PDFC_C KEEL Classification Algorithm

Description

PDFC_C Classification Algorithm from KEEL.

Usage

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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

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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

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