An S4 VIRTUAL class used as a base for the various vector machine classes in kernlab
Objects from the class cannot be created directly but only contained in other classes.
alpha:Object of class "listI" containing the
      resulting alpha vector (list in case of multiclass classification) (support vectors)
type:Object of class "character"  containing
      the vector machine type e.g.,
      ("C-svc", "nu-svc", "C-bsvc", "spoc-svc",
      "one-svc", "eps-svr", "nu-svr", "eps-bsvr")
kernelf:Object of class "function" containing
      the kernel function
kpar:Object of class "list" containing the
      kernel function parameters (hyperparameters)
kcall:Object of class "call" containing the function call
terms:Object of class "ANY" containing the
      terms representation of the symbolic model used (when using a formula)
xmatrix:Object of class "input" the data
      matrix used during computations (support vectors) (possibly scaled and without NA)
ymatrix:Object of class "output" the response matrix/vector
fitted:Object of class "output" with the fitted values,
      predictions using the training set.
lev:Object of class "vector" with the levels of the
      response (in the case of classification)
nclass:Object of class "numeric"  containing
      the number of classes (in the case of classification)
error:Object of class "vector" containing the
    training error
cross:Object of class "vector" containing the
      cross-validation error
n.action:Object of class "ANY" containing the
      action performed for NA
signature(object = "vm"): returns the complete
    alpha vector (wit zero values)
signature(object = "vm"): returns the
      cross-validation error
signature(object = "vm"): returns the training
      error
signature(object = "vm"): returns the fitted
      values (predict on training set)
signature(object = "vm"): returns the kernel
    function
signature(object = "vm"): returns the kernel
      parameters (hyperparameters)
signature(object = "vm"): returns the levels in
      case of classification
signature(object="vm"): returns the function call
signature(object = "vm"): returns the problem type
signature(object = "vm"): returns the data
      matrix used(support vectors)
signature(object = "vm"): returns the
      response vector