78 template < TESTNAME AttributeSelection,
bool isScalar = false >
100 double attributeSelectionThreshold,
116 double attributeSelectionThreshold,
267 varIter != this->setOfVars_.endSafe();
Base class for discrete random variable.
void chgNodeBoundVar_(NodeId chgedNodeId, const DiscreteVariable *desiredVar)
Changes the associated variable of a node.
NodeId _insertTerminalNode_(NodeId src)
Insert a terminal node in the target.
~ITI()
Default destructor.
double _attributeSelectionThreshold_
The threshold above which we consider variables to be dependant.
void removeNode_(NodeId removedNodeId)
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...
NodeId insertNode_(NodeDatabase< AttributeSelection, isScalar > *nDB, const DiscreteVariable *boundVar)
inserts a new node in internal graph
NodeId _insertNodeInFunctionGraph_(NodeId src)
Inserts an internal node in the target.
void updateGraph()
Updates the internal graph after a new observation has been added.
void updateFunctionGraph()
Updates target to currently learned graph structure.
Idx _nbTotalObservation_
The total number of observation added to this tree.
void updateNodeWithObservation_(const Observation *newObs, NodeId currentNodeId)
Will update internal graph's NodeDatabase of given node with the new observation.
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...
void addObservation(const Observation *obs)
Inserts a new observation.
void insertSetOfVars_(MultiDimFunctionGraph< double > *ret)
insertSetOfVars_
gum::VariableSet setOfVars_
IncrementalGraphLearner(MultiDimFunctionGraph< double > *target, gum::VariableSet attributesSet, const DiscreteVariable *learnVariable)
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 the Set class.
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