Package de.jstacs.scoringFunctions

Provides ScoringFunctions that can be used in a ScoreClassifier.

See:
Description

Interface Summary

NormalizableScoringFunction	The interface for normalizable ScoringFunctions.
ScoringFunction	This interface is the main part of any ScoreClassifier.

Class Summary

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

Package de.jstacs.scoringFunctions Description

Provides ScoringFunctions that can be used in a ScoreClassifier. Among the currently implemented ScoringFunctions are

• the BayesianNetworkScoringFunction, which provides structure learning for inhomogeneous Markov models, Bayesian trees, and permuted Markov models,
• the MixtureScoringFunction for mixtures of ScoringFunctions, and
• homogeneous ScoringFunctions.