C45Rules-C: C45Rules_C KEEL Classification Algorithm

In RKEEL: Using 'KEEL' in R Code

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

RKEEL documentation built on Sept. 15, 2023, 1:08 a.m.