DT_GA_C {RKEEL} | R Documentation |
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
[Package RKEEL version 1.3.4 Index]