Package | Description |
---|---|
de.jstacs.classifiers.differentiableSequenceScoreBased |
Provides the classes for
Classifier s that are based on SequenceScore s.It includes a sub-package for discriminative objective functions, namely conditional likelihood and supervised posterior, and a separate sub-package for the parameter priors, that can be used for the supervised posterior. |
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix |
Provides an implementation of a classifier that allows to train the parameters of a set of
DifferentiableStatisticalModel s by
a unified generative-discriminative learning principle. |
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling |
Provides the classes for
AbstractScoreBasedClassifier s that are based on
SamplingDifferentiableStatisticalModel s
and that sample parameters using the Metropolis-Hastings algorithm. |
de.jstacs.parameters |
This package provides classes for parameters that establish a general convention for the description of parameters
as defined in the
Parameter -interface. |
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels |
Provides
DifferentiableStatisticalModel s that are directed graphical models. |
de.jstacs.sequenceScores.statisticalModels.trainable.discrete | |
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters | |
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters |
Modifier and Type | Class and Description |
---|---|
class |
ScoreClassifierParameterSet
A set of
Parameter s for any
ScoreClassifier . |
Modifier and Type | Class and Description |
---|---|
class |
GenDisMixClassifierParameterSet
This class contains the parameters for the
GenDisMixClassifier . |
Modifier and Type | Class and Description |
---|---|
class |
SamplingGenDisMixClassifierParameterSet
ParameterSet to instantiate a SamplingGenDisMixClassifier . |
class |
SamplingScoreBasedClassifierParameterSet
ParameterSet to instantiate a SamplingScoreBasedClassifier . |
Modifier and Type | Method and Description |
---|---|
SequenceScoringParameterSet<T> |
SequenceScoringParameterSet.clone() |
Modifier and Type | Class and Description |
---|---|
class |
BayesianNetworkDiffSMParameterSet
Class for the parameters of a
BayesianNetworkDiffSM . |
Modifier and Type | Class and Description |
---|---|
class |
DGTrainSMParameterSet<T extends DiscreteGraphicalTrainSM>
The super
ParameterSet for any parameter set of
a DiscreteGraphicalTrainSM . |
Modifier and Type | Class and Description |
---|---|
class |
HomMMParameterSet
This class implements a container for all parameters of a homogeneous Markov
model.
|
class |
HomogeneousTrainSMParameterSet
This class implements a container for all parameters of any homogeneous
model.
|
Modifier and Type | Class and Description |
---|---|
class |
BayesianNetworkTrainSMParameterSet
The
ParameterSet for the class
BayesianNetworkTrainSM . |
class |
FSDAGModelForGibbsSamplingParameterSet
The class for the parameters of a
FSDAGModelForGibbsSampling . |
class |
FSDAGTrainSMParameterSet
The class for the parameters of a
FSDAGTrainSM (fixed
structure directed acyclic graphical
model). |
class |
FSMEMParameterSet
The ParameterSet for a FSMEManager.
|
class |
IDGTrainSMParameterSet
This is the abstract container of parameters that is a root container for all
inhomogeneous discrete graphical model parameter containers.
|
class |
MEManagerParameterSet
The ParameterSet for any MEManager.
|