aGrUM  0.20.3
a C++ library for (probabilistic) graphical models
gum::learning::genericBNLearner Member List

This is the complete list of members for gum::learning::genericBNLearner, including all inherited members.

_setAprioriWeight_(double weight)gum::learning::genericBNLearner
addForbiddenArc(const Arc &arc)gum::learning::genericBNLearner
addForbiddenArc(const NodeId tail, const NodeId head)gum::learning::genericBNLearner
addForbiddenArc(const std::string &tail, const std::string &head)gum::learning::genericBNLearner
addMandatoryArc(const Arc &arc)gum::learning::genericBNLearner
addMandatoryArc(const NodeId tail, const NodeId head)gum::learning::genericBNLearner
addMandatoryArc(const std::string &tail, const std::string &head)gum::learning::genericBNLearner
addPossibleEdge(const Edge &edge)gum::learning::genericBNLearner
addPossibleEdge(const NodeId tail, const NodeId head)gum::learning::genericBNLearner
addPossibleEdge(const std::string &tail, const std::string &head)gum::learning::genericBNLearner
algoK2_gum::learning::genericBNLearnerprotected
algoMiic3off2_gum::learning::genericBNLearnerprotected
AlgoType enum namegum::learning::genericBNLearner
ApproximationSchemeSTATE enum namegum::IApproximationSchemeConfiguration
apriori_gum::learning::genericBNLearnerprotected
aprioriDatabase_gum::learning::genericBNLearnerprotected
aprioriDbname_gum::learning::genericBNLearnerprotected
AprioriType enum namegum::learning::genericBNLearner
aprioriType_gum::learning::genericBNLearnerprotected
aprioriWeight_gum::learning::genericBNLearnerprotected
checkFileName_(const std::string &filename)gum::learning::genericBNLearnerprotectedstatic
checkScoreAprioriCompatibility()gum::learning::genericBNLearner
chi2(const NodeId id1, const NodeId id2, const std::vector< NodeId > &knowing={})gum::learning::genericBNLearner
chi2(const std::string &name1, const std::string &name2, const std::vector< std::string > &knowing={})gum::learning::genericBNLearner
clearDatabaseRanges()gum::learning::genericBNLearner
constraintForbiddenArcs_gum::learning::genericBNLearnerprotected
constraintIndegree_gum::learning::genericBNLearnerprotected
constraintMandatoryArcs_gum::learning::genericBNLearnerprotected
constraintPossibleEdges_gum::learning::genericBNLearnerprotected
constraintSliceOrder_gum::learning::genericBNLearnerprotected
constraintTabuList_gum::learning::genericBNLearnerprotected
createApriori_()gum::learning::genericBNLearnerprotected
createCorrectedMutualInformation_()gum::learning::genericBNLearnerprotected
createParamEstimator_(DBRowGeneratorParser<> &parser, bool take_into_account_score=true)gum::learning::genericBNLearnerprotected
createScore_()gum::learning::genericBNLearnerprotected
currentAlgorithm_gum::learning::genericBNLearnerprotected
currentTime() constgum::learning::genericBNLearnerinlinevirtual
Dag2BN_gum::learning::genericBNLearnerprotected
database() constgum::learning::genericBNLearner
databaseRanges() constgum::learning::genericBNLearner
databaseWeight() constgum::learning::genericBNLearner
disableEpsilon()gum::learning::genericBNLearnerinlinevirtual
disableMaxIter()gum::learning::genericBNLearnerinlinevirtual
disableMaxTime()gum::learning::genericBNLearnerinlinevirtual
disableMinEpsilonRate()gum::learning::genericBNLearnerinlinevirtual
distributeProgress(const ApproximationScheme *approximationScheme, Size pourcent, double error, double time)gum::learning::genericBNLearnerinline
distributeStop(const ApproximationScheme *approximationScheme, std::string message)gum::learning::genericBNLearnerinline
domainSize(NodeId var) constgum::learning::genericBNLearner
domainSize(const std::string &var) constgum::learning::genericBNLearner
domainSizes() constgum::learning::genericBNLearner
enableEpsilon()gum::learning::genericBNLearnerinlinevirtual
enableMaxIter()gum::learning::genericBNLearnerinlinevirtual
enableMaxTime()gum::learning::genericBNLearnerinlinevirtual
enableMinEpsilonRate()gum::learning::genericBNLearnerinlinevirtual
epsilon() constgum::learning::genericBNLearnerinlinevirtual
epsilonEM_gum::learning::genericBNLearnerprotected
eraseForbiddenArc(const Arc &arc)gum::learning::genericBNLearner
eraseForbiddenArc(const NodeId tail, const NodeId head)gum::learning::genericBNLearner
eraseForbiddenArc(const std::string &tail, const std::string &head)gum::learning::genericBNLearner
eraseMandatoryArc(const Arc &arc)gum::learning::genericBNLearner
eraseMandatoryArc(const NodeId tail, const NodeId head)gum::learning::genericBNLearner
eraseMandatoryArc(const std::string &tail, const std::string &head)gum::learning::genericBNLearner
erasePossibleEdge(const Edge &edge)gum::learning::genericBNLearner
erasePossibleEdge(const NodeId tail, const NodeId head)gum::learning::genericBNLearner
erasePossibleEdge(const std::string &tail, const std::string &head)gum::learning::genericBNLearner
G2(const NodeId id1, const NodeId id2, const std::vector< NodeId > &knowing={})gum::learning::genericBNLearner
G2(const std::string &name1, const std::string &name2, const std::vector< std::string > &knowing={})gum::learning::genericBNLearner
genericBNLearner(const std::string &filename, const std::vector< std::string > &missing_symbols)gum::learning::genericBNLearner
genericBNLearner(const DatabaseTable<> &db)gum::learning::genericBNLearner
genericBNLearner(const std::string &filename, const gum::BayesNet< GUM_SCALAR > &src, const std::vector< std::string > &missing_symbols)gum::learning::genericBNLearner
genericBNLearner(const genericBNLearner &)gum::learning::genericBNLearner
genericBNLearner(genericBNLearner &&)gum::learning::genericBNLearner
getAprioriType_() constgum::learning::genericBNLearnerprotected
greedyHillClimbing_gum::learning::genericBNLearnerprotected
hasMissingValues() constgum::learning::genericBNLearner
history() constgum::learning::genericBNLearnerinlinevirtual
IApproximationSchemeConfiguration()gum::IApproximationSchemeConfiguration
idFromName(const std::string &var_name) constgum::learning::genericBNLearner
initialDag_gum::learning::genericBNLearnerprotected
isEnabledEpsilon() constgum::learning::genericBNLearnerinlinevirtual
isEnabledMaxIter() constgum::learning::genericBNLearnerinlinevirtual
isEnabledMaxTime() constgum::learning::genericBNLearnerinlinevirtual
isEnabledMinEpsilonRate() constgum::learning::genericBNLearnerinlinevirtual
kmode3Off2_gum::learning::genericBNLearnerprotected
latentVariables() constgum::learning::genericBNLearner
learnDAG()gum::learning::genericBNLearner
learnDag_()gum::learning::genericBNLearnerprotected
learnMixedStructure()gum::learning::genericBNLearner
localSearchWithTabuList_gum::learning::genericBNLearnerprotected
logLikelihood(const std::vector< NodeId > &vars, const std::vector< NodeId > &knowing={})gum::learning::genericBNLearner
logLikelihood(const std::vector< std::string > &vars, const std::vector< std::string > &knowing={})gum::learning::genericBNLearner
maxIter() constgum::learning::genericBNLearnerinlinevirtual
maxTime() constgum::learning::genericBNLearnerinlinevirtual
messageApproximationScheme() constgum::IApproximationSchemeConfiguration
minEpsilonRate() constgum::learning::genericBNLearnerinlinevirtual
mutualInfo_gum::learning::genericBNLearnerprotected
nameFromId(NodeId id) constgum::learning::genericBNLearner
names() constgum::learning::genericBNLearner
nbCols() constgum::learning::genericBNLearner
nbrIterations() constgum::learning::genericBNLearnerinlinevirtual
nbRows() constgum::learning::genericBNLearner
noApriori_gum::learning::genericBNLearnerprotected
onProgressgum::IApproximationSchemeConfiguration
onStopgum::IApproximationSchemeConfiguration
operator=(const genericBNLearner &)gum::learning::genericBNLearner
operator=(genericBNLearner &&)gum::learning::genericBNLearner
ParamEstimatorType enum namegum::learning::genericBNLearner
paramEstimatorType_gum::learning::genericBNLearnerprotected
periodSize() constgum::learning::genericBNLearnerinlinevirtual
prepareMiic3Off2_()gum::learning::genericBNLearnerprotected
ranges_gum::learning::genericBNLearnerprotected
rawPseudoCount(const std::vector< NodeId > &vars)gum::learning::genericBNLearner
rawPseudoCount(const std::vector< std::string > &vars)gum::learning::genericBNLearner
readFile_(const std::string &filename, const std::vector< std::string > &missing_symbols)gum::learning::genericBNLearnerprotectedstatic
recordWeight(const std::size_t i) constgum::learning::genericBNLearner
score_gum::learning::genericBNLearnerprotected
scoreDatabase_gum::learning::genericBNLearnerprotected
ScoreType enum namegum::learning::genericBNLearner
scoreType_gum::learning::genericBNLearnerprotected
selectedAlgo_gum::learning::genericBNLearnerprotected
setCurrentApproximationScheme(const ApproximationScheme *approximationScheme)gum::learning::genericBNLearnerinline
setDatabaseWeight(const double new_weight)gum::learning::genericBNLearner
setEpsilon(double eps)gum::learning::genericBNLearnerinlinevirtual
setForbiddenArcs(const ArcSet &set)gum::learning::genericBNLearner
setInitialDAG(const DAG &)gum::learning::genericBNLearner
setMandatoryArcs(const ArcSet &set)gum::learning::genericBNLearner
setMaxIndegree(Size max_indegree)gum::learning::genericBNLearner
setMaxIter(Size max)gum::learning::genericBNLearnerinlinevirtual
setMaxTime(double timeout)gum::learning::genericBNLearnerinlinevirtual
setMinEpsilonRate(double rate)gum::learning::genericBNLearnerinlinevirtual
setPeriodSize(Size p)gum::learning::genericBNLearnerinlinevirtual
setPossibleEdges(const EdgeSet &set)gum::learning::genericBNLearner
setPossibleSkeleton(const UndiGraph &skeleton)gum::learning::genericBNLearner
setRecordWeight(const std::size_t i, const double weight)gum::learning::genericBNLearner
setSliceOrder(const NodeProperty< NodeId > &slice_order)gum::learning::genericBNLearner
setSliceOrder(const std::vector< std::vector< std::string > > &slices)gum::learning::genericBNLearner
setVerbosity(bool v)gum::learning::genericBNLearnerinlinevirtual
stateApproximationScheme() constgum::learning::genericBNLearnerinlinevirtual
use3off2()gum::learning::genericBNLearner
useAprioriBDeu(double weight=1)gum::learning::genericBNLearner
useAprioriDirichlet(const std::string &filename, double weight=1)gum::learning::genericBNLearner
useAprioriSmoothing(double weight=1)gum::learning::genericBNLearner
useCrossValidationFold(const std::size_t learning_fold, const std::size_t k_fold)gum::learning::genericBNLearner
useDatabaseRanges(const std::vector< std::pair< std::size_t, std::size_t >, XALLOC< std::pair< std::size_t, std::size_t > > > &new_ranges)gum::learning::genericBNLearner
useEM(const double epsilon)gum::learning::genericBNLearner
useGreedyHillClimbing()gum::learning::genericBNLearner
useK2(const Sequence< NodeId > &order)gum::learning::genericBNLearner
useK2(const std::vector< NodeId > &order)gum::learning::genericBNLearner
useLocalSearchWithTabuList(Size tabu_size=100, Size nb_decrease=2)gum::learning::genericBNLearner
useMDLCorrection()gum::learning::genericBNLearner
useMIIC()gum::learning::genericBNLearner
useNMLCorrection()gum::learning::genericBNLearner
useNoApriori()gum::learning::genericBNLearner
useNoCorrection()gum::learning::genericBNLearner
useScoreAIC()gum::learning::genericBNLearner
useScoreBD()gum::learning::genericBNLearner
useScoreBDeu()gum::learning::genericBNLearner
useScoreBIC()gum::learning::genericBNLearner
useScoreK2()gum::learning::genericBNLearner
useScoreLog2Likelihood()gum::learning::genericBNLearner
verbosity() constgum::learning::genericBNLearnerinlinevirtual
~genericBNLearner()gum::learning::genericBNLearnervirtual
~IApproximationSchemeConfiguration()gum::IApproximationSchemeConfiguration