the base class for all a priori More...

#include <agrum/tools/database/apriori.h>

Inheritance diagram for gum::learning::Apriori< ALLOC >:

Collaboration diagram for gum::learning::Apriori< ALLOC >:

Public Member Functions
Constructors / Destructors
	Apriori (const DatabaseTable< ALLOC > &database, const Bijection< NodeId, std::size_t, ALLOC< std::size_t > > &nodeId2columns=Bijection< NodeId, std::size_t, ALLOC< std::size_t > >(), const allocator_type &alloc=allocator_type())
	default constructor More...

virtual Apriori< ALLOC > *	clone () const =0
	virtual copy constructor More...

virtual Apriori< ALLOC > *	clone (const allocator_type &alloc) const =0
	virtual copy constructor with a given allocator More...

virtual	~Apriori ()
	destructor More...

Accessors / Modifiers
virtual void	setWeight (const double weight)
	sets the weight of the a priori (kind of effective sample size) More...

double	weight () const
	returns the weight assigned to the apriori More...

virtual bool	isOfType (const std::string &type)=0
	indicates whether an apriori is of a certain type More...

virtual const std::string &	getType () const =0
	returns the type of the apriori More...

virtual bool	isInformative () const =0
	indicates whether the apriori is potentially informative More...

virtual void	addAllApriori (const IdCondSet< ALLOC > &idset, std::vector< double, ALLOC< double > > &counts)=0
	adds the apriori to a counting vector corresponding to the idset More...

virtual void	addConditioningApriori (const IdCondSet< ALLOC > &idset, std::vector< double, ALLOC< double > > &counts)=0
	adds the apriori to a counting vectordefined over the right hand side of the idset More...

allocator_type	getAllocator () const
	returns the allocator used by the internal apriori More...

Public Types
using	allocator_type = ALLOC< NodeId >
	type for the allocators passed in arguments of methods More...

Protected Attributes
double	weight_ {1.0}
	the weight of the apriori More...

const DatabaseTable< ALLOC > *	database_
	a reference to the database in order to have access to its variables More...

Bijection< NodeId, std::size_t, ALLOC< std::size_t > >	nodeId2columns_
	a mapping from the NodeIds of the variables to the indices of the columns in the database More...

Protected Member Functions
	Apriori (const Apriori< ALLOC > &from)
	copy constructor More...

	Apriori (const Apriori< ALLOC > &from, const allocator_type &alloc)
	copy constructor with a given allocator More...

	Apriori (Apriori< ALLOC > &&from)
	move constructor More...

	Apriori (Apriori< ALLOC > &&from, const allocator_type &alloc)
	move constructor with a given allocator More...

Apriori< ALLOC > &	operator= (const Apriori< ALLOC > &from)
	copy operator More...

Apriori< ALLOC > &	operator= (Apriori< ALLOC > &&from)
	move operator More...

Detailed Description

template<template< typename > class ALLOC = std::allocator>
class gum::learning::Apriori< ALLOC >

the base class for all a priori

Definition at line 49 of file apriori.h.

Member Typedef Documentation

◆ allocator_type

template<template< typename > class ALLOC = std::allocator>

using gum::learning::Apriori< ALLOC >::allocator_type = ALLOC< NodeId >

type for the allocators passed in arguments of methods

Definition at line 52 of file apriori.h.

Constructor & Destructor Documentation

◆ Apriori() [1/5]

template<template< typename > class ALLOC = std::allocator>

gum::learning::Apriori< ALLOC >::Apriori	(	const DatabaseTable< ALLOC > &	database,
		const Bijection< NodeId, std::size_t, ALLOC< std::size_t > > &	nodeId2columns = `Bijection< NodeId, std::size_t, ALLOC< std::size_t > >()`,
		const allocator_type &	alloc = `allocator_type()`
	)

default constructor

Parameters

database	the database from which learning is performed. This is useful to get access to the random variables
nodeId2Columns	a mapping from the ids of the nodes in the graphical model to the corresponding column in the DatabaseTable. This enables estimating from a database in which variable A corresponds to the 2nd column the parameters of a BN in which variable A has a NodeId of 5. An empty nodeId2Columns bijection means that the mapping is an identity, i.e., the value of a NodeId is equal to the index of the column in the DatabaseTable.
alloc	the allocator used to allocate the structures within the RecordCounter.

