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

N

NA - Static variable in class de.jstacs.results.StorableResult

the Storable cannot be trained anyway.

name - Variable in class de.jstacs.parameters.SimpleParameter

The name of the parameter

name - Variable in class de.jstacs.results.Result

The name of the result

nameTemplate - Variable in class de.jstacs.parameters.ExpandableParameterSet

A template for the name of the enclosing ParameterSetContainer

neededReference - Variable in class de.jstacs.parameters.Parameter

In cases, when the validity of some ParameterSet depends on the value of this Parameter, this variable holds a reference to that ParameterSet

neededReferenceId - Variable in class de.jstacs.parameters.Parameter

In addition to the reference, the id of the ParameterSet is saved, which assists reconstruction from XML.

NegativeDifferentiableFunction - Class in de.jstacs.algorithms.optimization

The function -f for a given function f.

NegativeDifferentiableFunction(DifferentiableFunction) - Constructor for class de.jstacs.algorithms.optimization.NegativeDifferentiableFunction

Creates the function f for which -f should be calculated.

NegativeFunction - Class in de.jstacs.algorithms.optimization

The Function -f for a given function f.

NegativeFunction(Function) - Constructor for class de.jstacs.algorithms.optimization.NegativeFunction

Creates the function f for which -f should be calculated.

NegativeOneDimensionalFunction - Class in de.jstacs.algorithms.optimization

This class extends the class OneDimensionalFunction.

NegativeOneDimensionalFunction(OneDimensionalFunction) - Constructor for class de.jstacs.algorithms.optimization.NegativeOneDimensionalFunction

Creates the function f for which -f should be calculated.

next() - Method in class de.jstacs.models.discrete.inhomogeneous.CombinationIterator

Steps to the next combination.

next() - Method in class de.jstacs.models.discrete.inhomogeneous.SequenceIterator

Changes the internal sequence representation to the next sequence.

next() - Method in class de.jstacs.models.utils.ModelTester.SeqIterator

next() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter

next() - Method in class de.jstacs.parameters.ParameterSet

next() - Method in class de.jstacs.parameters.ParameterSetContainer

next() - Method in interface de.jstacs.parameters.RangeIterator

Switches to the next value in the collection of values in the specified range.

next() - Method in class de.jstacs.parameters.RangeParameter

Returns true if the next element still exists and get be fetched using getValue(), false otherwise

next(int) - Method in class de.jstacs.utils.random.RandomNumberGenerator

nextBeta(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Beta(alpha,beta) (E(X)=a/(a+b) ; Var(X)=ab/[(a+b+1)(a+b)^2])

nextBoolean() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random boolean variable

nextBoolean(double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates true with probability p

nextChiSq() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from ChiSq(1) (E(X)=1 ; Var(X)=2)

nextChiSq(int) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from ChiSq(df) (E(X)=df ; Var(X)=2*df)

nextChiSq(int, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from shifted-ChiSq(df) (E(X)=df+lambda ; Var(X)=2*df)

nextElement() - Method in class de.jstacs.data.DiscreteSequenceEnumerator

nextElement() - Method in class de.jstacs.data.Sample.ElementEnumerator

nextElement() - Method in class de.jstacs.io.SparseStringExtractor

nextElement() - Method in class de.jstacs.io.StringExtractor

nextElement() - Method in class de.jstacs.io.SymbolExtractor

nextExp() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Exp(1) (E(X)=1 ; Var(X)=1)

nextExp(double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Exp(beta) (E(X)=beta ; Var(X)=beta^2)

nextExp(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from shifted-Exp(beta) (E(X)=beta+lambda ; Var(X)=beta^2)

nextGamma() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Gamma(1,1) (E(X)=1 ; Var(X)=1)

nextGamma(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Gamma(alpha,beta) (E(X)=alpha*beta ; Var(X)=alpha*beta^2)

nextGamma(double, double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from shifted-Gamma(alpha,beta) (E(X)=alpha*beta+lambda ; Var(X)=alpha*beta^2)

nextGaussian() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from N(0,1) (E(X)=0 ; Var(X)=1)

nextGaussian(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from N(m,s2) (E(X)=m ; Var(X)=s2)

nextInt() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates an integer between 0 and 2^32

nextInt(int) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates an integer between 0 and n-1 (inclusive)

nextPoisson(double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Poisson(lambda) (E(X)=lambda ; Var(X)=lambda)

nextPoisson() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from Poisson(1) (E(X)=1 ; Var(X)=1)

nextSequence() - Method in class de.jstacs.data.bioJava.SimpleSequenceIterator

nextUniform() - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from U(0,1) (E(X)=1/2 ; Var(X)=1/12)

nextUniform(double, double) - Method in class de.jstacs.utils.random.RandomNumberGenerator

generates a random number from U(a,b) (E(X)=(b-a)/2 ; Var(X)=(b-a)^2/12)

NonParsableException - Exception in de.jstacs

A NonParsable exception is thrown if some object could not be restored from a StringBuffer.

