aGrUM 2.3.2
a C++ library for (probabilistic) graphical models
localSearchWithTabuList.h
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54#ifndef GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H
55#define GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H
56
57#include <string>
58#include <vector>
59
61#include <agrum/BN/BayesNet.h>
62
63namespace gum {
64
65 namespace learning {
66
80 public:
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131 template < typename GRAPH_CHANGES_SELECTOR >
132 DAG learnStructure(GRAPH_CHANGES_SELECTOR& selector, DAG initial_dag = DAG());
133
135 template < typename GUM_SCALAR = double,
136 typename GRAPH_CHANGES_SELECTOR,
137 typename PARAM_ESTIMATOR >
138 BayesNet< GUM_SCALAR > learnBN(GRAPH_CHANGES_SELECTOR& selector,
139 PARAM_ESTIMATOR& estimator,
140 DAG initial_dag = DAG());
141
143
144 private:
147 };
148
149 } /* namespace learning */
150
151} /* namespace gum */
152
154#ifndef GUM_NO_INLINE
156#endif /* GUM_NO_INLINE */
157
160
161#endif /* GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H */
Class representing Bayesian networks.
This file contains general scheme for iteratively convergent algorithms.
ApproximationScheme(bool verbosity=false)
Base class for dag.
Definition DAG.h:121
Size _MaxNbDecreasing_
the max number of changes decreasing the score that we allow to apply
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
LocalSearchWithTabuList(const LocalSearchWithTabuList &from)
copy constructor
LocalSearchWithTabuList & operator=(LocalSearchWithTabuList &&from)
move operator
DAG learnStructure(GRAPH_CHANGES_SELECTOR &selector, DAG initial_dag=DAG())
learns the structure of a Bayes net
LocalSearchWithTabuList()
default constructor
void setMaxNbDecreasingChanges(Size nb)
set the max number of changes decreasing the score that we allow to apply
LocalSearchWithTabuList & operator=(const LocalSearchWithTabuList &from)
copy operator
LocalSearchWithTabuList(LocalSearchWithTabuList &&from)
move constructor
virtual ~LocalSearchWithTabuList()
destructor
std::size_t Size
In aGrUM, hashed values are unsigned long int.
Definition types.h:74
The local search learning algorithm (for directed graphs).
The local search with tabu list learning algorithm (for directed graphs).
include the inlined functions if necessary
Definition CSVParser.h:54
gum is the global namespace for all aGrUM entities
Definition agrum.h:46