RKEEL (version 1.3.4)

SSGA_Integer_knn_FS: SSGA_Integer_knn_FS KEEL Preprocess Algorithm

Description

SSGA_Integer_knn_FS Preprocess Algorithm from KEEL.

Usage

SSGA_Integer_knn_FS(train, test, paramKNN, nEval, pop_size,
   numFeatures, seed)

Value

A data.frame with the preprocessed data for both train and test datasets.

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

paramKNN

paramKNN. Default value = 1

nEval

nEval. Default value = 5000

pop_size

pop_size. Default value = 100

numFeatures

numFeatures. Default value = 3

seed

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

Examples

data_train <- RKEEL::loadKeelDataset("car_train")
data_test <- RKEEL::loadKeelDataset("car_test")

#Create algorithm
algorithm <- RKEEL::SSGA_Integer_knn_FS(data_train, data_test)
algorithm <- RKEEL::SSGA_Integer_knn_FS(data_train, data_test, nEval = 10, pop_size = 10)

#Run algorithm
algorithm$run()

#See results
algorithm$preprocessed_test