RKEEL (version 1.3.3)

Bojarczuk_GP_C: Bojarczuk_GP_C KEEL Classification Algorithm

Description

Bojarczuk_GP_C Classification Algorithm from KEEL.

Usage

Bojarczuk_GP_C(train, test, population_size, max_generations,
   max_deriv_size, rec_prob, copy_prob, seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

population_size

population_size. Default value = 200

max_generations

max_generations. Default value = 200

max_deriv_size

max_deriv_size. Default value = 20

rec_prob

rec_prob. Default value = 0.8

copy_prob

copy_prob. 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

# NOT RUN {
#data_train <- RKEEL::loadKeelDataset("iris_train")
#data_test <- RKEEL::loadKeelDataset("iris_test")

#Create algorithm
#algorithm <- RKEEL::Bojarczuk_GP_C(data_train, data_test)
#algorithm <- RKEEL::Bojarczuk_GP_C(data_train, data_test, population_size=5, max_generations=10)

#Run algorithm
#algorithm$run()

#See results
#algorithm$testPredictions
# }