GFS-LogitBoost-C: GFS_LogitBoost_C KEEL Classification Algorithm

GFS_LogitBoost_CR Documentation

GFS_LogitBoost_C KEEL Classification Algorithm

Description

GFS_LogitBoost_C Classification Algorithm from KEEL.

Usage

GFS_LogitBoost_C(train, test, numLabels, numRules, seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

numLabels

numLabels. Default value = 3

numRules

numRules. Default value = 25

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::GFS_LogitBoost_C(data_train, data_test)

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions


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