General options:
-t <name of training file>
Sets training file.
-T <name of test file>
Sets test file. If missing, a cross-validation will be performed on the
training data.
-c <class index>
Sets index of class attribute (default: last).
-x <number of folds>
Sets number of folds for cross-validation (default: 10).
-no-cv
Do not perform any cross validation.
-split-percentage <percentage>
Sets the percentage for the train/test set split, e.g., 66.
-preserve-order
Preserves the order in the percentage split.
-s <random number seed>
Sets random number seed for cross-validation or percentage split
(default: 1).
-m <name of file with cost matrix>
Sets file with cost matrix.
-l <name of input file>
Sets model input file. In case the filename ends with '.xml',
the options are loaded from the XML file.
-d <name of output file>
Sets model output file. In case the filename ends with '.xml',
only the options are saved to the XML file, not the model.
-v
Outputs no statistics for training data.
-o
Outputs statistics only, not the classifier.
-i
Outputs detailed information-retrieval statistics for each class.
-k
Outputs information-theoretic statistics.
-p <attribute range>
Only outputs predictions for test instances (or the train
instances if no test instances provided), along with attributes
(0 for none).
-distribution
Outputs the distribution instead of only the prediction
in conjunction with the '-p' option (only nominal classes).
-r
Only outputs cumulative margin distribution.
-g
Only outputs the graph representation of the classifier.
-xml filename | xml-string
Retrieves the options from the XML-data instead of the command line.
Options specific to weka.classifiers.bayes.BayesNet:
-D
Do not use ADTree data structure
-B <BIF file>
BIF file to compare with
-Q weka.classifiers.bayes.net.search.SearchAlgorithm
Search algorithm
-E weka.classifiers.bayes.net.estimate.SimpleEstimator
Estimator algorithm
The search algorithm option -Q and estimator option -E options are mandatory.
Note that it is important that the -E options should be used after the -Q option. Extra options can be passed to the search algorithm and the estimator after the class name specified following '-'.
For example:
java weka.classifiers.bayes.BayesNet -t iris.arff -D \ -Q weka.classifiers.bayes.net.search.local.K2 -- -P 2 -S ENTROPY \ -E weka.classifiers.bayes.net.estimate.SimpleEstimator -- -A 1.0