PDFC-C: PDFC_C KEEL Classification Algorithm

In RKEEL: Using 'KEEL' in R Code

PDFC_C KEEL Classification Algorithm

Description

PDFC_C Classification Algorithm from KEEL.

Usage

PDFC_C(train, test, C, d, tolerance, epsilon, PDRFtype,
   nominal_to_binary, preprocess_type, seed)

Arguments

train	Train dataset as a data.frame object
test	Test dataset as a data.frame object
C	C. Default value = 100.0
d	d. Default value = 0.25
tolerance	tolerance. Default value = 0.001
epsilon	epsilon. Default value = 1.0E-12
PDRFtype	PDRFtype. Default value = "Gaussian
nominal_to_binary	nominal_to_binary. Default value = TRUE
preprocess_type	preprocess_type. Default value = "Normalize"
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 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::PDFC_C(data_train, data_test)

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions

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