/**
* Returns an enumeration describing the available options.
* @return an enumeration of all the available options.
**/
public Enumeration listOptions () {
Vector newVector = new Vector(4);
newVector.addElement(new Option(
"\tclass name of base learner to use for \taccuracy estimation.\n"
+ "\tPlace any classifier options LAST on the command line\n"
+ "\tfollowing a \"--\". eg.:\n"
+ "\t\t-B weka.classifiers.bayes.NaiveBayes ... -- -K\n"
+ "\t(default: weka.classifiers.rules.ZeroR)",
"B", 1, "-B <base learner>"));
newVector.addElement(new Option(
"\tnumber of cross validation folds to use for estimating accuracy.\n"
+ "\t(default=5)",
"F", 1, "-F <num>"));
newVector.addElement(new Option(
"\tSeed for cross validation accuracy testimation.\n"
+ "\t(default = 1)",
"R", 1,"-R <seed>"));
newVector.addElement(new Option(
"\tthreshold by which to execute another cross validation\n"
+ "\t(standard deviation---expressed as a percentage of the mean).\n"
+ "\t(default: 0.01 (1%))",
"T", 1, "-T <num>"));
newVector.addElement(new Option(
"\tPerformance evaluation measure to use for selecting attributes.\n" +
"\t(Default = accuracy for discrete class and rmse for numeric class)",
"E", 1, "-E <acc | rmse | mae | f-meas | auc>"));
if ((m_BaseClassifier != null) &&
(m_BaseClassifier instanceof OptionHandler)) {
newVector.addElement(new Option("", "", 0, "\nOptions specific to scheme "
+ m_BaseClassifier.getClass().getName()
+ ":"));
Enumeration enu = ((OptionHandler)m_BaseClassifier).listOptions();
while (enu.hasMoreElements()) {
newVector.addElement(enu.nextElement());
}
}
return newVector.elements();
}