CBA-C: CBA_C KEEL Associative Classification Algorithm

In RKEEL: Using 'KEEL' in R Code

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)

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

Value

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

Examples

data <- loadKeelDataset("breast")

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

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions

RKEEL documentation built on Sept. 15, 2023, 1:08 a.m.