C45Binarization_C KEEL Classification Algorithm

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Description

C45Binarization_C Classification Algorithm from KEEL.

Usage

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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

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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

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