Parses a given list of options.
Valid options are:
-L <num>
The lower run number to start the experiment from.
(default 1)
-U <num>
The upper run number to end the experiment at (inclusive).
(default 10)
-T <arff file>
The dataset to run the experiment on.
(required, may be specified multiple times)
-P <class name>
The full class name of a ResultProducer (required).
eg: weka.experiment.RandomSplitResultProducer
-D <class name>
The full class name of a ResultListener (required).
eg: weka.experiment.CSVResultListener
-N <string>
A string containing any notes about the experiment.
(default none)
Options specific to result producer weka.experiment.RandomSplitResultProducer:
-P <percent>
The percentage of instances to use for training.
(default 66)
-D
Save raw split evaluator output.
-O <file/directory name/path>
The filename where raw output will be stored.
If a directory name is specified then then individual
outputs will be gzipped, otherwise all output will be
zipped to the named file. Use in conjuction with -D. (default splitEvalutorOut.zip)
-W <class name>
The full class name of a SplitEvaluator.
eg: weka.experiment.ClassifierSplitEvaluator
-R
Set when data is not to be randomized and the data sets' size.
Is not to be determined via probabilistic rounding.
Options specific to split evaluator weka.experiment.ClassifierSplitEvaluator:
-W <class name>
The full class name of the classifier.
eg: weka.classifiers.bayes.NaiveBayes
-C <index>
The index of the class for which IR statistics
are to be output. (default 1)
-I <index>
The index of an attribute to output in the
results. This attribute should identify an
instance in order to know which instances are
in the test set of a cross validation. if 0
no output (default 0).
-P
Add target and prediction columns to the result
for each fold.
Options specific to classifier weka.classifiers.rules.ZeroR:
-D
If set, classifier is run in debug mode and
may output additional info to the console
All options after -- will be passed to the result producer.