| _arcProbas_ | gum::learning::Miic | private |
| _emptySet_ | gum::learning::Miic | private |
| _existsDirectedPath_(const MixedGraph &graph, NodeId n1, NodeId n2) | gum::learning::Miic | privatestatic |
| _existsNonTrivialDirectedPath_(const MixedGraph &graph, NodeId n1, NodeId n2) | gum::learning::Miic | privatestatic |
| _initialMarks_ | gum::learning::Miic | private |
| _isNotLatentCouple_(NodeId x, NodeId y) | gum::learning::Miic | private |
| _latentCouples_ | gum::learning::Miic | private |
| _maxLog_ | gum::learning::Miic | private |
| _orientingVstructureMiic_(MixedGraph &graph, HashTable< std::pair< NodeId, NodeId >, char > &marks, NodeId x, NodeId y, NodeId z, double p1, double p2) | gum::learning::Miic | private |
| _propagatingOrientationMiic_(MixedGraph &graph, HashTable< std::pair< NodeId, NodeId >, char > &marks, NodeId x, NodeId y, NodeId z, double p1, double p2) | gum::learning::Miic | private |
| _size_ | gum::learning::Miic | private |
| _useMiic_ | gum::learning::Miic | private |
| addConstraints(HashTable< std::pair< NodeId, NodeId >, char > constraints) | gum::learning::Miic | |
| ApproximationScheme(bool verbosity=false) | gum::ApproximationScheme | |
| ApproximationSchemeSTATE enum name | gum::IApproximationSchemeConfiguration | |
| burn_in_ | gum::ApproximationScheme | protected |
| continueApproximationScheme(double error) | gum::ApproximationScheme | |
| current_epsilon_ | gum::ApproximationScheme | protected |
| current_rate_ | gum::ApproximationScheme | protected |
| current_state_ | gum::ApproximationScheme | protected |
| current_step_ | gum::ApproximationScheme | protected |
| currentTime() const | gum::ApproximationScheme | virtual |
| disableEpsilon() | gum::ApproximationScheme | virtual |
| disableMaxIter() | gum::ApproximationScheme | virtual |
| disableMaxTime() | gum::ApproximationScheme | virtual |
| disableMinEpsilonRate() | gum::ApproximationScheme | virtual |
| enabled_eps_ | gum::ApproximationScheme | protected |
| enabled_max_iter_ | gum::ApproximationScheme | protected |
| enabled_max_time_ | gum::ApproximationScheme | protected |
| enabled_min_rate_eps_ | gum::ApproximationScheme | protected |
| enableEpsilon() | gum::ApproximationScheme | virtual |
| enableMaxIter() | gum::ApproximationScheme | virtual |
| enableMaxTime() | gum::ApproximationScheme | virtual |
| enableMinEpsilonRate() | gum::ApproximationScheme | virtual |
| eps_ | gum::ApproximationScheme | protected |
| epsilon() const | gum::ApproximationScheme | virtual |
| findBestContributor_(NodeId x, NodeId y, const std::vector< NodeId > &ui, const MixedGraph &graph, CorrectedMutualInformation<> &mutualInformation, Heap< CondRanking, GreaterPairOn2nd > &rank) | gum::learning::Miic | protected |
| history() const | gum::ApproximationScheme | virtual |
| history_ | gum::ApproximationScheme | protected |
| IApproximationSchemeConfiguration() | gum::IApproximationSchemeConfiguration | |
| initApproximationScheme() | gum::ApproximationScheme | |
| initiation_(CorrectedMutualInformation<> &mutualInformation, MixedGraph &graph, HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sepSet, Heap< CondRanking, GreaterPairOn2nd > &rank) | gum::learning::Miic | protected |
| isEnabledEpsilon() const | gum::ApproximationScheme | virtual |
| isEnabledMaxIter() const | gum::ApproximationScheme | virtual |
| isEnabledMaxTime() const | gum::ApproximationScheme | virtual |
| isEnabledMinEpsilonRate() const | gum::ApproximationScheme | virtual |
| isForbidenArc_(NodeId x, NodeId y) const | gum::learning::Miic | protected |
| isOrientable_(const MixedGraph &graph, NodeId xi, NodeId xj) const | gum::learning::Miic | protected |
| iteration_(CorrectedMutualInformation<> &mutualInformation, MixedGraph &graph, HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sepSet, Heap< CondRanking, GreaterPairOn2nd > &rank) | gum::learning::Miic | protected |
| last_epsilon_ | gum::ApproximationScheme | protected |
| latentVariables() const | gum::learning::Miic | |
| learnBN(GRAPH_CHANGES_SELECTOR &selector, PARAM_ESTIMATOR &estimator, DAG initial_dag=DAG()) | gum::learning::Miic | |
| learnMixedStructure(CorrectedMutualInformation<> &mutualInformation, MixedGraph graph) | gum::learning::Miic | |
| learnStructure(CorrectedMutualInformation<> &I, MixedGraph graph) | gum::learning::Miic | |
| max_iter_ | gum::ApproximationScheme | protected |
| max_time_ | gum::ApproximationScheme | protected |
| maxIter() const | gum::ApproximationScheme | virtual |
| maxTime() const | gum::ApproximationScheme | virtual |
| messageApproximationScheme() const | gum::IApproximationSchemeConfiguration | |
| Miic() | gum::learning::Miic | |
| Miic(int maxLog) | gum::learning::Miic | explicit |
| Miic(const Miic &from) | gum::learning::Miic | |
| Miic(Miic &&from) | gum::learning::Miic | |
| min_rate_eps_ | gum::ApproximationScheme | protected |
| minEpsilonRate() const | gum::ApproximationScheme | virtual |
| nbrIterations() const | gum::ApproximationScheme | virtual |
| onProgress | gum::IApproximationSchemeConfiguration | |
| onStop | gum::IApproximationSchemeConfiguration | |
| operator=(const Miic &from) | gum::learning::Miic | |
| operator=(Miic &&from) | gum::learning::Miic | |
| orientation3off2_(CorrectedMutualInformation<> &mutualInformation, MixedGraph &graph, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sepSet) | gum::learning::Miic | protected |
| orientationLatents_(CorrectedMutualInformation<> &mutualInformation, MixedGraph &graph, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sepSet) | gum::learning::Miic | protected |
| orientationMiic_(CorrectedMutualInformation<> &mutualInformation, MixedGraph &graph, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sepSet) | gum::learning::Miic | protected |
| period_size_ | gum::ApproximationScheme | protected |
| periodSize() const | gum::ApproximationScheme | virtual |
| propagatesOrientationInChainOfRemainingEdges_(MixedGraph &graph) | gum::learning::Miic | protected |
| propagatesRemainingOrientableEdges_(MixedGraph &graph, NodeId xj) | gum::learning::Miic | protected |
| remainingBurnIn() | gum::ApproximationScheme | |
| set3of2Behaviour() | gum::learning::Miic | |
| setEpsilon(double eps) | gum::ApproximationScheme | virtual |
| setMaxIter(Size max) | gum::ApproximationScheme | virtual |
| setMaxTime(double timeout) | gum::ApproximationScheme | virtual |
| setMiicBehaviour() | gum::learning::Miic | |
| setMinEpsilonRate(double rate) | gum::ApproximationScheme | virtual |
| setPeriodSize(Size p) | gum::ApproximationScheme | virtual |
| setVerbosity(bool v) | gum::ApproximationScheme | virtual |
| startOfPeriod() | gum::ApproximationScheme | |
| stateApproximationScheme() const | gum::ApproximationScheme | virtual |
| stopApproximationScheme() | gum::ApproximationScheme | |
| timer_ | gum::ApproximationScheme | protected |
| unshieldedTriples_(const MixedGraph &graph, CorrectedMutualInformation<> &mutualInformation, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sepSet) | gum::learning::Miic | protected |
| unshieldedTriplesMiic_(const MixedGraph &graph, CorrectedMutualInformation<> &mutualInformation, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sepSet, HashTable< std::pair< NodeId, NodeId >, char > &marks) | gum::learning::Miic | protected |
| updateApproximationScheme(unsigned int incr=1) | gum::ApproximationScheme | |
| updateProbaTriples_(const MixedGraph &graph, std::vector< ProbabilisticRanking > probaTriples) | gum::learning::Miic | protected |
| verbosity() const | gum::ApproximationScheme | virtual |
| verbosity_ | gum::ApproximationScheme | protected |
| ~ApproximationScheme() | gum::ApproximationScheme | virtual |
| ~IApproximationSchemeConfiguration() | gum::IApproximationSchemeConfiguration | |
| ~Miic() override | gum::learning::Miic | |
