Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV LETTER NEXT LETTER | FRAMES NO FRAMES

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 `Parameter`s 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 the interface `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
mean(int, int) - Method in class de.jstacs.utils.DoubleList
  This method computes the mean of a part of the list.
MeanResultSet - Class in de.jstacs.results
  Class that computes the mean and the standard error of a series of `NumericalResultSet`s.
MeanResultSet(SimpleResult...) - Constructor for class de.jstacs.results.MeanResultSet
  Constructs a new `MeanResultSet` with an empty set of `NumericalResultSet`s.
MeanResultSet() - Constructor for class de.jstacs.results.MeanResultSet
  Constructs a new `MeanResultSet` with an empty set of `NumericalResultSet`s 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
  Recreates 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 `Model`s.
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 the interface `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
modify(double[], double[], int, int) - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture
  This method modifies the computed weights for one sequence and returns the score.
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()`.
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
motifLength - Variable in class de.jstacs.models.mixture.motif.positionprior.PositionPrior
  The length of the motif.
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 values 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[], String, String, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionCollectionParameter
  Creates a new `MultiSelectionCollectionParameter` from an array of `ParameterSet`s.
MultiSelectionCollectionParameter(InstanceParameterSet[], String, String, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionCollectionParameter
  Creates a new `MultiSelectionCollectionParameter` from an array of `ParameterSet`s.
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 (MRG).
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
  `true` or `false`
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
  The temporary result set.

Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV LETTER NEXT LETTER | FRAMES NO FRAMES

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