DT_GA-C: DT_GA_C KEEL Classification Algorithm

In RKEEL: Using 'KEEL' in R Code

DT_GA_C KEEL Classification Algorithm

Description

DT_GA_C Classification Algorithm from KEEL.

Usage

DT_GA_C(train, test, confidence, instancesPerLeaf,
   geneticAlgorithmApproach, threshold, numGenerations,
   popSize, crossoverProb, mutProb, seed)

Arguments

train	Train dataset as a data.frame object
test	Test dataset as a data.frame object
confidence	confidence. Default value = 0.25
instancesPerLeaf	instancesPerLeaf. Default value = 2
geneticAlgorithmApproach	geneticAlgorithmApproach. Default value = "GA-LARGE-SN"
threshold	threshold. Default value = 10
numGenerations	numGenerations. Default value = 50
popSize	popSize. Default value = 200
crossoverProb	crossoverProb. Default value = 0.8
mutProb	mutProb. Default value = 0.01
seed	Seed for random numbers. If it is not assigned a value, the seed will be a random number

Value

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

Examples

data_train <- RKEEL::loadKeelDataset("iris_train")
data_test <- RKEEL::loadKeelDataset("iris_test")

#Create algorithm
algorithm <- RKEEL::DT_GA_C(data_train, data_test)

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions

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