35 #ifndef GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H 36 #define GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H 113 template <
typename GRAPH_CHANGES_
SELECTOR >
118 template <
typename GUM_SCALAR =
double,
119 typename GRAPH_CHANGES_SELECTOR,
120 typename PARAM_ESTIMATOR >
122 PARAM_ESTIMATOR& estimator,
137 #ifndef GUM_NO_INLINE Class representing a Bayesian Network.
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
LocalSearchWithTabuList()
default constructor
LocalSearchWithTabuList & operator=(const LocalSearchWithTabuList &from)
copy operator
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
virtual ~LocalSearchWithTabuList()
destructor
ApproximationScheme & approximationScheme()
returns the approximation policy of the learning algorithm
BayesNet< GUM_SCALAR > learnBN(GRAPH_CHANGES_SELECTOR &selector, PARAM_ESTIMATOR &estimator, DAG initial_dag=DAG())
learns the structure and the parameters of a BN
Size __MaxNbDecreasing
the max number of changes decreasing the score that we allow to apply
The local search with tabu list learning algorithm (for directed graphs)
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
DAG learnStructure(GRAPH_CHANGES_SELECTOR &selector, DAG initial_dag=DAG())
learns the structure of a Bayes net
std::size_t Size
In aGrUM, hashed values are unsigned long int.
void setMaxNbDecreasingChanges(Size nb)
set the max number of changes decreasing the score that we allow to apply
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.