SVMr: Classification using Support Vector Machine with a radial...

In fdm2id: Data Mining and R Programming for Beginners

Classification using Support Vector Machine with a radial kernel

Description

This function builds a classification model using Support Vector Machine with a radial kernel.

Usage

SVMr(
  train,
  labels,
  gamma = 2^(-3:3),
  cost = 2^(-3:3),
  methodparameters = NULL,
  tune = FALSE,
  ...
)

Arguments

train	The training set (description), as a data.frame.
labels	Class labels of the training set (vector or factor).
gamma	The gamma parameter (if a vector, cross-over validation is used to chose the best size).
cost	The cost parameter (if a vector, cross-over validation is used to chose the best size).
methodparameters	Object containing the parameters. If given, it replaces gamma and cost.
tune	If true, the function returns paramters instead of a classification model.
...	Other arguments.

Value

The classification model.

See Also

svm, SVM

Examples

## Not run: 
require (datasets)
data (iris)
SVMr (iris [, -5], iris [, 5], gamma = 1, cost = 1)

## End(Not run)

fdm2id documentation built on July 9, 2023, 6:05 p.m.