DSM-C: DSM_C KEEL Classification Algorithm

DSM_CR Documentation

DSM_C KEEL Classification Algorithm

Description

DSM_C Classification Algorithm from KEEL.

Usage

DSM_C(train, test, iterations, percentage, alpha_0, seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

iterations

iterations. Default value = 100

percentage

percentage. Default value = 10

alpha_0

alpha_0. Default value = 0.1

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::DSM_C(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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