Bayesian nets in the experimenter

Bayesian networks generate extra measures that can be examined in the experimenter. The experimenter can then be used to calculate mean and variance for those measures.

The following metrics are generated:

• measureExtraArcs: extra arcs compared to reference network. The network must be provided as BIFFile to the BayesNet class. If no such network is provided, this value is zero.
• measureMissingArcs: missing arcs compared to reference network or zero if not provided.
• measureReversedArcs: reversed arcs compared to reference network or zero if not provided.
• measureDivergence: divergence of network learned compared to reference network or zero if not provided.
• measureBayesScore: log of the K2 score of the network structure.
• measureBDeuScore: log of the BDeu score of the network structure.
• measureMDLScore: log of the MDL score.
• measureAICScore: log of the AIC score.
• measureEntropyScore:log of the entropy.