Common options for cross-validation based algorithms are:
initAsNaiveBayes, markovBlanketClassifier and maxNrOfParents (see Section 2 for description).
Further, for each of the cross-validation based algorithms the CVType can be chosen out of the following:
Finally, the useProb flag indicates whether the accuracy of the classifier should be estimated using the zero-one loss (if set to false) or using the estimated probability of the class.
The following search algorithms are implemented: K2, HillClimbing, RepeatedHillClimber, TAN, Tabu Search, Simulated Annealing and Genetic Search. See Section 2 for a description of the specific options for those algorithms.