gum::learning Namespace Reference

Classes
struct	__GraphChangesGenerator4K2
class	Apriori
	the base class for all a priori More...
class	AprioriBDeu
	the internal apriori for the BDeu score (N' / (r_i * q_i)BDeu is a BD score with a N'/(r_i * q_i) apriori, where N' is an effective sample size and r_i is the domain size of the target variable and q_i is the domain size of the Cartesian product of its parents. More...
struct	AprioriBDeuType
class	AprioriDirichletFromDatabase
	A dirichlet priori: computes its N'_ijk from a database. More...
struct	AprioriDirichletType
class	AprioriK2
	the internal apriori for the K2 score = Laplace AprioriK2 is a BD score with a Laplace apriori (i.e., a smoothing of 1). More...
class	AprioriNoApriori
	the no a priori class: corresponds to 0 weight-sample More...
struct	AprioriNoAprioriType
class	AprioriSmoothing
	the smooth a priori: adds a weight w to all the countings More...
struct	AprioriSmoothingType
class	ArcAddition
	The class for notifying learning algorithms of new arc additionsThis class is convenient to know at compile time which graph change we are dealing with. More...
class	ArcDeletion
	The class for notifying learning algorithms of arc removalsThis class is convenient to know at compile time which graph change we are dealing with. More...
class	ArcReversal
	The class for notifying learning algorithms of arc reversalsThis class is convenient to know at compile time which graph change we are dealing with. More...
class	BNDatabaseGenerator
class	BNLearner
	A pack of learning algorithms that can easily be used. More...
class	BNLearnerListener
	A class that redirects gum_signal from algorithms to the listeners of BNLearn. More...
class	CorrectedMutualInformation
	The class computing n times the corrected mutual information, as used in the 3off2 algorithm. More...
class	CSVParser
	Class for fast parsing of CSV file (never more than one line in application memory) More...
class	DAG2BNLearner
	A class that, given a structure and a parameter estimator returns a full Bayes net. More...
class	DatabaseTable
	The class representing a tabular database as used by learning tasks. More...
class	DBCell
	The class representing the original values of the cells of databases. More...
class	DBHandler
	The base class for all database handlers. More...
class	DBInitializerFromCSV
	The class for initializing DatabaseTable and RawDatabaseTable instances from CSV files. More...
class	DBInitializerFromSQL
	The class for initializing DatabaseTable and RawDatabaseTable instances from SQL databases. More...
class	DBRow
	The class for storing a record in a database. More...
class	DBRowGenerator
	The base class for all DBRow generators. More...
class	DBRowGenerator4CompleteRows
	A DBRowGenerator class that returns the rows that are complete (fully observed) w.r.t. More...
class	DBRowGeneratorEM
	A DBRowGenerator class that returns incomplete rows as EM would do. More...
class	DBRowGeneratorIdentity
	A DBRowGenerator class that returns exactly the rows it gets in input. More...
class	DBRowGeneratorParser
	the class used to read a row in the database and to transform it into a set of DBRow instances that can be used for learning. More...
class	DBRowGeneratorSet
	The class used to pack sets of generators. More...
class	DBRowGeneratorWithBN
	Base class for DBRowGenerator classes that use a BN for computing their outputs. More...
union	DBTranslatedValue
	The union class for storing the translated values in learning databases. More...
class	DBTranslator
	The base class for all the tabular database cell translators. More...
class	DBTranslator4ContinuousVariable
	The databases' cell translators for continuous variables. More...
class	DBTranslator4DiscretizedVariable
	The databases' cell translators for discretized variables. More...
class	DBTranslator4LabelizedVariable
	The databases' cell translators for labelized variables. More...
class	DBTranslator4RangeVariable
	The databases' cell translators for range variables. More...
class	DBTranslatorSet
	the class for packing together the translators used to preprocess the datasets More...
class	EdgeAddition
	The class for notifying learning algorithms of new edge additionsThis class is convenient to know at compile time which graph change we are dealing with. More...
class	EdgeDeletion
	The class for notifying learning algorithms of edge removalsThis class is convenient to know at compile time which graph change we are dealing with. More...
class	genericBNLearner
	A pack of learning algorithms that can easily be used. More...
class	GraphChange
class	GraphChangesGenerator4DiGraph
	The basic class for computing the next graph changes possible in a structure learning algorithm. More...
class	GraphChangesGenerator4K2
	The basic class for computing the next graph changes possible in a structure learning algorithm. More...
class	GraphChangesGenerator4UndiGraph
	The basic class for computing the next graph changes possible in an undirected structure learning algorithm. More...
class	GraphChangesGeneratorOnSubDiGraph
	The basic class for computing the next graph changes possible in a structure learning algorithm. More...
class	GraphChangesSelector4DiGraph
	The mecanism to compute the next available graph changes for directed structure learning search algorithms. More...
class	GreaterAbsPairOn2nd
class	GreaterPairOn2nd
class	GreaterTupleOnLast
class	GreedyHillClimbing
	The greedy hill climbing learning algorithm (for directed graphs) More...
class	IDatabaseTable
	The common class for the tabular database tables. More...
struct	IDatabaseTableInsert4DBCell
struct	IDatabaseTableInsert4DBCell< ALLOC, false >
struct	IDatabaseTableInsert4DBCell< ALLOC, true >
class	IDBInitializer
	The base class for initializing DatabaseTable and RawDatabaseTable instances from CSV files or SQL databases. More...
class	IdSet
	A class for storing a pair of sets of NodeIds, the second one corresponding to a conditional set. More...
class	IdSetIterator
	The iterators for IdSets. More...
class	IGraphChangesGenerator4DiGraph
class	IGraphChangesGenerator4UndiGraph
class	IndependenceTest
	The base class for all the independence tests used for learning. More...
class	IndepTestChi2
	the class for computing Chi2 independence test scores More...
class	IndepTestG2
	the class for computing G2 independence test scores More...
class	K2
	The K2 algorithm. More...
class	KNML
	the class for computing the NML penalty used by 3off2 More...
class	LocalSearchWithTabuList
	The local search with tabu list learning algorithm (for directed graphs) More...
class	Miic
	The miic learning algorithm. More...
class	NanodbcParser
	Class for parsing SQL results using Nanodbc. More...
class	ParamEstimator
	The base class for estimating parameters of CPTs. More...
class	ParamEstimatorML
	The class for estimating parameters of CPTs using Maximum Likelihood. More...
class	RawDatabaseTable
	The table containing the raw/original data of a databaseClass RawDatabaseTable is intended to store in RAM the raw/original data of a database. More...
class	RecordCounter
	The class that computes countings of observations from the database. More...
class	Score
	The base class for all the scores used for learning (BIC, BDeu, etc) More...
class	ScoreAIC
	the class for computing AIC scores More...
class	ScoreBD
	the class for computing Bayesian Dirichlet (BD) log2 scores More...
class	ScoreBDeu
	the class for computing BDeu scores More...
class	ScoreBIC
	the class for computing BIC scores More...
class	ScorefNML
	the class for computing fNML scores More...
class	ScoreK2
	the class for computing K2 scores (actually their log2 value) More...
class	ScoreLog2Likelihood
	the class for computing Log2-likelihood scores More...
class	ScoringCache
	a cache for caching scores and independence tests resultsCaching previously computed scores or the results of conditional independence tests is very important for learning algorithms because computing a score or an independence test requires parsing the database and this is the most time consuming operation in learning. More...
class	StructuralConstraintDAG
	The base class for structural constraints imposed by DAGs. More...
class	StructuralConstraintDiGraph
	The base class for structural constraints used by learning algorithms that learn a directed graph structure. More...
class	StructuralConstraintEmpty
	the base class for all structural constraints More...
class	StructuralConstraintForbiddenArcs
	the structural constraint for forbidding the creation of some arcs during structure learning More...
class	StructuralConstraintIndegree
	the class for structural constraints limiting the number of parents of nodes in a directed graph More...
class	StructuralConstraintMandatoryArcs
	the structural constraint indicating that some arcs shall never be removed or reversed More...
class	StructuralConstraintPossibleEdges
	the structural constraint for forbidding the creation of some arcs except those defined in the class during structure learning More...
class	StructuralConstraintSetStatic
	the "meta-programming" class for storing structural constraintsIn aGrUM, there are two ways to store sets of structural constraints: the first one is to put them into a StructuralConstraintSetDynamic. More...
class	StructuralConstraintSliceOrder
	the structural constraint imposing a partial order over nodes More...
class	StructuralConstraintTabuList
	The class imposing a N-sized tabu list as a structural constraints for learning algorithms. More...
class	StructuralConstraintUndiGraph
	The base class for structural constraints used by learning algorithms that learn an undirected graph structure. More...

