Uses of Class
de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

Packages that use AbstractNormalizableScoringFunction
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. 
de.jstacs.scoringFunctions.mix.motifSearch   
 

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions
 

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions
 class IndependentProductScoringFunction
          This class enables the user to model parts of a sequence independent of each other.
 class MRFScoringFunction
          This class implements the scoring function for any MRF (Markov Random Field).
 class NormalizedScoringFunction
          This class makes an unnormalized ScoringFunction to a normalized ScoringFunction.
 class UniformScoringFunction
          This ScoringFunction 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 AbstractNormalizableScoringFunction
 AbstractNormalizableScoringFunction AbstractNormalizableScoringFunction.clone()
           
 

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.directedGraphicalModels
 

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.directedGraphicalModels
 class BayesianNetworkScoringFunction
          This class implements a scoring function that is a moral directed graphical model, i.e. a moral Bayesian network.
 class MutableMarkovModelScoringFunction
          This class implements a NormalizableScoringFunction for an inhomogeneous Markov model.
 

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.homogeneous
 

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.homogeneous
 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 AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.mix
 

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.mix
 class AbstractMixtureScoringFunction
          This main abstract class for any mixture scoring function (e.g.
 class MixtureScoringFunction
          This class implements a real mixture model.
 class StrandScoringFunction
          This class enables the user to search on both strand.
 

Uses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.mix.motifSearch
 

Subclasses of AbstractNormalizableScoringFunction in de.jstacs.scoringFunctions.mix.motifSearch
 class DurationScoringFunction
          This class is the super class for all one dimensional position scoring functions that can be used as durations for semi Markov models.
 class HiddenMotifsMixture
          This class handles mixtures with at least one hidden motif.
 class PositionScoringFunction
          This class implements a position scoring function that enables the user to get a score without using a Sequence object.
 class SkewNormalLikeScoringFunction
          This class implements a skew normal like discrete truncated distribution.
 class UniformDurationScoringFunction
          This scoring function implements a uniform distribution for positions.