fdm2id (version 0.9.5)

SVMr: 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)
# }