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

M

main(String[]) - Static method in class de.jstacs.classifier.Classification
This main method computes some performance measures for two given score files
makeRanged() - Method in class de.jstacs.parameters.ParameterSet
Replaces all Parameters in this ParameterSet by their equivalents implementing the Rangeable interface.
MappingClassifier - Class in de.jstacs.classifier
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.classifier.MappingClassifier
The main constructor.
MappingClassifier(StringBuffer) - Constructor for class de.jstacs.classifier.MappingClassifier
This is the constructor for Storable.
mapSample(Sample[]) - Method in class de.jstacs.classifier.MappingClassifier
This method maps the Samples to the internal classes.
max(double[], int, int) - Static method in class de.jstacs.models.mixture.AbstractMixtureModel
This method returns the index of a maximal entry in the array w betwwen index start and end.
max - Variable in class de.jstacs.utils.DefaultProgressUpdater
The maximal number of steps.
MAXIMALBRANCHING - Static variable in class de.jstacs.algorithms.graphs.Chu_Liu_Edmonds
Compute the branching yielding the maximum sum of weights
MeanResultSet - Class in de.jstacs.results
Class that computes the mean and the standard error of a series of NumericalResultSets.
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 constructor for a model in xml format.
MeanResultSet.AdditionImpossibleException - Exception in de.jstacs.results
Class for the exception that is thrown if two MeanResultSet should be added that do not match.
MeanResultSet.AdditionImpossibleException() - Constructor for exception de.jstacs.results.MeanResultSet.AdditionImpossibleException
Constructs a new AdditionImpossibleException with an appropriate error message.
MeanResultSet.InconsistentResultNumberException - Exception in de.jstacs.results
Class for the exception that is thrown if an 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.
MeanResultSet.InconsistentResultNumberException() - Constructor for exception de.jstacs.results.MeanResultSet.InconsistentResultNumberException
Constructs a new InconsistentResultNumberException with an appropriate error message.
Measure - Class in de.jstacs.scoringFunctions.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() - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
 
MeasureParameters - Class in de.jstacs.classifier
This class holds the parameters for evaluate-methods of a classifier.
MeasureParameters(boolean) - Constructor for class de.jstacs.classifier.MeasureParameters
This constructor creates a new empty instance of MeasureParameters.
MeasureParameters(boolean, double, double, double) - Constructor for class de.jstacs.classifier.MeasureParameters
This constructor creates a new instance of MeasureParameters.
MeasureParameters(boolean, double, double, double, double, double, int, RangeParameter.Scale) - Constructor for class de.jstacs.classifier.MeasureParameters
 
MeasureParameters(StringBuffer) - Constructor for class de.jstacs.classifier.MeasureParameters
Re-creates a MeasureParameters instance from its XML-representation as returned by MultiSelectionCollectionParameter.toXML().
MeasureParameters.Measure - Enum in de.jstacs.classifier
This Enum defines all measures that are currently implemented in Jstacs.
MEMConstraint - Class in de.jstacs.models.discrete.inhomogeneous
The constraint can be used for any MEM application.
MEMConstraint(int[], int[]) - Constructor for class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Creates a MEMConstraint as part of a (whole) model
MEMConstraint(int[], int[], int[]) - Constructor for class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Creates a MEMConstraint as part of a model
MEMConstraint(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Creates a MEMConstraint from a StringBuffer
MINIMALBRANCHING - Static variable in class de.jstacs.algorithms.graphs.Chu_Liu_Edmonds
Compute the branching yielding the minimum sum of weights
MixtureModel - Class in de.jstacs.models.mixture
Class for a mixture model of any Models.
MixtureModel(int, Model[], int, boolean, double[], double[], AbstractMixtureModel.Algorithm, double, double, AbstractMixtureModel.Parameterization, int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.MixtureModel
Creates a new MixtureModel.
MixtureModel(int, Model[], int, double[], double, double, AbstractMixtureModel.Parameterization) - Constructor for class de.jstacs.models.mixture.MixtureModel
Creates an instance using EM and estimating the component probabilities.
MixtureModel(int, Model[], double[], int, double, double, AbstractMixtureModel.Parameterization) - Constructor for class de.jstacs.models.mixture.MixtureModel
Creates an instance using EM and fixed component probabilities.
MixtureModel(int, Model[], int, double[], int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.MixtureModel
Creates an instance using Gibbs Sampling and sampling the component probabilities.
MixtureModel(int, Model[], double[], int, int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.MixtureModel
Creates an instance using Gibbs Sampling and fixed component probabilities.
MixtureModel(StringBuffer) - Constructor for class de.jstacs.models.mixture.MixtureModel
The constructor for the interface Storable.
MixtureScoringFunction - Class in de.jstacs.scoringFunctions.mix
This class implements a real mixture model.
MixtureScoringFunction(int, boolean, NormalizableScoringFunction...) - Constructor for class de.jstacs.scoringFunctions.mix.MixtureScoringFunction
This constructor creates a mixture.
MixtureScoringFunction(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.mix.MixtureScoringFunction
This is the constructor for Storable.
model - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The model for the sequences.
Model - Interface in de.jstacs.models
This interface defines all methods for a probabilistic model.
ModelBasedClassifier - Class in de.jstacs.classifier.modelBased
This class is the main class for all model based classifiers.
ModelBasedClassifier(boolean, Model...) - Constructor for class de.jstacs.classifier.modelBased.ModelBasedClassifier
This constructor creates a new instance with the given models and clones these if necessary.
ModelBasedClassifier(Model...) - Constructor for class de.jstacs.classifier.modelBased.ModelBasedClassifier
The default constructor.
ModelBasedClassifier(StringBuffer) - Constructor for class de.jstacs.classifier.modelBased.ModelBasedClassifier
This is the constructor for Storable.
models - Variable in class de.jstacs.classifier.modelBased.ModelBasedClassifier
The internal models.
models - Variable in class de.jstacs.models.CompositeModel
The models for the components
ModelTester - Class in de.jstacs.models.utils
This class is useful for some test for any (discrete) models.
ModelTester() - Constructor for class de.jstacs.models.utils.ModelTester
 
