C_SVM_C KEEL Classification Algorithm

Description

C_SVM_C Classification Algorithm from KEEL.

Usage

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C_SVM_C(train, test, KernelType, C, eps, degree, gamma, coef0,
   nu, p, shrinking, seed)

Arguments

train

Train dataset as a data.frame object

test

Test dataset as a data.frame object

KernelType

KernelType. Default value = "RBF"

C

C. Default value = 100.0

eps

eps. Default value = 0.001

degree

degree. Default value = 1

gamma

gamma. Default value = 0.01

coef0

coef0. Default value = 0.0

nu

nu. Default value = 0.1

p

p. Default value = 1.0

shrinking

shrinking. Default value = 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

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data_train <- RKEEL::loadKeelDataset("iris_train")
data_test <- RKEEL::loadKeelDataset("iris_test")

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

#Run algorithm
algorithm$run()

#See results
algorithm$testPredictions

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