| __arc_probas | gum::learning::Miic | private |
| __empty_set | gum::learning::Miic | private |
| __existsDirectedPath(const MixedGraph &graph, const NodeId n1, const NodeId n2) const | gum::learning::Miic | private |
| __initial_marks | gum::learning::Miic | private |
| __latent_couples | gum::learning::Miic | private |
| __maxLog | gum::learning::Miic | private |
| __N | gum::learning::Miic | private |
| __usemiic | gum::learning::Miic | private |
| _burn_in | gum::ApproximationScheme | protected |
| _current_epsilon | gum::ApproximationScheme | protected |
| _current_rate | gum::ApproximationScheme | protected |
| _current_state | gum::ApproximationScheme | protected |
| _current_step | gum::ApproximationScheme | protected |
| _enabled_eps | gum::ApproximationScheme | protected |
| _enabled_max_iter | gum::ApproximationScheme | protected |
| _enabled_max_time | gum::ApproximationScheme | protected |
| _enabled_min_rate_eps | gum::ApproximationScheme | protected |
| _eps | gum::ApproximationScheme | protected |
| _findBestContributor(NodeId x, NodeId y, const std::vector< NodeId > &ui, const MixedGraph &graph, CorrectedMutualInformation<> &I, Heap< std::pair< std::tuple< NodeId, NodeId, NodeId, std::vector< NodeId > > *, double >, GreaterPairOn2nd > &_rank) | gum::learning::Miic | protected |
| _getUnshieldedTriples(const MixedGraph &graph, CorrectedMutualInformation<> &I, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sep_set) | gum::learning::Miic | protected |
| _getUnshieldedTriplesMIIC(const MixedGraph &graph, CorrectedMutualInformation<> &I, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sep_set, HashTable< std::pair< NodeId, NodeId >, char > &marks) | gum::learning::Miic | protected |
| _history | gum::ApproximationScheme | protected |
| _initiation(CorrectedMutualInformation<> &I, MixedGraph &graph, HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sep_set, Heap< std::pair< std::tuple< NodeId, NodeId, NodeId, std::vector< NodeId > > *, double >, GreaterPairOn2nd > &_rank) | gum::learning::Miic | protected |
| _iteration(CorrectedMutualInformation<> &I, MixedGraph &graph, HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sep_set, Heap< std::pair< std::tuple< NodeId, NodeId, NodeId, std::vector< NodeId > > *, double >, GreaterPairOn2nd > &_rank) | gum::learning::Miic | protected |
| _last_epsilon | gum::ApproximationScheme | protected |
| _max_iter | gum::ApproximationScheme | protected |
| _max_time | gum::ApproximationScheme | protected |
| _min_rate_eps | gum::ApproximationScheme | protected |
| _orientation_3off2(CorrectedMutualInformation<> &I, MixedGraph &graph, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sep_set) | gum::learning::Miic | protected |
| _orientation_latents(CorrectedMutualInformation<> &I, MixedGraph &graph, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sep_set) | gum::learning::Miic | protected |
| _orientation_miic(CorrectedMutualInformation<> &I, MixedGraph &graph, const HashTable< std::pair< NodeId, NodeId >, std::vector< NodeId > > &sep_set) | gum::learning::Miic | protected |
| _period_size | gum::ApproximationScheme | protected |
| _propagatesHead(MixedGraph &graph, NodeId node) | gum::learning::Miic | protected |
| _timer | gum::ApproximationScheme | protected |
| _updateProbaTriples(const MixedGraph &graph, std::vector< std::tuple< std::tuple< NodeId, NodeId, NodeId > *, double, double, double > > proba_triples) | gum::learning::Miic | protected |
| _verbosity | gum::ApproximationScheme | protected |
| addConstraints(HashTable< std::pair< NodeId, NodeId >, char > constraints) | gum::learning::Miic | |
| ApproximationScheme(bool verbosity=false) | gum::ApproximationScheme | |
| ApproximationSchemeSTATE enum name | gum::IApproximationSchemeConfiguration | |
| continueApproximationScheme(double error) | gum::ApproximationScheme | |
| currentTime() const | gum::ApproximationScheme | virtual |
| disableEpsilon() | gum::ApproximationScheme | virtual |
| disableMaxIter() | gum::ApproximationScheme | virtual |
| disableMaxTime() | gum::ApproximationScheme | virtual |
| disableMinEpsilonRate() | gum::ApproximationScheme | virtual |
| enableEpsilon() | gum::ApproximationScheme | virtual |
| enableMaxIter() | gum::ApproximationScheme | virtual |
| enableMaxTime() | gum::ApproximationScheme | virtual |
| enableMinEpsilonRate() | gum::ApproximationScheme | virtual |
| epsilon() const | gum::ApproximationScheme | virtual |
| history() const | gum::ApproximationScheme | virtual |
| IApproximationSchemeConfiguration() | gum::IApproximationSchemeConfiguration | |
| initApproximationScheme() | gum::ApproximationScheme | |
| isEnabledEpsilon() const | gum::ApproximationScheme | virtual |
| isEnabledMaxIter() const | gum::ApproximationScheme | virtual |
| isEnabledMaxTime() const | gum::ApproximationScheme | virtual |
| isEnabledMinEpsilonRate() const | gum::ApproximationScheme | virtual |
| latentVariables() const | gum::learning::Miic | |
| learnBN(GRAPH_CHANGES_SELECTOR &selector, PARAM_ESTIMATOR &estimator, DAG initial_dag=DAG()) | gum::learning::Miic | |
| learnMixedStructure(CorrectedMutualInformation<> &I, MixedGraph graph) | gum::learning::Miic | |
| learnStructure(CorrectedMutualInformation<> &I, MixedGraph graph) | gum::learning::Miic | |
| maxIter() const | gum::ApproximationScheme | virtual |
| maxTime() const | gum::ApproximationScheme | virtual |
| messageApproximationScheme() const | gum::IApproximationSchemeConfiguration | |
| Miic() | gum::learning::Miic | |
| Miic(int maxLog) | gum::learning::Miic | |
| Miic(const Miic &from) | gum::learning::Miic | |
| Miic(Miic &&from) | gum::learning::Miic | |
| 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 | |
| periodSize() const | gum::ApproximationScheme | virtual |
| remainingBurnIn() | gum::ApproximationScheme | |
| set3off2Behaviour() | 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 | |
| updateApproximationScheme(unsigned int incr=1) | gum::ApproximationScheme | |
| verbosity() const | gum::ApproximationScheme | virtual |
| ~ApproximationScheme() | gum::ApproximationScheme | virtual |
| ~IApproximationSchemeConfiguration() | gum::IApproximationSchemeConfiguration | |
| ~Miic() | gum::learning::Miic | |
