Here is a list of all functions with links to the classes they belong to:

- m -

• main2prime() : gum::FMDP< GUM_SCALAR >
• mainImport() : gum::prm::o3prmr::O3prmrContext< GUM_SCALAR >
• makeAbstract() : gum::IScheduleMultiDim, gum::ScheduleMultiDim< TABLE >
• makeArgMax_() : gum::StructuredPlaner< GUM_SCALAR >
• makeClique() : gum::SimplicialSet
• makeInference() : gum::credal::CNLoopyPropagation< GUM_SCALAR >, gum::credal::CNMonteCarloSampling< GUM_SCALAR, BNInferenceEngine >, gum::credal::InferenceEngine< GUM_SCALAR >, gum::credal::MultipleInferenceEngine< GUM_SCALAR, BNInferenceEngine >, gum::GraphicalModelInference< GUM_SCALAR >
• makeInference_() : gum::GraphicalModelInference< GUM_SCALAR >, gum::InformationTheory< INFERENCE_ENGINE, GUM_SCALAR >, gum::LazyPropagation< GUM_SCALAR >, gum::LoopyBeliefPropagation< GUM_SCALAR >, gum::LoopySamplingInference< GUM_SCALAR, APPROX >, gum::SamplingInference< GUM_SCALAR >, gum::ShaferShenoyInference< GUM_SCALAR >, gum::ShaferShenoyLIMIDInference< GUM_SCALAR >, gum::ShaferShenoyMRFInference< GUM_SCALAR >, gum::VariableElimination< GUM_SCALAR >
• makeInferenceByOrderedArcs_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• makeInferenceByRandomOrder_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• makeInferenceNodeToNeighbours_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• makePlanning() : gum::AdaptiveRMaxPlaner, gum::IPlanningStrategy< GUM_SCALAR >, gum::SDYNA, gum::StructuredPlaner< GUM_SCALAR >
• makeResultsPersistent() : gum::ScheduleOperator
• manager() : gum::MultiDimFunctionGraph< GUM_SCALAR, TerminalNodePolicy >
• map() : gum::HashTable< Key, Val >, gum::List< Val >
• mapMainPrime() : gum::FMDP< GUM_SCALAR >
• mapToDot() : gum::CliqueGraph
• marginalization() : gum::DecisionTensor< GUM_SCALAR >
• marginalize_() : gum::learning::IndependenceTest, gum::learning::Score
• marginalMax() : gum::credal::InferenceEngine< GUM_SCALAR >
• marginalMin() : gum::credal::InferenceEngine< GUM_SCALAR >
• MarginalTargetedInference() : gum::MarginalTargetedInference< GUM_SCALAR >
• MarginalTargetedMRFInference() : gum::MarginalTargetedMRFInference< GUM_SCALAR >
• MarkovBlanket() : gum::MarkovBlanket
• matches() : gum::prm::GSpan< GUM_SCALAR >
• Max() : gum::aggregator::Max< GUM_SCALAR >
• max() : gum::Dirichlet, gum::Tensor< GUM_SCALAR >
• max_indep_set() : gum::prm::gspan::DFSTree< GUM_SCALAR >
• maxArcs() : gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >
• maximiseQactions_() : gum::StructuredPlaner< GUM_SCALAR >
• maximize() : gum::IOperatorStrategy< GUM_SCALAR >, gum::MDDOperatorStrategy< GUM_SCALAR >, gum::TreeOperatorStrategy< GUM_SCALAR >
• maxIn() : gum::Tensor< GUM_SCALAR >
• maxIndegree() : gum::learning::StructuralConstraintIndegree
• MaxInducedWidthMCBayesNetGenerator() : gum::MaxInducedWidthMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• maxIter() : gum::ApproximationScheme, gum::IApproximationSchemeConfiguration, gum::learning::IBNLearner
• maxLog10CliqueDomainSize() : gum::Triangulation
• maxlog10InducedWidth() : gum::MaxInducedWidthMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• maxMemory() : gum::ScheduledInference, gum::Scheduler
• maxModality() : gum::IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >
• maxNode_() : gum::BinSearchTree< Val, Cmp, Node >
• maxNonOne() : gum::Tensor< GUM_SCALAR >
• maxNonOneParam() : gum::IBayesNet< GUM_SCALAR >, gum::IMarkovRandomField< GUM_SCALAR >
• maxOut() : gum::Tensor< GUM_SCALAR >
• maxParam() : gum::IBayesNet< GUM_SCALAR >, gum::IMarkovRandomField< GUM_SCALAR >
• maxParents() : gum::MaxParentsMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• MaxParentsMCBayesNetGenerator() : gum::MaxParentsMCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• maxPrimeSubgraphTree() : gum::IncrementalTriangulation, gum::StaticTriangulation, gum::Triangulation
• maxTime() : gum::ApproximationScheme, gum::IApproximationSchemeConfiguration, gum::learning::IBNLearner
• maxVal() : gum::RangeVariable
• maxValue() : gum::BinSearchTree< Val, Cmp, Node >
• maxVarDomainSize() : gum::IBayesNet< GUM_SCALAR >, gum::IMarkovRandomField< GUM_SCALAR >
• MCBayesNetGenerator() : gum::MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber >
• MDDOperatorStrategy() : gum::MDDOperatorStrategy< GUM_SCALAR >
• meanVar() : gum::DecisionTensor< GUM_SCALAR >, gum::InfluenceDiagramInference< GUM_SCALAR >, gum::ShaferShenoyLIMIDInference< GUM_SCALAR >
• Median() : gum::aggregator::Median< GUM_SCALAR >
• MeekRules() : gum::MeekRules
• memoryFootprint() : gum::IBayesNet< GUM_SCALAR >, gum::Tensor< GUM_SCALAR >
• memoryUsage() : gum::MultiDimCombination< TABLE >, gum::MultiDimCombinationDefault< TABLE >, gum::MultiDimCombineAndProject< TABLE >, gum::MultiDimCombineAndProjectDefault< TABLE >, gum::MultiDimProjection< TABLE >, gum::ScheduleBinaryCombination< TABLE1, TABLE2, TABLE_RES >, gum::ScheduleOperator, gum::ScheduleProjection< TABLE >, gum::Scheduler, gum::SchedulerParallel, gum::SchedulerSequential, gum::ScheduleStorage< TABLE, CONTAINER >
• messageApproximationScheme() : gum::IApproximationSchemeConfiguration
• MEU() : gum::InfluenceDiagramInference< GUM_SCALAR >, gum::ShaferShenoyLIMIDInference< GUM_SCALAR >
• migrateNode_() : gum::MultiDimFunctionGraphManager< GUM_SCALAR, TerminalNodePolicy >
• Miic() : gum::learning::Miic
• Min() : gum::aggregator::Min< GUM_SCALAR >
• min() : gum::Dirichlet, gum::Tensor< GUM_SCALAR >
• minEpsilonRate() : gum::ApproximationScheme, gum::IApproximationSchemeConfiguration, gum::learning::IBNLearner
• minimalCondSet() : gum::DAG, gum::DAGmodel, gum::IMarkovRandomField< GUM_SCALAR >
• minimiseFunctions_() : gum::StructuredPlaner< GUM_SCALAR >
• minimize() : gum::IOperatorStrategy< GUM_SCALAR >, gum::MDDOperatorStrategy< GUM_SCALAR >, gum::TreeOperatorStrategy< GUM_SCALAR >
• minimizeSize() : gum::MultiDimFunctionGraphManager< GUM_SCALAR, TerminalNodePolicy >
• minIn() : gum::Tensor< GUM_SCALAR >
• minNbRowsPerThread() : gum::learning::CorrectedMutualInformation, gum::learning::IDatabaseTable< T_DATA >, gum::learning::IndependenceTest, gum::learning::KNML, gum::learning::ParamEstimator, gum::learning::PseudoCount, gum::learning::RecordCounter, gum::learning::Score
• minNode_() : gum::BinSearchTree< Val, Cmp, Node >
• minNonZero() : gum::Tensor< GUM_SCALAR >
• minNonZeroParam() : gum::IBayesNet< GUM_SCALAR >, gum::IMarkovRandomField< GUM_SCALAR >
• minOut() : gum::Tensor< GUM_SCALAR >
• minParam() : gum::IBayesNet< GUM_SCALAR >, gum::IMarkovRandomField< GUM_SCALAR >
• minVal() : gum::RangeVariable
• minValue() : gum::BinSearchTree< Val, Cmp, Node >
• missingSymbols() : gum::learning::DBTranslator, gum::learning::IBNLearner::Database, gum::learning::IDatabaseTable< T_DATA >
• missingValue() : gum::learning::DBTranslator4ContinuousVariable, gum::learning::DBTranslator4DiscretizedVariable, gum::learning::DBTranslator4IntegerVariable, gum::learning::DBTranslator4LabelizedVariable, gum::learning::DBTranslator4NumericalDiscreteVariable, gum::learning::DBTranslator4RangeVariable, gum::learning::DBTranslator
• MixedGraph() : gum::MixedGraph
• MixedGraphListener() : gum::MixedGraphListener
• mixedOrientedPath() : gum::MixedGraph
• mixedUnorientedPath() : gum::MixedGraph
• modalities() : gum::prm::ClassBayesNet< GUM_SCALAR >, gum::prm::ClassDependencyGraph< GUM_SCALAR >, gum::prm::InstanceBayesNet< GUM_SCALAR >
• modality() : gum::Observation
• modaMax() : gum::FMDPLearner< VariableAttributeSelection, RewardAttributeSelection, LearnerSelection >, gum::ILearningStrategy
• model() : gum::GraphicalModelInference< GUM_SCALAR >, gum::MultiDimFunctionGraph< GUM_SCALAR, TerminalNodePolicy >
• modelSize() : gum::SDYNA
• modifyGraph() : gum::learning::GraphChangesGenerator4DiGraph< STRUCT_CONSTRAINT >, gum::learning::GraphChangesGenerator4K2< STRUCT_CONSTRAINT >, gum::learning::GraphChangesGenerator4UndiGraph< STRUCT_CONSTRAINT >, gum::learning::GraphChangesGeneratorOnSubDiGraph< STRUCT_CONSTRAINT >, gum::learning::IGraphChangesGenerator4DiGraph, gum::learning::IGraphChangesGenerator4UndiGraph, gum::learning::StructuralConstraintSetStatic< CONSTRAINT1, OTHER_CONSTRAINTS >
• modifyGraphAlone() : gum::learning::StructuralConstraintDAG, gum::learning::StructuralConstraintDiGraph, gum::learning::StructuralConstraintForbiddenArcs, gum::learning::StructuralConstraintIndegree, gum::learning::StructuralConstraintMandatoryArcs, gum::learning::StructuralConstraintNoChildrenNodes, gum::learning::StructuralConstraintNoParentNodes, gum::learning::StructuralConstraintPossibleEdges, gum::learning::StructuralConstraintSliceOrder, gum::learning::StructuralConstraintTabuList, gum::learning::StructuralConstraintUndiGraph
• monteCarloSample() : gum::GibbsOperator< GUM_SCALAR >
• monteCarloSample_() : gum::GibbsSampling< GUM_SCALAR >
• MonteCarloSampling() : gum::MonteCarloSampling< GUM_SCALAR >
• moralGraph() : gum::DAG, gum::DAGmodel, gum::PDAG
• moralGraph_() : gum::InfluenceDiagram< GUM_SCALAR >
• moralizedAncestralGraph() : gum::DAG, gum::DAGmodel, gum::PDAG
• moveTo() : gum::MultiDimFunctionGraphManager< GUM_SCALAR, TerminalNodePolicy >
• moveTriangulation() : gum::JunctionTreeStrategy
• mpe() : gum::LazyPropagation< GUM_SCALAR >
• mpeLog2Posterior() : gum::LazyPropagation< GUM_SCALAR >
• MRF() : gum::MRFInference< GUM_SCALAR >
