CMAR-C: CMAR_C KEEL Associative Classification Algorithm

In RKEEL: Using KEEL in R Code

Description

CMAR_C Associative Classification Algorithm from KEEL.

Usage

CMAR_C(train, test, min_confidence, min_support, databaseCoverage)

Arguments

train	Train dataset as a data.frame object
test	Test dataset as a data.frame object
min_confidence	min_confidence. Default value = 0.5
min_support	min_support. Default value = 0.01
databaseCoverage	databaseCoverage. Default value = 4

Value

A data.frame with the actual and predicted classes for both train and test datasets.

Examples

#data <- loadKeelDataset("breast")

#Create algorithm
#algorithm <- RKEEL::CMAR_C(data, data)

#Run algorithm
#algorithm$run()

#See results
#algorithm$testPredictions

Example output

RKEEL documentation built on March 19, 2020, 5:09 p.m.