FuzzyFARCHD_C KEEL Classification Algorithm

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Description

FuzzyFARCHD_C Classification Algorithm from KEEL.

Usage

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FuzzyFARCHD_C(train, test, linguistic_values, min_support,
   max_confidence, depth_max, K, max_evaluations, pop_size,
   alpha, bits_per_gen, inference_type, seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

linguistic_values

linguistic_values. Default value = 5

min_support

min_support. Default value = 0.05

max_confidence

max_confidence. Default value = 0.8

depth_max

depth_max. Default value = 3

K

K. Default value = 2

max_evaluations

max_evaluations. Default value = 15000

pop_size

pop_size. Default value = 50

alpha

alpha. Default value = 0.15

bits_per_gen

bits_per_gen. Default value = 30

inference_type

inference_type. Default value = 1

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::FuzzyFARCHD_C(data_train, data_test)

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions

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