Abstract Bayesian Multi-nets (BMNs) are a special kind of Bayesian network (BN) classifiers
that consist of several local Bayesian networks, one for each predictable class, to model an
asymmetric set of variable dependencies given each class value. Deterministic methods
using greedy local search are the most frequently used methods for learning the structure of
BMNs based on optimizing a scoring function. Ant Colony Optimization (ACO) is a meta-
heuristic global search method for solving combinatorial optimization problems, inspired by …

Abstract Bayesian Multi-nets (BMNs) are a special kind of Bayesian network (BN) classifiers
that consist of several local Bayesian networks, one for each predictable class, to model an
asymmetric set of variable dependencies given each class value. Deterministic methods
using greedy local search are the most frequently used methods for learning the structure of
BMNs based on optimizing a scoring function. Ant Colony Optimization (ACO) is a meta-
heuristic global search method for solving combinatorial optimization problems, inspired by …