RKEEL (version 1.3.4)

CBA_C: CBA_C KEEL Associative Classification Algorithm

Description

CBA_C Associative Classification Algorithm from KEEL.

Usage

CBA_C(train, test, min_support, min_confidence, pruning, maxCandidates)

Value

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

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

min_support

min_support. Default value = 0.01

min_confidence

min_confidence. Default value = 0.5

pruning

indicates wether pruning or not. Default value = TRUE

maxCandidates

maxCandidates; if 0, no limit. Default value = 80000

Examples

data <- loadKeelDataset("breast")

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

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions