de-novo motif discovery should implement.
MotifDiscoverer.KindOfProfile - Enum in de.jstacs.motifDiscovery
This enum can be used to determine which kind of profile should be returned.
MotifDiscovererToolBox - Class in de.jstacs.motifDiscovery
This class contains static methods for the MotifDiscoverer.
MotifDiscovererToolBox() - Constructor for class de.jstacs.motifDiscovery.MotifDiscovererToolBox
 
MotifDiscoveryAssessment - Class in de.jstacs.motifDiscovery
This class enables the user to assess the prediction of motif occurrences
MotifDiscoveryAssessment() - Constructor for class de.jstacs.motifDiscovery.MotifDiscoveryAssessment
 
motifLength - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
The length of the motif.
MRGParams - Class in de.jstacs.utils.random
The super container for parameter of multivariate random generators.
MRGParams() - Constructor for class de.jstacs.utils.random.MRGParams
 
MSPClassifier - Class in de.jstacs.classifiers.differentiableSequenceScoreBased.msp
This class implements a classifier that allows the training via MCL or MSP principle.
MSPClassifier(GenDisMixClassifierParameterSet, DifferentiableSequenceScore...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier
This convenience constructor creates an MSPClassifier that used MCL principle for training.
MSPClassifier(GenDisMixClassifierParameterSet, LogPrior, DifferentiableSequenceScore...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier
The default constructor that creates a new MSPClassifier from a given parameter set, a prior and DifferentiableSequenceScores for the classes.
MSPClassifier(GenDisMixClassifierParameterSet, LogPrior, double, DifferentiableSequenceScore...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier
This constructor that creates a new MSPClassifier from a given parameter set, a prior and DifferentiableSequenceScores for the classes.
MSPClassifier(StringBuffer) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier
This is the constructor for Storable.
MST - Class in de.jstacs.algorithms.graphs
This class enables you to compute the maximal spanning forest for an undirected, weighted graph.
MST() - Constructor for class de.jstacs.algorithms.graphs.MST
 