◆ ~Apriori()

template<template< typename > class ALLOC = std::allocator>

virtual gum::learning::Apriori< ALLOC >::~Apriori ( )

virtual

destructor

◆ Apriori() [2/5]

template<template< typename > class ALLOC = std::allocator>

gum::learning::Apriori< ALLOC >::Apriori ( const Apriori< ALLOC > & from )

protected

copy constructor

◆ Apriori() [3/5]

template<template< typename > class ALLOC = std::allocator>

gum::learning::Apriori< ALLOC >::Apriori	(	const Apriori< ALLOC > &	from,
		const allocator_type &	alloc
	)

protected

copy constructor with a given allocator

◆ Apriori() [4/5]

template<template< typename > class ALLOC = std::allocator>

gum::learning::Apriori< ALLOC >::Apriori ( Apriori< ALLOC > && from )

protected

move constructor

◆ Apriori() [5/5]

template<template< typename > class ALLOC = std::allocator>

gum::learning::Apriori< ALLOC >::Apriori	(	Apriori< ALLOC > &&	from,
		const allocator_type &	alloc
	)

protected

move constructor with a given allocator

Member Function Documentation

◆ addAllApriori()

template<template< typename > class ALLOC = std::allocator>

virtual void gum::learning::Apriori< ALLOC >::addAllApriori	(	const IdCondSet< ALLOC > &	idset,
		std::vector< double, ALLOC< double > > &	counts
	)

pure virtual

adds the apriori to a counting vector corresponding to the idset

adds the apriori to an already created counting vector defined over the union of the variables on both the left and right hand side of the conditioning bar of the idset.

Warning: the method assumes that the size of the vector is exactly the domain size of the joint variables set.

Implemented in gum::learning::AprioriDirichletFromDatabase< ALLOC >, gum::learning::AprioriBDeu< ALLOC >, gum::learning::AprioriNoApriori< ALLOC >, and gum::learning::AprioriSmoothing< ALLOC >.

◆ addConditioningApriori()

template<template< typename > class ALLOC = std::allocator>

virtual void gum::learning::Apriori< ALLOC >::addConditioningApriori	(	const IdCondSet< ALLOC > &	idset,
		std::vector< double, ALLOC< double > > &	counts
	)

pure virtual

adds the apriori to a counting vectordefined over the right hand side of the idset

Warning: the method assumes that the size of the vector is exactly the domain size of the joint RHS variables of the idset.

Implemented in gum::learning::AprioriDirichletFromDatabase< ALLOC >, gum::learning::AprioriBDeu< ALLOC >, gum::learning::AprioriNoApriori< ALLOC >, and gum::learning::AprioriSmoothing< ALLOC >.

◆ clone() [1/2]

template<template< typename > class ALLOC = std::allocator>

virtual Apriori< ALLOC >* gum::learning::Apriori< ALLOC >::clone ( ) const

pure virtual

virtual copy constructor

Implemented in gum::learning::AprioriDirichletFromDatabase< ALLOC >, gum::learning::AprioriBDeu< ALLOC >, gum::learning::AprioriK2< ALLOC >, gum::learning::AprioriNoApriori< ALLOC >, and gum::learning::AprioriSmoothing< ALLOC >.

◆ clone() [2/2]

template<template< typename > class ALLOC = std::allocator>

virtual Apriori< ALLOC >* gum::learning::Apriori< ALLOC >::clone ( const allocator_type & alloc ) const

pure virtual

virtual copy constructor with a given allocator

Implemented in gum::learning::AprioriDirichletFromDatabase< ALLOC >, gum::learning::AprioriBDeu< ALLOC >, gum::learning::AprioriK2< ALLOC >, gum::learning::AprioriNoApriori< ALLOC >, and gum::learning::AprioriSmoothing< ALLOC >.

◆ getAllocator()

template<template< typename > class ALLOC = std::allocator>

allocator_type gum::learning::Apriori< ALLOC >::getAllocator ( ) const

returns the allocator used by the internal apriori

◆ getType()

template<template< typename > class ALLOC = std::allocator>

virtual const std::string& gum::learning::Apriori< ALLOC >::getType ( ) const

pure virtual

returns the type of the apriori

Implemented in gum::learning::AprioriDirichletFromDatabase< ALLOC >, gum::learning::AprioriBDeu< ALLOC >, gum::learning::AprioriNoApriori< ALLOC >, and gum::learning::AprioriSmoothing< ALLOC >.

