IterativePartitioningFilter_F {RKEEL}

IterativePartitioningFilter_F KEEL Preprocess Algorithm

Description

IterativePartitioningFilter_F Preprocess Algorithm from KEEL.

Usage

IterativePartitioningFilter_F(train, test, numPartitions,
   filterType, confidence, itemsetsPerLeaf, seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

numPartitions

numPartitions. Default value = 5

filterType

filterType. Default value = "consensus"

confidence

confidence. Default value = 0.25

itemsetsPerLeaf

itemsetsPerLeaf. Default value = 2

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 preprocessed data for both train and test datasets.

Examples

data_train <- RKEEL::loadKeelDataset("car_train")
data_test <- RKEEL::loadKeelDataset("car_test")

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

#Run algorithm
algorithm$run()

#See results
algorithm$preprocessed_test