| Package | Description |
|---|---|
| de.jstacs.sequenceScores.statisticalModels.trainable |
Provides all
TrainableStatisticalModels, which can
be learned from a single DataSet. |
| de.jstacs.sequenceScores.statisticalModels.trainable.discrete | |
| de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous |
This package contains various inhomogeneous models.
|
| de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters | |
| de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared |
| Class and Description |
|---|
| BayesianNetworkTrainSM
The class implements a Bayesian network (
StructureLearner.ModelType.BN ) of fixed order. |
| FSDAGTrainSM
This class can be used for any discrete fixed structure
directed acyclic graphical model (
FSDAGTrainSM). |
| Class and Description |
|---|
| InhCondProb
This class handles (conditional) probabilities of sequences for
inhomogeneous models.
|
| MEM
This class represents a maximum entropy model.
|
| MEMConstraint
This constraint can be used for any maximum entropy
model (MEM) application.
|
| Class and Description |
|---|
| BayesianNetworkTrainSM
The class implements a Bayesian network (
StructureLearner.ModelType.BN ) of fixed order. |
| DAGTrainSM
The abstract class for directed acyclic graphical models
(
DAGTrainSM). |
| FSDAGModelForGibbsSampling
This is the class for a fixed structure directed acyclic graphical model (see
FSDAGTrainSM) that can be used in a Gibbs sampling. |
| FSDAGTrainSM
This class can be used for any discrete fixed structure
directed acyclic graphical model (
FSDAGTrainSM). |
| InhCondProb
This class handles (conditional) probabilities of sequences for
inhomogeneous models.
|
| InhConstraint
This class is the superclass for all inhomogeneous constraints.
|
| InhomogeneousDGTrainSM
This class is the main class for all inhomogeneous discrete
graphical models (
InhomogeneousDGTrainSM). |
| MEM
This class represents a maximum entropy model.
|
| MEManager
This class is the super class for all maximum entropy models
|
| MEMConstraint
This constraint can be used for any maximum entropy
model (MEM) application.
|
| SequenceIterator
This class is used to iterate over a discrete sequence.
|
| StructureLearner.LearningType
This
enum defines the different types of learning that are
possible with the StructureLearner. |
| StructureLearner.ModelType
This
enum defines the different types of models that can be
learned with the StructureLearner. |
| Class and Description |
|---|
| FSDAGTrainSM
This class can be used for any discrete fixed structure
directed acyclic graphical model (
FSDAGTrainSM). |
| InhomogeneousDGTrainSM
This class is the main class for all inhomogeneous discrete
graphical models (
InhomogeneousDGTrainSM). |
| MEManager
This class is the super class for all maximum entropy models
|
| StructureLearner.LearningType
This
enum defines the different types of learning that are
possible with the StructureLearner. |
| StructureLearner.ModelType
This
enum defines the different types of models that can be
learned with the StructureLearner. |
| Class and Description |
|---|
| FSDAGTrainSM
This class can be used for any discrete fixed structure
directed acyclic graphical model (
FSDAGTrainSM). |
| StructureLearner.LearningType
This
enum defines the different types of learning that are
possible with the StructureLearner. |
| StructureLearner.ModelType
This
enum defines the different types of models that can be
learned with the StructureLearner. |