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Packages that use FSDAGModel | |
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de.jstacs.models.discrete.inhomogeneous.parameters | |
de.jstacs.models.discrete.inhomogeneous.shared | |
de.jstacs.models.mixture.gibbssampling | This package contains many classes that can be used while a Gibbs sampling. |
Uses of FSDAGModel in de.jstacs.models.discrete.inhomogeneous.parameters |
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Constructor parameters in de.jstacs.models.discrete.inhomogeneous.parameters with type arguments of type FSDAGModel | |
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FSDAGMParameterSet(Class<? extends FSDAGModel> clazz)
This is the constructor that creates an empty parameter set. |
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FSDAGMParameterSet(Class<? extends FSDAGModel> clazz,
AlphabetContainer alphabet,
int length,
double ess,
String description,
String graph)
This is the constructor that creates a filled parameter set. |
Uses of FSDAGModel in de.jstacs.models.discrete.inhomogeneous.shared |
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Constructors in de.jstacs.models.discrete.inhomogeneous.shared with parameters of type FSDAGModel | |
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SharedStructureClassifier(int length,
StructureLearner.ModelType model,
byte order,
StructureLearner.LearningType method,
FSDAGModel... models)
The main constructor. |
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SharedStructureMixture(FSDAGModel[] m,
StructureLearner.ModelType model,
byte order,
int starts,
boolean estimateComponentProbs,
double[] weights,
double alpha,
double epsilon)
This constructor is used from the other main constructors. |
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SharedStructureMixture(FSDAGModel[] m,
StructureLearner.ModelType model,
byte order,
int starts,
double[] weights,
double alpha,
double epsilon)
This main constructor creates an instance with fixed component weights. |
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SharedStructureMixture(FSDAGModel[] m,
StructureLearner.ModelType model,
byte order,
int starts,
double alpha,
double epsilon)
This main constructor creates an instance which estimates the component probabilities. |
Uses of FSDAGModel in de.jstacs.models.mixture.gibbssampling |
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Subclasses of FSDAGModel in de.jstacs.models.mixture.gibbssampling | |
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class |
FSDAGModelForGibbsSampling
This is the class for a fixed structure directed acyclic graphical model that can be used in a Gibbs sampling. |
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