AssociationRules: Simple way to obtain data mining rules

In MachineLearning: Machine Learning Algorithms for Innovation in Tourism

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

## 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)])

MachineLearning documentation built on March 13, 2020, 2:54 a.m.