Uses of Class
de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore

Packages that use AbstractDifferentiableSequenceScore

Package	Description
de.jstacs.sequenceScores.differentiable
de.jstacs.sequenceScores.differentiable.logistic
de.jstacs.sequenceScores.statisticalModels.differentiable	Provides all DifferentiableStatisticalModels, which can compute the gradient with respect to their parameters for a given input Sequence.
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels	Provides DifferentiableStatisticalModels that are directed graphical models.
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous	Provides DifferentiableStatisticalModels that are homogeneous, i.e.
de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture	Provides DifferentiableSequenceScores that are mixtures of other DifferentiableSequenceScores.
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif

Uses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.differentiable

Subclasses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.differentiable

Modifier and Type	Class and Description
class	IndependentProductDiffSS This class enables the user to model parts of a sequence independent of each other.
class	MultiDimensionalSequenceWrapperDiffSS This class implements a simple wrapper for multidimensional sequences.
class	UniformDiffSS This DifferentiableSequenceScore does nothing.

Methods in de.jstacs.sequenceScores.differentiable that return AbstractDifferentiableSequenceScore

Modifier and Type	Method and Description
AbstractDifferentiableSequenceScore	AbstractDifferentiableSequenceScore.clone()

Uses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.differentiable.logistic

Subclasses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.differentiable.logistic

Modifier and Type	Class and Description
class	LogisticDiffSS This class implements a logistic function.

Uses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable

Subclasses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable

Modifier and Type	Class and Description
class	AbstractDifferentiableStatisticalModel This class is the main part of any ScoreClassifier.
class	AbstractVariableLengthDiffSM This abstract class implements some methods declared in DifferentiableStatisticalModel based on the declaration of methods in VariableLengthDiffSM.
class	CyclicMarkovModelDiffSM This scoring function implements a cyclic Markov model of arbitrary order and periodicity for any sequence length.
class	IndependentProductDiffSM This class enables the user to model parts of a sequence independent of each other.
class	MappingDiffSM This class implements a DifferentiableStatisticalModel that works on mapped Sequences.
class	MarkovRandomFieldDiffSM This class implements the scoring function for any MRF (Markov Random Field).
class	NormalizedDiffSM This class makes an unnormalized DifferentiableStatisticalModel to a normalized DifferentiableStatisticalModel.
class	UniformDiffSM This DifferentiableStatisticalModel does nothing.

Uses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

Subclasses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

Modifier and Type	Class and Description
class	BayesianNetworkDiffSM This class implements a scoring function that is a moral directed graphical model, i.e.
class	MarkovModelDiffSM This class implements a AbstractDifferentiableStatisticalModel for an inhomogeneous Markov model.

Uses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

Subclasses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

Modifier and Type	Class and Description
class	HomogeneousDiffSM This is the main class for all homogeneous DifferentiableSequenceScores.
class	HomogeneousMM0DiffSM This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.
class	HomogeneousMMDiffSM This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.
class	UniformHomogeneousDiffSM This scoring function does nothing.

Uses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture

Subclasses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture

Modifier and Type	Class and Description
class	LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder Class for a sparse local inhomogeneous mixture (Slim) model.

Uses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture

Subclasses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture

Modifier and Type	Class and Description
class	AbstractMixtureDiffSM This main abstract class for any mixture scoring function (e.g.
class	MixtureDiffSM This class implements a real mixture model.
class	StrandDiffSM This class enables the user to search on both strand.
class	VariableLengthMixtureDiffSM This class implements a mixture of VariableLengthDiffSM by extending MixtureDiffSM and implementing the methods of VariableLengthDiffSM.

Uses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif

Subclasses of AbstractDifferentiableSequenceScore in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif

Modifier and Type	Class and Description
class	DurationDiffSM This class is the super class for all one dimensional position scoring functions that can be used as durations for semi Markov models.
class	ExtendedZOOPSDiffSM This class handles mixtures with at least one hidden motif.
class	MixtureDurationDiffSM This class implements a mixture of DurationDiffSMs.
class	PositionDiffSM This class implements a position scoring function that enables the user to get a score without using a Sequence object.
class	SkewNormalLikeDurationDiffSM This class implements a skew normal like discrete truncated distribution.
class	UniformDurationDiffSM This scoring function implements a uniform distribution for positions.