Relief-FS: Relief_FS KEEL Preprocess Algorithm

Relief_FSR Documentation

Relief_FS KEEL Preprocess Algorithm

Description

Relief_FS Preprocess Algorithm from KEEL.

Usage

Relief_FS(train, test, paramKNN, relevanceThreshold,
   numInstancesSampled, seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

paramKNN

paramKNN. Default value = 1

relevanceThreshold

relevanceThreshold. Default value = 0.20

numInstancesSampled

numInstancesSampled. Default value = 1000

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::Relief_FS(data_train, data_test)

#Run algorithm
algorithm$run()

#See results
algorithm$preprocessed_test

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

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