CFAR-C: CFAR_C KEEL Classification Algorithm

Description Usage Arguments Value Examples

Description

CFAR_C Classification Algorithm from KEEL.

Usage

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CFAR_C(train, test, min_support, min_confidence, threshold,
   num_labels, seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

min_support

min_support. Default value = 0.1

min_confidence

min_confidence. Default value = 0.85

threshold

threshold. Default value = 0.15

num_labels

num_labels. Default value = 5

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::CFAR_C(data_train, data_test)

#Run algorithm
#algorithm$run()

#See results
#algorithm$testPredictions

Example output



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

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