NonParsableException() - Constructor for exception de.jstacs.NonParsableException

Creates a new NonParsableException with standard message ("StringBuffer not parsable.

NonParsableException(String) - Constructor for exception de.jstacs.NonParsableException

Creates a new NonParsableException with your own message.

norm - Variable in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction

Whether a normalization should be done or not.

norm - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

This double contains normalization constant of the instance.

Normalisation - Class in de.jstacs.utils

This class can be used for normalisation of any double array or a part of a double array.

Normalisation() - Constructor for class de.jstacs.utils.Normalisation

normalisation(double[], double) - Static method in class de.jstacs.utils.Normalisation

The method does a normalisation on d using the value v for normalisation.

normalisation(double[], double, double[], int) - Static method in class de.jstacs.utils.Normalisation

The method does a normalisation on d writing the result in dest starting at position start while d remains unchanged.

normalisation(double[], double, int, int) - Static method in class de.jstacs.utils.Normalisation

The method does a sum normalisation on d between start index start and end index end using the value v for the normalisation.

NormalizableScoringFunction - Interface in de.jstacs.scoringFunctions

The interface for normalizable ScoringFunctions.

normalizationConstant - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

Normalization constant to obtain normalized probabilities

normalizeParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree

Normalizes the parameter values to the corresponding log-probabilities.

normalizePlugInParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree

Starts the normalization of the plug in parameters to the log of the MAP-estimates.

NormConditionalLogLikelihood - Class in de.jstacs.classifier.scoringFunctionBased.cll

This class implements the normalized log conditional likelihood.

NormConditionalLogLikelihood(ScoringFunction[], Sample[], double[][], boolean, boolean) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.NormConditionalLogLikelihood

The constructor creates an instance of the log conditional likelihood.

NormConditionalLogLikelihood(ScoringFunction[], Sample[], double[][], LogPrior, boolean, boolean) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.NormConditionalLogLikelihood

The constructor creates an instance using the given prior.

NotTrainedException - Exception in de.jstacs

A NotTrainedException is thrown if the user tries to use an untrained model.

NotTrainedException() - Constructor for exception de.jstacs.NotTrainedException

Creates a new NotTrainedException with standard message ("The model is not trained yet.

NotTrainedException(String) - Constructor for exception de.jstacs.NotTrainedException

Creates a new NotTrainedException with your own message.

NullProgressUpdater - Class in de.jstacs.utils

This class implements a ProgressUpdater doing nothing but forces a crossvalidation that is used with an instance of this class to continue to its end.

NumberValidator<E extends Comparable<? extends Number>> - Class in de.jstacs.parameters.validation

Class that validates all subclasses of Number that implement Comparable (e.g.

NumberValidator(E, E) - Constructor for class de.jstacs.parameters.validation.NumberValidator

Constructs a NumberValidator for a given upper and lower bound.

NumberValidator(StringBuffer) - Constructor for class de.jstacs.parameters.validation.NumberValidator

Constructs a NumberValidator out of a XML representation

NumericalDifferentiableFunction - Class in de.jstacs.algorithms.optimization

This class is the framework for any function f: R^n -> R.

NumericalDifferentiableFunction(double) - Constructor for class de.jstacs.algorithms.optimization.NumericalDifferentiableFunction

Sets the value for epsilon.

NumericalResult - Class in de.jstacs.results

Class for numerical Result values.

NumericalResult(StringBuffer) - Constructor for class de.jstacs.results.NumericalResult

Constructs a NumericalResult from its XML-representation.

NumericalResult(String, String, double) - Constructor for class de.jstacs.results.NumericalResult

The simplified constructor for the primitive type double.

NumericalResult(String, String, int) - Constructor for class de.jstacs.results.NumericalResult

The simplified constructor for the primitive type int.

NumericalResult(String, String, Integer) - Constructor for class de.jstacs.results.NumericalResult

The simplified constructor for the type Integer.

NumericalResult(String, String, long) - Constructor for class de.jstacs.results.NumericalResult

The simplified constructor for the primitive type long.

NumericalResultSet - Class in de.jstacs.results

Class for a set of numerical result values, which are all of the type NumericalResult.

NumericalResultSet(NumericalResult) - Constructor for class de.jstacs.results.NumericalResultSet

Constructs a NumericalResultSet containing one NumericalResult.

NumericalResultSet(NumericalResult[]...) - Constructor for class de.jstacs.results.NumericalResultSet

Constructs a NumericalResultSet from an array of NumericalResults.

NumericalResultSet(LinkedList<? extends NumericalResult>) - Constructor for class de.jstacs.results.NumericalResultSet

Constructs a NumericalResultSet from a LinkedList of NumericalResults.

NumericalResultSet(StringBuffer) - Constructor for class de.jstacs.results.NumericalResultSet

This is the constructor for Storable.

numFreePars - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

The number of free parameters.

nums - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

Used, internally.