SimulatedAnnealing (original) (raw)

This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring network structure.

For more information see:

R.R. Bouckaert (1995). Bayesian Belief Networks: from Construction to Inference. Utrecht, Netherlands.

BibTeX:

@phdthesis{Bouckaert1995, address = {Utrecht, Netherlands}, author = {R.R. Bouckaert}, institution = {University of Utrecht}, title = {Bayesian Belief Networks: from Construction to Inference}, year = {1995} }

Valid options are:

-A Start temperature

-U Number of runs

-D Delta temperature

-R Random number seed

-mbc Applies a Markov Blanket correction to the network structure, after a network structure is learned. This ensures that all nodes in the network are part of the Markov blanket of the classifier node.

-S [LOO-CV|k-Fold-CV|Cumulative-CV] Score type (LOO-CV,k-Fold-CV,Cumulative-CV)

-Q Use probabilistic or 0/1 scoring. (default probabilistic scoring)