Uses of Interface
de.jstacs.scoringFunctions.ScoringFunction

Packages that use ScoringFunction
de.jstacs.classifier.scoringFunctionBased Provides the classes for Classifiers that are based on ScoringFunctions. 
de.jstacs.classifier.scoringFunctionBased.cll Provides the implementation of the log conditional likelihood as an OptimizableFunction and a classifier that uses log conditional likelihood or supervised posterior to learn the parameters of a set of ScoringFunctions 
de.jstacs.classifier.scoringFunctionBased.logPrior Provides a general definition of a parameter log-prior and a number of implementations of Laplace and Gaussian priors 
de.jstacs.scoringFunctions Provides ScoringFunctions that can be used in a ScoreClassifier
de.jstacs.scoringFunctions.directedGraphicalModels Provides ScoringFunctions that are equivalent to directed graphical models. 
de.jstacs.scoringFunctions.homogeneous Provides ScoringFunctions that are homogeneous, i.e. model probabilities or scores independent of the position within a sequence 
de.jstacs.scoringFunctions.mix Provides ScoringFunctions that are mixtures of other ScoringFunctions. 
 

Uses of ScoringFunction in de.jstacs.classifier.scoringFunctionBased
 

Fields in de.jstacs.classifier.scoringFunctionBased declared as ScoringFunction
protected  ScoringFunction[] ScoreClassifier.score
          The internally used scoring functions.
 

Methods in de.jstacs.classifier.scoringFunctionBased that return ScoringFunction
 ScoringFunction ScoreClassifier.getScoringFunction(int i)
          Returns the internally used ScoringFunction with index i.
 ScoringFunction[] ScoreClassifier.getScoringFunctions()
          Returns all internally used ScoringFunctions in the internal order.
 

Methods in de.jstacs.classifier.scoringFunctionBased with parameters of type ScoringFunction
abstract  void OptimizableFunction.reset(ScoringFunction[] score)
          Resets the scoringFunctions and all precomputed values.
 

Constructors in de.jstacs.classifier.scoringFunctionBased with parameters of type ScoringFunction
ScoreClassifier(ScoreClassifierParameterSet params, ScoringFunction... score)
          The default constructor.
 

Uses of ScoringFunction in de.jstacs.classifier.scoringFunctionBased.cll
 

Methods in de.jstacs.classifier.scoringFunctionBased.cll with parameters of type ScoringFunction
static CLLClassifier[] CLLClassifier.create(CLLClassifierParameterSet params, LogPrior prior, ScoringFunction[]... functions)
          This method creates an array of CLLClassifier by using the cross-product of the given ScoringFunctions.
 void NormConditionalLogLikelihood.reset(ScoringFunction[] funs)
           
 

Constructors in de.jstacs.classifier.scoringFunctionBased.cll with parameters of type ScoringFunction
CLLClassifier(CLLClassifierParameterSet params, LogPrior prior, ScoringFunction... score)
          The default constructor.
CLLClassifier(CLLClassifierParameterSet params, ScoringFunction... score)
          The default constructor.
NormConditionalLogLikelihood(ScoringFunction[] score, Sample[] data, double[][] weights, boolean norm, boolean freeParams)
          The constructor creates an instance of the log conditional likelihood.
NormConditionalLogLikelihood(ScoringFunction[] score, Sample[] data, double[][] weights, LogPrior prior, boolean norm, boolean freeParams)
          The constructor creates an instance using the given prior.
 

Uses of ScoringFunction in de.jstacs.classifier.scoringFunctionBased.logPrior
 

Methods in de.jstacs.classifier.scoringFunctionBased.logPrior with parameters of type ScoringFunction
 void SeparateLogPrior.set(boolean freeParameters, ScoringFunction... funs)
           
 void LogPrior.set(boolean freeParameters, ScoringFunction... funs)
          Resets all pre-computed values to their initial values using the ScoringFunctions funs
 

Uses of ScoringFunction in de.jstacs.scoringFunctions
 

Subinterfaces of ScoringFunction in de.jstacs.scoringFunctions
 interface NormalizableScoringFunction
          The interface for normalizable ScoringFunctions.
 

Classes in de.jstacs.scoringFunctions that implement ScoringFunction
 class AbstractNormalizableScoringFunction
          This class is the main part of any ScoreClassifier.
 class IndependentProductScoringFunction
          This class enables the user to model parts of the sequence independent of each other.
 class MRFScoringFunction
          This class implements the scoring function for any MRF.
 class UniformScoringFunction
          This scoring function does nothing.
 class VariableLengthScoringFunction
          This is the main class for all ScoringFunctions that allow to score subsequences of arbitrary length.
 

Methods in de.jstacs.scoringFunctions that return ScoringFunction
 ScoringFunction ScoringFunction.clone()
          Creates a clone (deep copy) of the current ScoringFunction instance.
 

Uses of ScoringFunction in de.jstacs.scoringFunctions.directedGraphicalModels
 

Classes in de.jstacs.scoringFunctions.directedGraphicalModels that implement ScoringFunction
 class BayesianNetworkScoringFunction
          This class implements a scoring function that is a moral directed graphical model, i.e. a moral Bayesian network.
 

Uses of ScoringFunction in de.jstacs.scoringFunctions.homogeneous
 

Classes in de.jstacs.scoringFunctions.homogeneous that implement ScoringFunction
 class HMM0ScoringFunction
          This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.
 class HMMScoringFunction
          This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.
 class HomogeneousScoringFunction
          This is the main class for all homogeneous ScoringFunctions.
 class UniformHomogeneousScoringFunction
          This scoring function does nothing.
 

Uses of ScoringFunction in de.jstacs.scoringFunctions.mix
 

Classes in de.jstacs.scoringFunctions.mix that implement ScoringFunction
 class AbstractMixtureScoringFunction
          This main abstract class for any mixture (e.g.
 class MixtureScoringFunction
          This class implements a real mixture model.