aGrUM  0.16.0
localSearchWithTabuList.h
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1 
35 #ifndef GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H
36 #define GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H
37 
38 #include <string>
39 #include <vector>
40 
41 #include <agrum/BN/BayesNet.h>
43 #include <agrum/graphs/DAG.h>
44 
45 namespace gum {
46 
47  namespace learning {
48 
62  public:
63  // ##########################################################################
65  // ##########################################################################
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70 
73 
76 
78  virtual ~LocalSearchWithTabuList();
79 
81 
82  // ##########################################################################
84  // ##########################################################################
86 
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92 
94 
95  // ##########################################################################
97  // ##########################################################################
99 
102 
106 
108 
113  template < typename GRAPH_CHANGES_SELECTOR >
114  DAG learnStructure(GRAPH_CHANGES_SELECTOR& selector,
115  DAG initial_dag = DAG());
116 
118  template < typename GUM_SCALAR = double,
119  typename GRAPH_CHANGES_SELECTOR,
120  typename PARAM_ESTIMATOR >
121  BayesNet< GUM_SCALAR > learnBN(GRAPH_CHANGES_SELECTOR& selector,
122  PARAM_ESTIMATOR& estimator,
123  DAG initial_dag = DAG());
124 
126 
127  private:
130  };
131 
132  } /* namespace learning */
133 
134 } /* namespace gum */
135 
137 #ifndef GUM_NO_INLINE
139 #endif /* GUM_NO_INLINE */
140 
143 
144 #endif /* GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H */
Class representing a Bayesian Network.
Definition: BayesNet.h:78
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
Approximation Scheme.
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.
Definition: agrum.h:25
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.
Definition: types.h:48
void setMaxNbDecreasingChanges(Size nb)
set the max number of changes decreasing the score that we allow to apply
Base class for dag.
Definition: DAG.h:102
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.