SSGA-Integer-knn-FS: SSGA_Integer_knn_FS KEEL Preprocess Algorithm

In RKEEL: Using 'KEEL' in R Code

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)

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

Value

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

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

RKEEL documentation built on Sept. 15, 2023, 1:08 a.m.