This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and return the best structure of the various runs.
Valid options are:
-U <integer>
Number of runs
-A <seed>
Random number seed
-P <nr of parents>
Maximum number of parents
-R
Use arc reversal operation.
(default false)
-N
Initial structure is empty (instead of Naive Bayes)
-mbc
Applies a Markov Blanket correction to the network structure,
after a network structure is learned. |