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