CHC-C: CHC_C KEEL Classification Algorithm

Description Usage Arguments Value Examples

Description

CHC_C Classification Algorithm from KEEL.

Usage

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CHC_C(train, test, pop_size, evaluations, alfa, restart_change,
   prob_restart, prob_diverge, k, distance, seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

pop_size

pop_size. Default value = 50

evaluations

evaluations. Default value = 10000

alfa

alfa. Default value = 0.5

restart_change

restart_change. Default value = 0.35

prob_restart

prob_restart. Default value = 0.25

prob_diverge

prob_diverge. Default value = 0.05

k

k. Default value = 1

distance

distance. Default value = "Euclidean"

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::CHC_C(data_train, data_test)

#Run algorithm
#algorithm$run()

#See results
#algorithm$testPredictions

RKEEL documentation built on March 19, 2020, 5:09 p.m.

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