27 #ifndef GUM_I_BAYES_NET_GENERATOR_H 28 #define GUM_I_BAYES_NET_GENERATOR_H 60 template <
typename GUM_SCALAR,
template <
typename >
class ICPTGenerator >
Class representing a Bayesian Network.
Abstract class for generating Conditional Probability Tables.
void fillCPT()
function that insert random values in the CPT of each nodes according to the CPTGenerator.
Class for generating bayesian networks.
IBayesNetGenerator(Size nbrNodes, Size maxArcs, Size maxModality)
constructor.
void setNbrNodes(Size nbrNodes)
Modifies the value of the number of nodes imposed on the BayesGenerator.
Class representing Bayesian networks.
Size nbrNodes() const
Return a constant reference to the number of nodes imposed on the IBayesNetGenerator.
algorithm for KL divergence between BNs
gum is the global namespace for all aGrUM entities
void setMaxArcs(Size maxArcs)
Modifies the value of the number of nodes imposed on the BayesGenerator.
Source implementation of IBayesNetGenerator.
BayesNet< GUM_SCALAR > _bayesNet
Size maxArcs() const
Return a constant reference to the maximum number of arcs imposed on the IBayesNetGenerator.
virtual ~IBayesNetGenerator()
Destructor.
virtual void generateBN(BayesNet< GUM_SCALAR > &bayesNet)=0
Virtual function that Generates a bayesian networks.
std::size_t Size
In aGrUM, hashed values are unsigned long int.
Base class for labelized discrete random variables.
Size maxModality() const
Return a constant reference to the maximum modality imposed on the IBayesNetGenerator.
void setMaxModality(Size maxModality)
Modifies the value of the number of nodes imposed on the BayesGenerator.