Data Mining Algorithms In R/Packages/RWeka/Weka associators
Description
[edit | edit source]R interfaces to Weka association rule learning algorithms.
Usage
[edit | edit source]Apriori(x, control = NULL)
Tertius(x, control = NULL)
Arguments
[edit | edit source]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
[edit | edit source]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
[edit | edit source]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
[edit | edit source] 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))