MultiDimensionalArbitrarySequence - Class in de.jstacs.data.sequences
This class is for multidimensional arbitrary sequences.
MultiDimensionalArbitrarySequence(SequenceAnnotation[], ArbitrarySequence...) - Constructor for class de.jstacs.data.sequences.MultiDimensionalArbitrarySequence
This constructor creates an MultiDimensionalDiscreteSequence from a set of individual Sequences.
MultiDimensionalDiscreteSequence - Class in de.jstacs.data.sequences
This class is for multidimensional discrete sequences that can be used, for instance, for phylogenetic footprinting.
MultiDimensionalDiscreteSequence(SequenceAnnotation[], SimpleDiscreteSequence...) - Constructor for class de.jstacs.data.sequences.MultiDimensionalDiscreteSequence
This constructor creates an MultiDimensionalDiscreteSequence from a set of individual Sequences.
MultiDimensionalSequence<T> - Class in de.jstacs.data.sequences
This class is for multidimensional sequences that can be used, for instance, for phylogenetic footprinting.
MultiDimensionalSequence(SequenceAnnotation[], Sequence...) - Constructor for class de.jstacs.data.sequences.MultiDimensionalSequence
This constructor creates an MultiDimensionalSequence from a set of individual Sequences.
MultiDimensionalSequenceWrapperDiffSS - Class in de.jstacs.sequenceScores.differentiable
This class implements a simple wrapper for multidimensional sequences.
MultiDimensionalSequenceWrapperDiffSS(DifferentiableSequenceScore) - Constructor for class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
The main constructor.
MultiDimensionalSequenceWrapperDiffSS(StringBuffer) - Constructor for class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
This is the constructor for Storable.
MultilineSimpleParameter - Class in de.jstacs.tools.ui.galaxy
An extension of SimpleParameter that renders as a textarea in Galaxy, which is only suitable for DataType.STRINGs.
MultilineSimpleParameter(String, String, boolean, Object) - Constructor for class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter
Creates a new MultilineSimpleParameter with given default value.
MultilineSimpleParameter(String, String, boolean, ParameterValidator, Object) - Constructor for class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter
Creates a new MultilineSimpleParameter with given default value and a ParameterValidator.
MultilineSimpleParameter(String, String, boolean, ParameterValidator) - Constructor for class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter
Creates a new MultilineSimpleParameter with no default value and a ParameterValidator.
MultilineSimpleParameter(String, String, boolean) - Constructor for class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter
Creates a new MultilineSimpleParameter with no default value.
MultilineSimpleParameter(StringBuffer) - Constructor for class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter
The standard constructor for the interface Storable.
MultipleIterationsCondition - Class in de.jstacs.algorithms.optimization.termination
This TerminationCondition requires another provided TerminationCondition to fail a contiguous specified number of times before the optimization is terminated.
MultipleIterationsCondition(int, AbstractTerminationCondition) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition
This constructor creates an instance that stops the optimization if provided termination condition fails a contiguously a specified number of times.
MultipleIterationsCondition(MultipleIterationsCondition.MultipleIterationsConditionParameterSet) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition
This is the main constructor creating an instance from a given parameter set.
MultipleIterationsCondition(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition
The standard constructor for the interface Storable.
MultipleIterationsCondition.MultipleIterationsConditionParameterSet - Class in de.jstacs.algorithms.optimization.termination
This class implements the parameter set for a MultipleIterationsCondition.
MultipleIterationsConditionParameterSet() - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition.MultipleIterationsConditionParameterSet
This constructor creates an empty parameter set.
MultipleIterationsConditionParameterSet(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition.MultipleIterationsConditionParameterSet
The standard constructor for the interface Storable.
MultipleIterationsConditionParameterSet(int, AbstractTerminationCondition) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition.MultipleIterationsConditionParameterSet
This constructor creates a filled instance of the parameter set.
multiply(int, int, double) - Method in class de.jstacs.utils.DoubleList
Multiplies all values in the list from index start to end with the value factor.
multiplyExpLambdaWith(int, double) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
Multiplies the exponential value of $\lambda_{index}$ with the factor val: $\exp(\lambda_{index}) \cdot val$.
MultiSelectionParameter - Class in de.jstacs.parameters
Class for a Parameter that provides a collection of possible values.
MultiSelectionParameter(DataType, String[], Object[], String, String, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionParameter
Constructor for a MultiSelectionParameter.
MultiSelectionParameter(DataType, String[], Object[], String[], String, String, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionParameter
Constructor for a MultiSelectionParameter.
MultiSelectionParameter(String, String, boolean, ParameterSet...) - Constructor for class de.jstacs.parameters.MultiSelectionParameter
Creates a new MultiSelectionParameter from an array of ParameterSets.
MultiSelectionParameter(String, String, boolean, Class<? extends ParameterSet>...) - Constructor for class de.jstacs.parameters.MultiSelectionParameter
Creates a new MultiSelectionParameter from an array of Classes of ParameterSets.
MultiSelectionParameter(StringBuffer) - Constructor for class de.jstacs.parameters.MultiSelectionParameter
The standard constructor for the interface Storable.
MultiThreadedFunction - Interface in de.jstacs.algorithms.optimization
This interface defines methods for functions that are multi-threaded.
MultiThreadedTrainingParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training
This class is the super class for any MaxHMMTrainingParameterSet that is used for a multi-threaded maximizing training algorithm of a hidden Markov model.
MultiThreadedTrainingParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MultiThreadedTrainingParameterSet
This is the empty constructor that can be used to fill the parameters after creation.
MultiThreadedTrainingParameterSet(int, AbstractTerminationCondition, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MultiThreadedTrainingParameterSet
This constructor can be used to create an instance with specified parameters.
MultiThreadedTrainingParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MultiThreadedTrainingParameterSet
The standard constructor for the interface Storable.
MultivariateGaussianEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous
Multivariate Gaussian emission density for a Hidden Markov Model.
MultivariateGaussianEmission(double[], double[], double[][], double, double[], double, double[][]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
Creates a Multivariate Gaussian emission density.
MultivariateGaussianEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
Creates a MultivariateGaussianEmission from its XML representation.
MultivariateRandomGenerator - Class in de.jstacs.utils.random
This class is the abstract super class for any multivariate random generator (MRG).
MultivariateRandomGenerator() - Constructor for class de.jstacs.utils.random.MultivariateRandomGenerator
 
mus - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateGaussianLogPrior
The means
Mutable - Interface in de.jstacs.motifDiscovery
This interface allows to modify a motif model.
MutableMotifDiscoverer - Interface in de.jstacs.motifDiscovery
This is the interface that any tool for de-novo motif discovery should implement that allows any modify-operations like shift, shrink and expand.
MutableMotifDiscovererToolbox - Class in de.jstacs.motifDiscovery
This class contains some important methods for the initiation and optimization of MutableMotifDiscoverer.
MutableMotifDiscovererToolbox() - Constructor for class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
 
MutableMotifDiscovererToolbox.InitMethodForDiffSM - Enum in de.jstacs.motifDiscovery
myAbstractClassifier - Variable in class de.jstacs.classifiers.assessment.ClassifierAssessment
This array contains the internal used classifiers.
myModel - Variable in class de.jstacs.classifiers.assessment.ClassifierAssessment
This array contains for each class the internal used models.
myTempMeanResultSets - Variable in class de.jstacs.classifiers.assessment.ClassifierAssessment
The temporary result set.
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