[<< wikibooks] Data Mining Algorithms In R/Packages/RWeka/Weka associators
== Description ==
R interfaces to Weka association rule learning algorithms.


== Usage ==
Apriori(x, control = NULL)
Tertius(x, control = NULL)


== Arguments ==
x, an R object with the data to be associated.
control, an object of class Weka_control, or a character vector of control options, or NULL (default).


== Details ==
Apriori implements an Apriori-type algorithm, which iteratively reduces the minimum support until it finds the required number of rules with the given minimum confidence.
Tertius implements a Tertius-type algorithm, requires Weka package tertius.


== Value ==
A list inheriting from class Weka_associators with components including:
associator, a reference (of class jobjRef) to a Java object obtained by applying the Weka build Associations method to the training instances using the given control options.


== Example ==
   x <- read.arff(system.file("arff", "contact-lenses.arff",package = "RWeka"))
   Apriori(x)
   Apriori(x, Weka_control(N = 20))
   Tertius(x)
   Tertius(x, Weka_control(S = TRUE))