MachineLearning (version 0.1.4)

AssociationRules: Simple way to obtain data mining rules

Description

This is a rule-based machine learning method to discover interesting relationships between a consequent and an antecedent (or group of antecedents) in large databases.

Usage

AssociationRules(data, support = 0.2, confidence = 0.1, minlength = 2)

Arguments

data

a data frame with discrete variables.

support

a numeric value for the minimun support of the antecedents (default: 0.2).

confidence

a numeric value for the minimun confidence of confidence in rule/association method (default: 0.8)

minlength

an integer value for the minimal number of items per item set (default: 2 item)

Value

A MLA object of subclass Association

Examples

# NOT RUN {
## Load a Dataset
data(EGATUR)
## Generate an asociation rules with apriori, remmember only support discretized variables,
##  in this remove numerical variables.
Rules <- AssociationRules(EGATUR[,c(2,4,5,8)])

# }