73 template < TESTNAME AttributeSelection,
bool isScalar = false >
85 double attributeSelectionThreshold,
86 double pairSelectionThreshold,
94 double attributeSelectionThreshold,
95 double pairSelectionThreshold,
<agrum/FMDP/learning/datastructure/leaves/abstractLeaf.h>
Base class for discrete random variable.
The class for generic Hash Tables.
void _addLeaf_(NodeId)
Adds a new observation to the structure.
NodeId _insertLeafInFunctionGraph_(AbstractLeaf *, Int2Type< true >)
Computes the score of the given variables for the given node.
void updateNodeWithObservation_(const Observation *newObs, NodeId currentNodeId)
Adds a new observation to the structure.
void updateFunctionGraph()
Computes the score of the given variables for the given node.
void _updateNodeSet_(Set< NodeId > &, const DiscreteVariable *, VariableSelector &)
For each node in the given set, this methods checks whether or not we should installed the given vari...
Idx _nbTotalObservation_
The total number of observation added to this tree.
IMDDI(MultiDimFunctionGraph< double > *target, double attributeSelectionThreshold, double pairSelectionThreshold, gum::VariableSet attributeListe, const DiscreteVariable *learnedValue)
Variable Learner constructor.
void _removeLeaf_(NodeId)
Adds a new observation to the structure.
~IMDDI()
Default destructor.
void _updateScore_(const DiscreteVariable *, NodeId, VariableSelector &vs)
Computes the score of the given variables for the given node.
void removeNode_(NodeId removedNodeId)
Adds a new observation to the structure.
Sequence< const DiscreteVariable * > _varOrder_
void _downdateScore_(const DiscreteVariable *, NodeId, VariableSelector &vs)
Computes the score of the given variables for the given node.
double _attributeSelectionThreshold_
The threshold above which we consider variables to be dependant.
void chgNodeBoundVar_(NodeId chgedNodeId, const DiscreteVariable *desiredVar)
Adds a new observation to the structure.
HashTable< NodeId, AbstractLeaf * > _leafMap_
void updateGraph()
Updates the tree after a new observation has been added.
void insertSetOfVars(MultiDimFunctionGraph< double > *ret) const
void _rebuildFunctionGraph_()
Computes the score of the given variables for the given node.
NodeId insertLeafNode_(NodeDatabase< AttributeSelection, isScalar > *nDB, const DiscreteVariable *boundVar, Set< const Observation * > *sonsMap)
Adds a new observation to the structure.
void addObservation(const Observation *)
Adds a new observation to the structure.
IncrementalGraphLearner(MultiDimFunctionGraph< double > *target, gum::VariableSet attributesSet, const DiscreteVariable *learnVariable)
<agrum/FMDP/learning/FunctionGraph/leafAggregator.h>
virtual void add(const DiscreteVariable &v)
Adds a new var to the variables of the multidimensional matrix.
<agrum/FMDP/learning/datastructure/nodeDatabase.h>
Safe iterators for Sequence.
The generic class for storing (ordered) sequences of objects.
<agrum/FMDP/planning/FunctionGraph/variableselector.h>
Size Idx
Type for indexes.
Size NodeId
Type for node ids.
Headers of the interface specifying functions to be implemented by any incremental learner.
Headers of the Leaf Aggregator class.
gum is the global namespace for all aGrUM entities
Set< const DiscreteVariable * > VariableSet
Headers of the Variable Selector class.