Classification using Support Vector Machine
This function builds a classification model using Support Vector Machine.
SVM(
train,
labels,
gamma = 2^(-3:3),
cost = 2^(-3:3),
kernel = c("radial", "linear"),
methodparameters = NULL,
tune = FALSE,
...
)train |
The training set (description), as a |
labels |
Class labels of the training set ( |
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). |
kernel |
The kernel type. |
methodparameters |
Object containing the parameters. If given, it replaces |
tune |
If true, the function returns paramters instead of a classification model. |
... |
Other arguments. |
The classification model.
## Not run: require (datasets) data (iris) SVM (iris [, -5], iris [, 5], kernel = "linear", cost = 1) SVM (iris [, -5], iris [, 5], kernel = "radial", gamma = 1, cost = 1) ## End(Not run)
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