• MRFInference() : gum::MRFInference< GUM_SCALAR >
• MRFReader() : gum::MRFReader< GUM_SCALAR >
• MRFWriter() : gum::MRFWriter< GUM_SCALAR >
• msgL_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• msgP_() : gum::credal::CNLoopyPropagation< GUM_SCALAR >
• multiDim() : gum::ScheduleMultiDim< TABLE >
• MultiDimAdressable() : gum::MultiDimAdressable
• MultiDimAggregator() : gum::aggregator::MultiDimAggregator< GUM_SCALAR >
• MultiDimArray() : gum::MultiDimArray< GUM_SCALAR >
• MultiDimBijArray() : gum::MultiDimBijArray< GUM_SCALAR >
• MultiDimBucket() : gum::MultiDimBucket< GUM_SCALAR >
• MultiDimCombination() : gum::MultiDimCombination< TABLE >
• MultiDimCombinationDefault() : gum::MultiDimCombinationDefault< TABLE >
• MultiDimCombineAndProject() : gum::MultiDimCombineAndProject< TABLE >
• MultiDimCombineAndProjectDefault() : gum::MultiDimCombineAndProjectDefault< TABLE >
• MultiDimCompleteProjection() : gum::MultiDimCompleteProjection< GUM_SCALAR, TABLE >
• MultiDimContainer() : gum::MultiDimContainer< GUM_SCALAR >
• MultiDimDecorator() : gum::MultiDimDecorator< GUM_SCALAR >
• MultiDimFunctionGraph() : gum::MultiDimFunctionGraph< GUM_SCALAR, TerminalNodePolicy >
• MultiDimFunctionGraphGenerator() : gum::MultiDimFunctionGraphGenerator
• MultiDimFunctionGraphManager() : gum::MultiDimFunctionGraphManager< GUM_SCALAR, TerminalNodePolicy >
• MultiDimFunctionGraphOperator() : gum::MultiDimFunctionGraphOperator< GUM_SCALAR, FUNCTOR, TerminalNodePolicy >
• MultiDimFunctionGraphProjector() : gum::MultiDimFunctionGraphProjector< GUM_SCALAR, FUNCTOR, TerminalNodePolicy >
• MultiDimFunctionGraphROManager() : gum::MultiDimFunctionGraphROManager< GUM_SCALAR, TerminalNodePolicy >
• MultiDimFunctionGraphTreeManager() : gum::MultiDimFunctionGraphTreeManager< GUM_SCALAR, TerminalNodePolicy >
• MultiDimICIModel() : gum::MultiDimICIModel< GUM_SCALAR >
• MultiDimImplementation() : gum::MultiDimImplementation< GUM_SCALAR >
• MultiDimLogit() : gum::MultiDimLogit< GUM_SCALAR >
• MultiDimNoisyAND() : gum::MultiDimNoisyAND< GUM_SCALAR >
• MultiDimNoisyORCompound() : gum::MultiDimNoisyORCompound< GUM_SCALAR >
• MultiDimNoisyORNet() : gum::MultiDimNoisyORNet< GUM_SCALAR >
• MultiDimPartialInstantiation() : gum::MultiDimPartialInstantiation< GUM_SCALAR, TABLE >
• MultiDimProjection() : gum::MultiDimProjection< TABLE >
• MultiDimReadOnly() : gum::MultiDimReadOnly< GUM_SCALAR >
• multidims() : gum::MultiDimBucket< GUM_SCALAR >
• MultiDimSparse() : gum::MultiDimSparse< GUM_SCALAR >
• MultiDimWithOffset() : gum::MultiDimWithOffset< GUM_SCALAR >
• MultipleInferenceEngine() : gum::credal::MultipleInferenceEngine< GUM_SCALAR, BNInferenceEngine >
• multiply() : gum::credal::lp::LpExpr, gum::IOperatorStrategy< GUM_SCALAR >, gum::MDDOperatorStrategy< GUM_SCALAR >, gum::TreeOperatorStrategy< GUM_SCALAR >
• MultiPriorityQueue() : gum::MultiPriorityQueue< Val, Priority, Cmp >
• mutualInformation() : gum::learning::IBNLearner
• mutualInformationXY() : gum::InformationTheory< INFERENCE_ENGINE, GUM_SCALAR >
• mutualInformationXYgivenZ() : gum::InformationTheory< INFERENCE_ENGINE, GUM_SCALAR >