Typedefs
template<template< typename > class ALLOC = std::allocator>
using	ScoreMDL = ScoreBIC< ALLOC >

Enumerations
enum	DBRowGeneratorGoal : char { DBRowGeneratorGoal::ONLY_REMOVE_MISSING_VALUES, DBRowGeneratorGoal::OTHER_THINGS_THAN_REMOVE_MISSING_VALUES }
	the type of things that a DBRowGenerator is designed for More...
enum	DBTranslatedValueType : char { DBTranslatedValueType::DISCRETE, DBTranslatedValueType::CONTINUOUS }
	The nature of the elements handled by translators (discrete, continuous). More...
enum	GraphChangeType {   ARC_ADDITION, ARC_DELETION, ARC_REVERSAL, EDGE_ADDITION,   EDGE_DELETION }
	the type of modification that can be applied to the graph More...

Functions
DatabaseTable	readFile (const std::string &filename)
template<template< typename > class ALLOC>
std::ostream &	operator<< (std::ostream &stream, const IdSet< ALLOC > &idset)
	the display operator More...
std::ostream &	operator<< (std::ostream &stream, const GraphChange &change)
	a << operator for GraphChanges More...
std::ostream &	operator<< (std::ostream &stream, const ArcAddition &change)
	a << operator for ArcAddition More...
std::ostream &	operator<< (std::ostream &stream, const ArcDeletion &change)
	a << operator for ArcDeletion More...
std::ostream &	operator<< (std::ostream &stream, const ArcReversal &change)
	a << operator for ArcReversal More...
std::ostream &	operator<< (std::ostream &stream, const EdgeAddition &change)
	a << operator for EdgeAddition More...
std::ostream &	operator<< (std::ostream &stream, const EdgeDeletion &change)
	a << operator for EdgeDeletion More...

Typedef Documentation

ScoreMDL

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

using gum::learning::ScoreMDL = typedef ScoreBIC< ALLOC >

Definition at line 49 of file scoreMDL.h.

Enumeration Type Documentation

GraphChangeType

enum gum::learning::GraphChangeType

the type of modification that can be applied to the graph

Enumerator
ARC_ADDITION
ARC_DELETION
ARC_REVERSAL
EDGE_ADDITION
EDGE_DELETION

Definition at line 47 of file graphChange.h.

                         {
      ARC_ADDITION,
      ARC_DELETION,
      ARC_REVERSAL,
      EDGE_ADDITION,
      EDGE_DELETION
    };

Function Documentation

operator<<() [1/7]

std::ostream & gum::learning::operator<<	(	std::ostream &	stream,
		const GraphChange &	change
	)

a << operator for GraphChanges

Definition at line 108 of file graphChange.cpp.

References gum::learning::GraphChange::toString().

                                                                          {
      return stream << change.toString();
    }

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operator<<() [2/7]

std::ostream & gum::learning::operator<<	(	std::ostream &	stream,
		const ArcAddition &	change
	)

a << operator for ArcAddition

Definition at line 113 of file graphChange.cpp.

References gum::learning::ArcAddition::toString().

                                                                          {
      return stream << change.toString();
    }

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operator<<() [3/7]

std::ostream & gum::learning::operator<<	(	std::ostream &	stream,
		const ArcDeletion &	change
	)

a << operator for ArcDeletion

Definition at line 118 of file graphChange.cpp.

References gum::learning::ArcDeletion::toString().

                                                                          {
      return stream << change.toString();
    }

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operator<<() [4/7]

std::ostream & gum::learning::operator<<	(	std::ostream &	stream,
		const ArcReversal &	change
	)

a << operator for ArcReversal

Definition at line 123 of file graphChange.cpp.

References gum::learning::ArcReversal::toString().

                                                                          {
      return stream << change.toString();
    }

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operator<<() [5/7]

std::ostream & gum::learning::operator<<	(	std::ostream &	stream,
		const EdgeAddition &	change
	)

a << operator for EdgeAddition

Definition at line 128 of file graphChange.cpp.

References gum::learning::EdgeAddition::toString().

                                                                           {
      return stream << change.toString();
    }

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operator<<() [6/7]

std::ostream & gum::learning::operator<<	(	std::ostream &	stream,
		const EdgeDeletion &	change
	)

a << operator for EdgeDeletion

Definition at line 133 of file graphChange.cpp.

References gum::learning::EdgeDeletion::toString().

                                                                           {
      return stream << change.toString();
    }

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operator<<() [7/7]

template<template< typename > class ALLOC>

std::ostream& gum::learning::operator<<	(	std::ostream &	stream,
		const IdSet< ALLOC > &	idset
	)

the display operator

readFile()

DatabaseTable gum::learning::readFile

(

const std::string &

filename

)

Definition at line 372 of file genericBNLearner.cpp.

References gum::learning::genericBNLearner::database(), gum::learning::IDBInitializer< ALLOC >::fillDatabase(), GUM_ERROR, gum::learning::DBTranslatorSet< ALLOC >::insertTranslator(), gum::learning::DatabaseTable< ALLOC >::setVariableNames(), and gum::learning::IDBInitializer< ALLOC >::variableNames().

                                                        {
      // get the extension of the file
      Size filename_size = Size(filename.size());

      if (filename_size < 4) {
        GUM_ERROR(FormatNotFound,
                  "genericBNLearner could not determine the "
                  "file type of the database");
      }

      std::string extension = filename.substr(filename.size() - 4);
      std::transform(
         extension.begin(), extension.end(), extension.begin(), ::tolower);

      if (extension != ".csv") {
        GUM_ERROR(OperationNotAllowed,
                  "genericBNLearner does not support yet this type "
                  "of database file");
      }

      DBInitializerFromCSV<> initializer(filename);

      const auto&       var_names = initializer.variableNames();
      const std::size_t nb_vars = var_names.size();

      DBTranslatorSet<>                translator_set;
      DBTranslator4LabelizedVariable<> translator;
      for (std::size_t i = 0; i < nb_vars; ++i) {
        translator_set.insertTranslator(translator, i);
      }

      DatabaseTable<> database(translator_set);
      database.setVariableNames(initializer.variableNames());
      initializer.fillDatabase(database);

      return database;
    }

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