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