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