Supervised learners, i.e., algorithms for classification and
regression, are termed classifiers by Weka. (Numeric
prediction, i.e., regression, is interpreted as prediction of a
continuous class.) R interface functions to Weka classifiers are created by
make_Weka_classifier, and have formals formula,
data, subset, na.action, and control
(default: none), where the first four have the usual meanings
for statistical modeling functions in R, and the last again specifies
the control options to be employed by the Weka learner. By default,
the model formulae should only use the + and - operators
to indicate the variables to be included or not used, respectively.
Objects created by these interfaces always inherit from class
Weka_classifier, and have at least suitable print,
summary (via evaluate_Weka_classifier), and
predict methods.