◆ isInformative()

template<template< typename > class ALLOC = std::allocator>

virtual bool gum::learning::Apriori< ALLOC >::isInformative ( ) const

pure virtual

indicates whether the apriori is potentially informative

Basically, only the NoApriori is uninformative. However, it may happen that, under some circonstances, an apriori, which is usually not equal to the NoApriori, becomes equal to it (e.g., when the weight is equal to zero). In this case, if the apriori can detect this case, it shall inform the classes that use it that it is temporarily uninformative. These classes will then be able to speed-up their code by avoiding to take into account the apriori in their computations.

Implemented in gum::learning::AprioriDirichletFromDatabase< ALLOC >, gum::learning::AprioriBDeu< ALLOC >, gum::learning::AprioriNoApriori< ALLOC >, and gum::learning::AprioriSmoothing< ALLOC >.

◆ isOfType()

template<template< typename > class ALLOC = std::allocator>

virtual bool gum::learning::Apriori< ALLOC >::isOfType ( const std::string & type )

pure virtual

indicates whether an apriori is of a certain type

Implemented in gum::learning::AprioriDirichletFromDatabase< ALLOC >, gum::learning::AprioriBDeu< ALLOC >, gum::learning::AprioriNoApriori< ALLOC >, and gum::learning::AprioriSmoothing< ALLOC >.

◆ operator=() [1/2]

template<template< typename > class ALLOC = std::allocator>

Apriori< ALLOC >& gum::learning::Apriori< ALLOC >::operator= ( const Apriori< ALLOC > & from )

protected

copy operator

◆ operator=() [2/2]

template<template< typename > class ALLOC = std::allocator>

Apriori< ALLOC >& gum::learning::Apriori< ALLOC >::operator= ( Apriori< ALLOC > && from )

protected

move operator

◆ setWeight()

template<template< typename > class ALLOC = std::allocator>

virtual void gum::learning::Apriori< ALLOC >::setWeight ( const double weight )

virtual

sets the weight of the a priori (kind of effective sample size)

Reimplemented in gum::learning::AprioriDirichletFromDatabase< ALLOC >, gum::learning::AprioriBDeu< ALLOC >, gum::learning::AprioriK2< ALLOC >, and gum::learning::AprioriNoApriori< ALLOC >.

◆ weight()

template<template< typename > class ALLOC = std::allocator>

double gum::learning::Apriori< ALLOC >::weight ( ) const

returns the weight assigned to the apriori

Member Data Documentation

◆ database_

template<template< typename > class ALLOC = std::allocator>

const DatabaseTable< ALLOC >* gum::learning::Apriori< ALLOC >::database_

protected

a reference to the database in order to have access to its variables

Definition at line 144 of file apriori.h.

◆ nodeId2columns_

template<template< typename > class ALLOC = std::allocator>

Bijection< NodeId, std::size_t, ALLOC< std::size_t > > gum::learning::Apriori< ALLOC >::nodeId2columns_

protected

a mapping from the NodeIds of the variables to the indices of the columns in the database

Definition at line 148 of file apriori.h.

◆ weight_

template<template< typename > class ALLOC = std::allocator>

double gum::learning::Apriori< ALLOC >::weight_ {1.0}

protected

the weight of the apriori

Definition at line 141 of file apriori.h.

The documentation for this class was generated from the following file:

agrum/BN/learning/aprioris/apriori.h

Public Member Functions

Public Types

Protected Attributes

Protected Member Functions

Detailed Description

template<template< typename > class ALLOC = std::allocator> class gum::learning::Apriori< ALLOC >

Member Typedef Documentation

◆ allocator_type

Constructor & Destructor Documentation

◆ Apriori() [1/5]

◆ ~Apriori()

◆ Apriori() [2/5]

◆ Apriori() [3/5]

◆ Apriori() [4/5]

◆ Apriori() [5/5]

Member Function Documentation

◆ addAllApriori()

◆ addConditioningApriori()

◆ clone() [1/2]

◆ clone() [2/2]

◆ getAllocator()

◆ getType()

◆ isInformative()

◆ isOfType()

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ setWeight()

◆ weight()

Member Data Documentation

◆ database_

◆ nodeId2columns_

◆ weight_

template<template< typename > class ALLOC = std::allocator>
class gum::learning::Apriori< ALLOC >