49#ifndef GUM_D_SEPARATION_ALGORITHM_H
50#define GUM_D_SEPARATION_ALGORITHM_H
118 template <
typename GUM_SCALAR,
class TABLE >
Class representing the minimal interface for Bayesian network with no numerical data.
Class representing the minimal interface for Bayesian network with no numerical data.
~dSeparationAlgorithm()
destructor
void requisiteNodes(const DAG &dag, const NodeSet &query, const NodeSet &hardEvidence, const NodeSet &softEvidence, NodeSet &requisite) const
Fill the 'requisite' nodeset with the requisite nodes in dag given a query and evidence.
dSeparationAlgorithm()
default constructor
dSeparationAlgorithm & operator=(const dSeparationAlgorithm &from)
copy operator
void relevantTensors(const IBayesNet< GUM_SCALAR > &bn, const NodeSet &query, const NodeSet &hardEvidence, const NodeSet &softEvidence, Set< const TABLE * > &tensors)
update a set of tensors, keeping only those d-connected with query variables given evidence
d-separation analysis (as described in Koller & Friedman 2009)
d-separation analysis (as described in Koller & Friedman 2009)
Set< NodeId > NodeSet
Some typdefs and define for shortcuts ...
gum is the global namespace for all aGrUM entities