CPAR-C: CPAR_C KEEL Associative Classification Algorithm

In RKEEL: Using KEEL in R Code

Description

CPAR_C Associative Classification Algorithm from KEEL.

Usage

CPAR_C(train, test, delta, min_gain, alpha, rules_prediction)

Arguments

train	Train dataset as a data.frame object
test	Test dataset as a data.frame object
delta	delta. Default value = 0.05
min_gain	min_gain. Default value = 0.7
alpha	alpha. Default value = 0.66
rules_prediction	rules_prediction. Default value = 5

Value

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

Examples

#data <- loadKeelDataset("breast")

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

#Run algorithm
#algorithm$run()

#See results
#algorithm$testPredictions

Example output

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