ModelTester.SeqIterator - Class in de.jstacs.models.utils
 
ModelTester.SeqIterator(AlphabetContainer, int) - Constructor for class de.jstacs.models.utils.ModelTester.SeqIterator
 
modifyWeights(double[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
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 StrandedLocatedSequenceAnnotationWithLength of type type, with identifier identifier, and additional annotation (that does not fit the SequenceAnnotation definitions) additionalAnnotation.
MotifAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.MotifAnnotation
Re-creates a MotifAnnotation from its XML-representation as returned by StrandedLocatedSequenceAnnotationWithLength.toXML().
MRFScoringFunction - Class in de.jstacs.scoringFunctions
This class implements the scoring function for any MRF.
MRFScoringFunction(AlphabetContainer, int, String) - Constructor for class de.jstacs.scoringFunctions.MRFScoringFunction
This constructor creates an instance with ess 0.
MRFScoringFunction(AlphabetContainer, int, double, String) - Constructor for class de.jstacs.scoringFunctions.MRFScoringFunction
This is the main constructor.
MRFScoringFunction(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.MRFScoringFunction
This is the constructor for Storable.
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
 
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
 
multiply(int, int, double) - Method in class de.jstacs.utils.DoubleList
Multiplies all value in the list from index start to end with the value factor
multiplyExpLambdaWith(int, double) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Multiplies \exp(\lambda_{index}) with val
MultiSelectionCollectionParameter - Class in de.jstacs.parameters
Class for a Parameter that provides a collection of possible values.
MultiSelectionCollectionParameter(DataType, String[], Object[], String, String, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionCollectionParameter
Constructor for a MultiSelectionCollectionParameter.
MultiSelectionCollectionParameter(DataType, String[], Object[], String[], String, String, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionCollectionParameter
Constructor for a MultiSelectionCollectionParameter.
MultiSelectionCollectionParameter(ParameterSet[], String, String, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionCollectionParameter
Creates a new MultiSelectionCollectionParameter from an array of ParameterSets.
MultiSelectionCollectionParameter(StringBuffer) - Constructor for class de.jstacs.parameters.MultiSelectionCollectionParameter
Creates a new MultiSelectionCollectionParameter from its XML-representation
MultiSelectionCollectionParameter(ParameterSet, boolean[], boolean[], boolean, String, String, boolean, DataType, String, int, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionCollectionParameter
Creates a new MultiSelectionCollectionParameter from the necessary field.
MultivariateRandomGenerator - Class in de.jstacs.utils.random
This class is the abstract super class for any multivariate random generator.
MultivariateRandomGenerator() - Constructor for class de.jstacs.utils.random.MultivariateRandomGenerator
 
myAbstractClassifier - Variable in class de.jstacs.classifier.assessment.ClassifierAssessment
This array contains the internal used classifiers.
myBuildClassifierByCrossProduct - Variable in class de.jstacs.classifier.assessment.ClassifierAssessment
 
myModel - Variable in class de.jstacs.classifier.assessment.ClassifierAssessment
This array contains for each class the internal used models.
myTempMeanResultSets - Variable in class de.jstacs.classifier.assessment.ClassifierAssessment
 

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