DT_GA-C: DT_GA_C KEEL Classification Algorithm

Description Usage Arguments Value Examples

Description

DT_GA_C Classification Algorithm from KEEL.

Usage

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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

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#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 March 19, 2020, 5:09 p.m.

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