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a C++ library for (probabilistic) graphical models
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smoothingPrior.h
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/****************************************************************************
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* This file is part of the aGrUM/pyAgrum library. *
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* *
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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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* homepage : http://agrum.gitlab.io *
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****************************************************************************/
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#ifndef GUM_LEARNING_PRIOR_SMOOTHING_H
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#define GUM_LEARNING_PRIOR_SMOOTHING_H
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#include <vector>
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#include <
agrum/agrum.h
>
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#include <
agrum/base/stattests/priors/prior.h
>
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namespace
gum
{
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namespace
learning
{
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class
GUM_SHARED_PUBLIC
SmoothingPrior
:
public
Prior
{
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public
:
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// ##########################################################################
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// ##########################################################################
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explicit
SmoothingPrior
(
const
DatabaseTable
& database,
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const
Bijection< NodeId, std::size_t >
& nodeId2columns
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=
Bijection< NodeId, std::size_t >
());
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SmoothingPrior
(
const
SmoothingPrior
& from);
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SmoothingPrior
(
SmoothingPrior
&& from)
noexcept
;
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[[nodiscard]]
SmoothingPrior
*
clone
()
const override
;
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~SmoothingPrior
()
override
;
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// ##########################################################################
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// ##########################################################################
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SmoothingPrior
&
operator=
(
const
SmoothingPrior
& from);
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SmoothingPrior
&
operator=
(
SmoothingPrior
&& from);
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// ##########################################################################
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// ##########################################################################
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PriorType
getType
() const final;
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bool
isInformative
() const final;
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void
addJointPseudoCount
(const
IdCondSet
& idset,
std
::vector<
double
>& counts) final;
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void
addConditioningPseudoCount
(const
IdCondSet
& idset,
std
::vector<
double
>& counts) final;
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};
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}
/* namespace learning */
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}
/* namespace gum */
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// include the inlined functions if necessary
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#ifndef GUM_NO_INLINE
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# include <
agrum/base/stattests/priors/smoothingPrior_inl.h
>
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#endif
/* GUM_NO_INLINE */
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#endif
/* GUM_LEARNING_PRIOR_SMOOTHING_H */
agrum.h
gum::Bijection< NodeId, std::size_t >
gum::learning::DatabaseTable
The class representing a tabular database as used by learning tasks.
Definition
databaseTable.h:200
gum::learning::IdCondSet
A class for storing a pair of sets of NodeIds, the second one corresponding to a conditional set.
Definition
idCondSet.h:214
gum::learning::Prior::Prior
Prior(const DatabaseTable &database, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
gum::learning::SmoothingPrior::operator=
SmoothingPrior & operator=(SmoothingPrior &&from)
move operator
gum::learning::SmoothingPrior::addConditioningPseudoCount
void addConditioningPseudoCount(const IdCondSet &idset, std::vector< double > &counts) final
adds the prior to a counting vectordefined over the right hand side of the idset
gum::learning::SmoothingPrior::isInformative
bool isInformative() const final
indicates whether the prior is potentially informative
gum::learning::SmoothingPrior::SmoothingPrior
SmoothingPrior(const DatabaseTable &database, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
gum::learning::SmoothingPrior::SmoothingPrior
SmoothingPrior(const SmoothingPrior &from)
copy constructor
gum::learning::SmoothingPrior::addJointPseudoCount
void addJointPseudoCount(const IdCondSet &idset, std::vector< double > &counts) final
adds the prior to a counting vector corresponding to the idset
gum::learning::SmoothingPrior::operator=
SmoothingPrior & operator=(const SmoothingPrior &from)
copy operator
gum::learning::SmoothingPrior::clone
SmoothingPrior * clone() const override
virtual copy constructor
gum::learning::SmoothingPrior::~SmoothingPrior
~SmoothingPrior() override
destructor
gum::learning::SmoothingPrior::getType
PriorType getType() const final
returns the type of the prior
gum::learning::SmoothingPrior::SmoothingPrior
SmoothingPrior(SmoothingPrior &&from) noexcept
move constructor
gum::learning
include the inlined functions if necessary
Definition
CSVParser.h:55
gum::learning::PriorType
PriorType
Definition
prior.h:59
gum
gum is the global namespace for all aGrUM entities
Definition
agrum.h:46
std
STL namespace.
prior.h
the base class for all a priori
smoothingPrior_inl.h
the smooth a priori: adds a weight w to all the counts
aGrUM
3.2.0
© PHW&CG&others - 2022
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