78 template < TESTNAME AttributeSelection,
bool isScalar = false >
100 double attributeSelectionThreshold,
116 double attributeSelectionThreshold,
Base class for discrete random variable.
void updateFunctionGraph() override
Updates target to currently learned graph structure.
NodeId _insertTerminalNode_(NodeId src)
Insert a terminal node in the target.
double _attributeSelectionThreshold_
The threshold above which we consider variables to be dependant.
void removeNode_(NodeId removedNodeId) override
Removes a node from the internal graph.
HashTable< NodeId, bool > _staleTable_
Hashtable indicating if given node has been modified (upon receiving new exemple or through a transpo...
void updateGraph() override
Updates the internal graph after a new observation has been added.
NodeId _insertNodeInFunctionGraph_(NodeId src)
Inserts an internal node in the target.
Idx _nbTotalObservation_
The total number of observation added to this tree.
ITI(MultiDimFunctionGraph< double > *target, double attributeSelectionThreshold, gum::VariableSet attributeListe, const DiscreteVariable *learnedValue)
ITI constructor for functions describing the behaviour of one variable according to a set of other va...
NodeId insertNode_(NodeDatabase< AttributeSelection, isScalar > *nDB, const DiscreteVariable *boundVar) override
inserts a new node in internal graph
void insertSetOfVars_(MultiDimFunctionGraph< double > *ret)
insertSetOfVars_
void addObservation(const Observation *obs) override
Inserts a new observation.
void chgNodeBoundVar_(NodeId chgedNodeId, const DiscreteVariable *desiredVar) override
Changes the associated variable of a node.
~ITI() override
Default destructor.
void updateNodeWithObservation_(const Observation *newObs, NodeId currentNodeId) override
Will update internal graph's NodeDatabase of given node with the new observation.
IncrementalGraphLearner(MultiDimFunctionGraph< double > *target, gum::VariableSet attributesSet, const DiscreteVariable *learnVariable)
<agrum/FMDP/learning/datastructure/nodeDatabase.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.
Priority queues in which the same element can appear several times.
gum is the global namespace for all aGrUM entities
Set< const DiscreteVariable * > VariableSet