See: Description
Class | Description |
---|---|
BayesianNetworkTrainSM |
The class implements a Bayesian network (
StructureLearner.ModelType.BN ) of fixed order. |
CombinationIterator |
This class can be used for iterating over all possible combinations (in the
sense of combinatorics).
|
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 ). |
FSMEManager |
This class can be used for any discrete fixed structure maximum entropy model (FSMEM).
|
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.
|
MEMTools | |
MEMTools.DualFunction |
The dual function to the constraint problem of learning MEM's.
|
SequenceIterator |
This class is used to iterate over a discrete sequence.
|
StructureLearner |
This class can be used to learn the structure of any discrete model.
|
TwoPointEvaluater |
This class is for visualizing two point dependency between sequence
positions.
|
Enum | Description |
---|---|
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 . |
BayesianNetworkTrainSM
, which is either an inhomogeneous Markov model, a permuted Markov model or a Bayesian network
FSDAGTrainSM
, which is a model on a fixed structure of a directed acyclic graph