CW-C: CW_C KEEL Classification Algorithm

CW_CR Documentation

CW_C KEEL Classification Algorithm

Description

CW_C Classification Algorithm from KEEL.

Usage

CW_C(train, test, beta, mu, epsilon)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

beta

beta. Default value = 8.0

mu

mu. Default value = 0.001

epsilon

epsilon. Default value = 0.001

Value

A data.frame with the actual and predicted classes for both train and test datasets.

Examples

data_train <- RKEEL::loadKeelDataset("iris_train")
data_test <- RKEEL::loadKeelDataset("iris_test")

#Create algorithm
algorithm <- RKEEL::CW_C(data_train, data_test)

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions

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

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