Weka_filters: R/Weka Filters

In RWeka: R/Weka Interface

R/Weka Filters

Description

R interfaces to Weka filters.

Usage

Normalize(formula, data, subset, na.action, control = NULL)
Discretize(formula, data, subset, na.action, control = NULL)

Arguments

formula	a symbolic description of a model. Note that for unsupervised filters the response can be omitted.
data	an optional data frame containing the variables in the model.
subset	an optional vector specifying a subset of observations to be used in the fitting process.
na.action	a function which indicates what should happen when the data contain NAs. See model.frame for details.
control	an object of class Weka_control, or a character vector of control options, or NULL (default). Available options can be obtained on-line using the Weka Option Wizard WOW, or the Weka documentation.

Details

Normalize implements an unsupervised filter that normalizes all instances of a dataset to have a given norm. Only numeric values are considered, and the class attribute is ignored.

Discretize implements a supervised instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes. Discretization is by the MDL method of \bibcitetFayyad+Irani:1993.

Note that these methods ignore nominal attributes, i.e., variables of class factor.

Value

A data frame.

References

\bibshow

Fayyad+Irani:1993, Witten+Frank:2005

Examples

## Using a Weka data set ...
w <- read.arff(system.file("arff","weather.arff",
	       package = "RWeka"))

## Normalize (response irrelevant)
m1 <- Normalize(~., data = w)
m1

## Discretize
m2 <- Discretize(play ~., data = w)
m2

RWeka documentation built on July 13, 2026, 5:08 p.m.