IBk(formula, data, subset, na.action, control = Weka_control(), options = NULL)
LBR(formula, data, subset, na.action, control = Weka_control(), options = NULL)
NA
s. See model.frame
for
details.Weka_control
giving
options to be passed to the Weka learner. Available options can be
obtained on-line using the Weka Option Wizard WOW
, or
the Weka documentation.NULL
(default). See Details.Weka_lazy
and
Weka_classifiers
with components includingpredict
method for
predicting from the fitted models, and a summary
method based
on evaluate_Weka_classifier
. IBk
provides a $k$-nearest neighbors classifier, see Aha &
Kibler (1991).
LBR
(Lazy Bayesian Rules) implements a lazy learning
approach to lessening the attribute-independence assumption of naive
Bayes as suggested by Zheng & Webb (2000).
The model formulae should only use the + and - operators to indicate the variables to be included or not used, respectively.
Argument options
allows further customization. Currently,
options model
and instances
(or partial matches for
these) are used: if set to TRUE
, the model frame or the
corresponding Weka instances, respectively, are included in the fitted
model object, possibly speeding up subsequent computations on the
object. By default, neither is included.