C45Rules_C {RKEEL}

C45Rules_C KEEL Classification Algorithm

Description

C45Rules_C Classification Algorithm from KEEL.

Usage

C45Rules_C(train, test, confidence, itemsetsPerLeaf, threshold,
   seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

confidence

confidence. Default value = 0.25

itemsetsPerLeaf

itemsetsPerLeaf. Default value = 2

threshold

threshold. Default value = 10

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::C45Rules_C(data_train, data_test)

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions