CBA-C: CBA_C KEEL Associative Classification Algorithm

Description Usage Arguments Value Examples

Description

CBA_C Associative Classification Algorithm from KEEL.

Usage

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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

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#data <- loadKeelDataset("breast")

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

#Run algorithm
#algorithm$run()

#See results
#algorithm$testPredictions

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

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