_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::genericBNLearner | protected |
algoMiic3off2_ | gum::learning::genericBNLearner | protected |
AlgoType enum name | gum::learning::genericBNLearner | |
ApproximationSchemeSTATE enum name | gum::IApproximationSchemeConfiguration | |
apriori_ | gum::learning::genericBNLearner | protected |
aprioriDatabase_ | gum::learning::genericBNLearner | protected |
aprioriDbname_ | gum::learning::genericBNLearner | protected |
AprioriType enum name | gum::learning::genericBNLearner | |
aprioriType_ | gum::learning::genericBNLearner | protected |
aprioriWeight_ | gum::learning::genericBNLearner | protected |
checkFileName_(const std::string &filename) | gum::learning::genericBNLearner | protectedstatic |
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::genericBNLearner | protected |
constraintIndegree_ | gum::learning::genericBNLearner | protected |
constraintMandatoryArcs_ | gum::learning::genericBNLearner | protected |
constraintPossibleEdges_ | gum::learning::genericBNLearner | protected |
constraintSliceOrder_ | gum::learning::genericBNLearner | protected |
constraintTabuList_ | gum::learning::genericBNLearner | protected |
createApriori_() | gum::learning::genericBNLearner | protected |
createCorrectedMutualInformation_() | gum::learning::genericBNLearner | protected |
createParamEstimator_(DBRowGeneratorParser<> &parser, bool take_into_account_score=true) | gum::learning::genericBNLearner | protected |
createScore_() | gum::learning::genericBNLearner | protected |
currentAlgorithm_ | gum::learning::genericBNLearner | protected |
currentTime() const | gum::learning::genericBNLearner | inlinevirtual |
Dag2BN_ | gum::learning::genericBNLearner | protected |
database() const | gum::learning::genericBNLearner | |
databaseRanges() const | gum::learning::genericBNLearner | |
databaseWeight() const | gum::learning::genericBNLearner | |
disableEpsilon() | gum::learning::genericBNLearner | inlinevirtual |
disableMaxIter() | gum::learning::genericBNLearner | inlinevirtual |
disableMaxTime() | gum::learning::genericBNLearner | inlinevirtual |
disableMinEpsilonRate() | gum::learning::genericBNLearner | inlinevirtual |
distributeProgress(const ApproximationScheme *approximationScheme, Size pourcent, double error, double time) | gum::learning::genericBNLearner | inline |
distributeStop(const ApproximationScheme *approximationScheme, std::string message) | gum::learning::genericBNLearner | inline |
domainSize(NodeId var) const | gum::learning::genericBNLearner | |
domainSize(const std::string &var) const | gum::learning::genericBNLearner | |
domainSizes() const | gum::learning::genericBNLearner | |
enableEpsilon() | gum::learning::genericBNLearner | inlinevirtual |
enableMaxIter() | gum::learning::genericBNLearner | inlinevirtual |
enableMaxTime() | gum::learning::genericBNLearner | inlinevirtual |
enableMinEpsilonRate() | gum::learning::genericBNLearner | inlinevirtual |
epsilon() const | gum::learning::genericBNLearner | inlinevirtual |
epsilonEM_ | gum::learning::genericBNLearner | protected |
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_() const | gum::learning::genericBNLearner | protected |
greedyHillClimbing_ | gum::learning::genericBNLearner | protected |
hasMissingValues() const | gum::learning::genericBNLearner | |
history() const | gum::learning::genericBNLearner | inlinevirtual |
IApproximationSchemeConfiguration() | gum::IApproximationSchemeConfiguration | |
idFromName(const std::string &var_name) const | gum::learning::genericBNLearner | |
initialDag_ | gum::learning::genericBNLearner | protected |
isEnabledEpsilon() const | gum::learning::genericBNLearner | inlinevirtual |
isEnabledMaxIter() const | gum::learning::genericBNLearner | inlinevirtual |
isEnabledMaxTime() const | gum::learning::genericBNLearner | inlinevirtual |
isEnabledMinEpsilonRate() const | gum::learning::genericBNLearner | inlinevirtual |
kmode3Off2_ | gum::learning::genericBNLearner | protected |
latentVariables() const | gum::learning::genericBNLearner | |
learnDAG() | gum::learning::genericBNLearner | |
learnDag_() | gum::learning::genericBNLearner | protected |
learnMixedStructure() | gum::learning::genericBNLearner | |
localSearchWithTabuList_ | gum::learning::genericBNLearner | protected |
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() const | gum::learning::genericBNLearner | inlinevirtual |
maxTime() const | gum::learning::genericBNLearner | inlinevirtual |
messageApproximationScheme() const | gum::IApproximationSchemeConfiguration | |
minEpsilonRate() const | gum::learning::genericBNLearner | inlinevirtual |
mutualInfo_ | gum::learning::genericBNLearner | protected |
nameFromId(NodeId id) const | gum::learning::genericBNLearner | |
names() const | gum::learning::genericBNLearner | |
nbCols() const | gum::learning::genericBNLearner | |
nbrIterations() const | gum::learning::genericBNLearner | inlinevirtual |
nbRows() const | gum::learning::genericBNLearner | |
noApriori_ | gum::learning::genericBNLearner | protected |
onProgress | gum::IApproximationSchemeConfiguration | |
onStop | gum::IApproximationSchemeConfiguration | |
operator=(const genericBNLearner &) | gum::learning::genericBNLearner | |
operator=(genericBNLearner &&) | gum::learning::genericBNLearner | |
ParamEstimatorType enum name | gum::learning::genericBNLearner | |
paramEstimatorType_ | gum::learning::genericBNLearner | protected |
periodSize() const | gum::learning::genericBNLearner | inlinevirtual |
prepareMiic3Off2_() | gum::learning::genericBNLearner | protected |
ranges_ | gum::learning::genericBNLearner | protected |
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::genericBNLearner | protectedstatic |
recordWeight(const std::size_t i) const | gum::learning::genericBNLearner | |
score_ | gum::learning::genericBNLearner | protected |
scoreDatabase_ | gum::learning::genericBNLearner | protected |
ScoreType enum name | gum::learning::genericBNLearner | |
scoreType_ | gum::learning::genericBNLearner | protected |
selectedAlgo_ | gum::learning::genericBNLearner | protected |
setCurrentApproximationScheme(const ApproximationScheme *approximationScheme) | gum::learning::genericBNLearner | inline |
setDatabaseWeight(const double new_weight) | gum::learning::genericBNLearner | |
setEpsilon(double eps) | gum::learning::genericBNLearner | inlinevirtual |
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::genericBNLearner | inlinevirtual |
setMaxTime(double timeout) | gum::learning::genericBNLearner | inlinevirtual |
setMinEpsilonRate(double rate) | gum::learning::genericBNLearner | inlinevirtual |
setPeriodSize(Size p) | gum::learning::genericBNLearner | inlinevirtual |
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::genericBNLearner | inlinevirtual |
stateApproximationScheme() const | gum::learning::genericBNLearner | inlinevirtual |
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() const | gum::learning::genericBNLearner | inlinevirtual |
~genericBNLearner() | gum::learning::genericBNLearner | virtual |
~IApproximationSchemeConfiguration() | gum::IApproximationSchemeConfiguration | |