C45_Binarization-C: C45Binarization_C KEEL Classification Algorithm

In RKEEL: Using 'KEEL' in R Code

C45Binarization_C KEEL Classification Algorithm

Description

C45Binarization_C Classification Algorithm from KEEL.

Usage

C45Binarization_C(train, test, pruned, confidence, instancesPerLeaf,
   binarization, scoreFunction, bts)

Arguments

train	Train dataset as a data.frame object
test	Test dataset as a data.frame object
pruned	pruned. Default value = TRUE
confidence	confidence. Default value = 0.25
instancesPerLeaf	instancesPerLeaf. Default value = 2
binarization	binarization. Default value = "OVO"
scoreFunction	scoreFunction. Default value = "WEIGHTED"
bts	bts. Default value = 0.05

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::C45Binarization_C(data_train, data_test)
  
#Run algorithm
algorithm$run()
  
#See results
algorithm$testPredictions

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