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aGrUM 2.3.2
a C++ library for (probabilistic) graphical models
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The Miic algorithm. More...
#include <string>#include <vector>#include <agrum/config.h>#include <agrum/base/core/approximations/approximationScheme.h>#include <agrum/base/core/heap.h>#include <agrum/base/graphs/PDAG.h>#include <agrum/BN/learning/correctedMutualInformation.h>#include "agrum/base/graphs/algorithms/MeekRules.h"Go to the source code of this file.
Classes | |
| class | gum::learning::GreaterPairOn2nd |
| class | gum::learning::GreaterAbsPairOn2nd |
| class | gum::learning::GreaterTupleOnLast |
| class | gum::learning::Miic |
| The Miic learning algorithm. More... | |
Namespaces | |
| namespace | gum |
| gum is the global namespace for all aGrUM entities | |
| namespace | gum::learning |
| include the inlined functions if necessary | |
Macros | |
| #define | GUM_SL_EMIT(x, y, action, explain) |
Typedefs | |
| using | gum::learning::CondThreePoints = std::tuple< NodeId, NodeId, NodeId, std::vector< NodeId > > |
| using | gum::learning::CondRanking = std::pair< CondThreePoints*, double > |
| using | gum::learning::ThreePoints = std::tuple< NodeId, NodeId, NodeId > |
| using | gum::learning::Ranking = std::pair< ThreePoints*, double > |
| using | gum::learning::ProbabilisticRanking = std::tuple< ThreePoints*, double, double, double > |
The Miic algorithm.
The Miic class implements the miic algorithm based on https://doi.org/10.1371/journal.pcbi.1005662. It starts by eliminating edges that correspond to independent variables to build the skeleton of the graph, and then directs the remaining edges to get an essential graph. Latent variables can be detected using bi-directed arcs.
Miic allows the option of adding constraints on the skeleton construction such as: a maximum number of parents, mandatory arcs, forbidden arcs or an order between the variables.
Definition in file Miic.h.
| #define GUM_SL_EMIT | ( | x, | |
| y, | |||
| action, | |||
| explain ) |
Definition at line 74 of file Miic.h.
Referenced by gum::learning::Miic::_orientingVstructureMiic_(), gum::learning::Miic::_propagatingOrientationMiic_(), gum::learning::Miic::initiation_(), gum::learning::Miic::iteration_(), and gum::learning::Miic::orientationMiic_().