Description Objects from the Class Slots Methods Author(s) See Also Examples
The Gaussian Processes object
Objects can be created by calls of the form new("lssvm", ...).
or by calling the lssvm function
kernelf:Object of class "kfunction" contains
the kernel function used
kpar:Object of class "list" contains the
kernel parameter used
param:Object of class "list" contains the
regularization parameter used.
kcall:Object of class "call" contains the used
function call
type:Object of class "character" contains
type of problem
coef:Object of class "ANY" contains
the model parameter
terms:Object of class "ANY" contains the
terms representation of the symbolic model used (when using a formula)
xmatrix:Object of class "matrix" containing
the data matrix used
ymatrix:Object of class "output" containing the
response matrix
fitted:Object of class "output" containing the
fitted values
b:Object of class "numeric" containing the
offset
lev:Object of class "vector" containing the
levels of the response (in case of classification)
scaling:Object of class "ANY" containing the
scaling information performed on the data
nclass:Object of class "numeric" containing
the number of classes (in case of classification)
alpha:Object of class "listI" containing the
computes alpha values
alphaindexObject of class "list" containing
the indexes for the alphas in various classes (in multi-class problems).
error:Object of class "numeric" containing the
training error
cross:Object of class "numeric" containing the
cross validation error
n.action:Object of class "ANY" containing the
action performed in NA
nSV:Object of class "numeric" containing the
number of model parameters
signature(object = "lssvm"): returns the alpha
vector
signature(object = "lssvm"): returns the cross
validation error
signature(object = "lssvm"): returns the
training error
signature(object = "vm"): returns the fitted values
signature(object = "lssvm"): returns the call performed
signature(object = "lssvm"): returns the
kernel function used
signature(object = "lssvm"): returns the kernel
parameter used
signature(object = "lssvm"): returns the regularization
parameter used
signature(object = "lssvm"): returns the
response levels (in classification)
signature(object = "lssvm"): returns the type
of problem
signature(object = "ksvm"): returns the
scaling values
signature(object = "lssvm"): returns the
data matrix used
signature(object = "lssvm"): returns the
response matrix used
Alexandros Karatzoglou
alexandros.karatzoglou@ci.tuwien.ac.at
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