Learning Operators¶
This section includes learning operators that are used to make small, local changes to a given Bayesian network
structure. This is used for the score-and-search learning algorithms such as
GreedyHillClimbing,
MMHC and DMMHC.
There are two type of classes in this section: operators and operator sets:
The operators are the representation of a change in a Bayesian network structure.
The operator sets coordinate sets of operators. They can find the best operator over the set and update the score and availability of each operator in the set.