aGrUM
3.2.0
a C++ library for (probabilistic) graphical models
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localSearchWithTabuList.h
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/****************************************************************************
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* This file is part of the aGrUM/pyAgrum library. *
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* Copyright (c) 2005-2026 by *
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* - Pierre-Henri WUILLEMIN(_at_LIP6) *
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* - Christophe GONZALES(_at_AMU) *
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* *
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* The aGrUM/pyAgrum library is free software; you can redistribute it *
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* SPDX-FileCopyrightText: Copyright 2005-2026 *
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* - Pierre-Henri WUILLEMIN(_at_LIP6) *
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* - Christophe GONZALES(_at_AMU) *
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****************************************************************************/
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#ifndef GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H
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#define GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H
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#include <string>
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#include <vector>
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#include <
agrum/base/core/approximations/approximationScheme.h
>
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#include <
agrum/BN/BayesNet.h
>
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namespace
gum
{
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namespace
learning
{
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class
GUM_PUBLIC_BN
LocalSearchWithTabuList
:
public
ApproximationScheme
{
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public
:
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// ##########################################################################
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// ##########################################################################
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LocalSearchWithTabuList
();
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LocalSearchWithTabuList
(
const
LocalSearchWithTabuList
& from);
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LocalSearchWithTabuList
(
LocalSearchWithTabuList
&& from);
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~LocalSearchWithTabuList
()
override
;
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// ##########################################################################
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// ##########################################################################
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LocalSearchWithTabuList
&
operator=
(
const
LocalSearchWithTabuList
& from);
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LocalSearchWithTabuList
&
operator=
(
LocalSearchWithTabuList
&& from);
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// ##########################################################################
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// ##########################################################################
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ApproximationScheme
&
approximationScheme
();
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void
setMaxNbDecreasingChanges
(
Size
nb);
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template
<
typename
GRAPH_CHANGES_
SEL
ECTOR >
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DAG
learnStructure
(GRAPH_CHANGES_SELECTOR& selector,
DAG
initial_dag =
DAG
());
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template
<
GUM_Numeric
GUM_SCALAR =
double
,
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typename
GRAPH_CHANGES_SELECTOR,
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typename
PARAM_ESTIMATOR >
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BayesNet< GUM_SCALAR >
learnBN
(GRAPH_CHANGES_SELECTOR& selector,
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PARAM_ESTIMATOR& estimator,
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DAG
initial_dag =
DAG
());
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private
:
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Size
_MaxNbDecreasing_
{2};
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};
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}
/* namespace learning */
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}
/* namespace gum */
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#ifndef GUM_NO_INLINE
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# include <
agrum/BN/learning/localSearchWithTabuList_inl.h
>
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#endif
/* GUM_NO_INLINE */
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#include <
agrum/BN/learning/localSearchWithTabuList_tpl.h
>
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#endif
/* GUM_LEARNING_LOCAL_SEARCH_WITH_TABU_LIST_H */
BayesNet.h
Class representing Bayesian networks.
approximationScheme.h
This file contains general scheme for iteratively convergent algorithms.
double
gum::ApproximationScheme::ApproximationScheme
ApproximationScheme(bool verbosity=false)
Definition
approximationScheme.cpp:58
gum::DAG
Base class for dag.
Definition
DAG.h:121
gum::learning::LocalSearchWithTabuList::_MaxNbDecreasing_
Size _MaxNbDecreasing_
the max number of changes decreasing the score that we allow to apply
Definition
localSearchWithTabuList.h:146
gum::learning::LocalSearchWithTabuList::approximationScheme
ApproximationScheme & approximationScheme()
returns the approximation policy of the learning algorithm
gum::learning::LocalSearchWithTabuList::learnBN
BayesNet< GUM_SCALAR > learnBN(GRAPH_CHANGES_SELECTOR &selector, PARAM_ESTIMATOR &estimator, DAG initial_dag=DAG())
learns the structure and the parameters of a BN
Definition
localSearchWithTabuList_tpl.h:124
gum::learning::LocalSearchWithTabuList::learnStructure
DAG learnStructure(GRAPH_CHANGES_SELECTOR &selector, DAG initial_dag=DAG())
learns the structure of a Bayes net
Definition
localSearchWithTabuList_tpl.h:61
gum::learning::LocalSearchWithTabuList::LocalSearchWithTabuList
LocalSearchWithTabuList()
default constructor
Definition
localSearchWithTabuList.cpp:66
gum::learning::LocalSearchWithTabuList::setMaxNbDecreasingChanges
void setMaxNbDecreasingChanges(Size nb)
set the max number of changes decreasing the score that we allow to apply
gum::learning::LocalSearchWithTabuList::operator=
LocalSearchWithTabuList & operator=(const LocalSearchWithTabuList &from)
copy operator
gum::GUM_Numeric
Complete concept for GUM_SCALAR template parameter.
Definition
concepts.h:148
gum::Size
std::size_t Size
In aGrUM, hashed values are unsigned long int.
Definition
types.h:74
localSearchWithTabuList_inl.h
The local search learning algorithm (for directed graphs).
localSearchWithTabuList_tpl.h
The local search with tabu list learning algorithm (for directed graphs).
gum::learning
include the inlined functions if necessary
Definition
CSVParser.h:55
gum
gum is the global namespace for all aGrUM entities
Definition
agrum.h:46
aGrUM
3.2.0
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