M5Rules-R: M5Rules_R KEEL Regression Algorithm

M5Rules_RR Documentation

M5Rules_R KEEL Regression Algorithm

Description

M5Rules_R Regression Algorithm from KEEL.

Usage

M5Rules_R(train, test, pruningFactor, heuristic)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

pruningFactor

pruningFactor. Default value = 2

heuristic

heuristic. Default value = "Coverage"

Value

A data.frame with the actual and predicted values for both train and test datasets.

Examples

data_train <- RKEEL::loadKeelDataset("autoMPG6_train")
data_test <- RKEEL::loadKeelDataset("autoMPG6_test")

#Create algorithm
algorithm <- RKEEL::M5Rules_R(data_train, data_test)

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions

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

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