50#ifndef GUM_LEARNING_STRUCTURAL_COMPARATOR_H
51#define GUM_LEARNING_STRUCTURAL_COMPARATOR_H
89 template <
typename GS1,
typename GS2 >
92 template <
typename GUM_SCALAR >
93 void compare(
const BayesNet< GUM_SCALAR >& ref,
const PDAG& test);
95 template <
typename GUM_SCALAR >
96 void compare(
const PDAG& ref,
const BayesNet< GUM_SCALAR >& test);
Class representing Bayesian networks.
Base classes for partially directed acyclic graphs.
Class representing a Bayesian network.
Base class for all oriented graphs.
Base class for partially directed acyclic graphs.
void compare(const BayesNet< GS1 > &ref, const BayesNet< GS2 > &test)
compare two BNs based on their DAG
double _true_edge_
Confusion matrix.
~StructuralComparator()
destructor
double recall() const
compare two DiGraphs
double precision_skeleton() const
Measures for the skeleton, aka graph without orientations.
void compare(const BayesNet< GUM_SCALAR > &ref, const PDAG &test)
compare a PDAG with the essential graph of a reference BN
double precision() const
Measures for the graphs.
void compare(const PDAG &ref, const BayesNet< GUM_SCALAR > &test)
compare the essential graph of a BN with a reference PDAG
double recall_skeleton() const
compare two DiGraphs
void compare(const UndiGraph &ref, const UndiGraph &test)
compare two UndiGraphs
StructuralComparator()
default constructor
void compare(const PDAG &ref, const PDAG &test)
compare two PDAGs
double f_score_skeleton() const
compare two DiGraphs
void compare(const DiGraph &ref, const DiGraph &test)
compare two DiGraphs
double f_score() const
compare two DiGraphs
Base class for undirected graphs.
gum is the global namespace for all aGrUM entities