RKEEL (version 1.3.4)

GFS_RB_MF_R: GFS_RB_MF_R KEEL Regression Algorithm

Description

GFS_RB_MF_R Regression Algorithm from KEEL.

Usage

GFS_RB_MF_R(train, test, numLabels, popSize, generations,
   crossProb, mutProb, seed)

Value

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

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

numLabels

numLabels. Default value = 3

popSize

popSize. Default value = 50

generations

generations. Default value = 100

crossProb

crossProb. Default value = 0.9

mutProb

mutProb. Default value = 0.1

seed

Seed for random numbers. If it is not assigned a value, the seed will be a random number

Examples

data_train <- RKEEL::loadKeelDataset("autoMPG6_train")
data_test <- RKEEL::loadKeelDataset("autoMPG6_test")

#Create algorithm
algorithm <- RKEEL::GFS_RB_MF_R(data_train, data_test)
algorithm <- RKEEL::GFS_RB_MF_R(data_train, data_test, popSize = 5, generations = 10)

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions