lssvm-class function

Class "lssvm"

The Gaussian Processes object class

Objects from the Class

Objects can be created by calls of the form new("lssvm", ...). or by calling the lssvm function

Slots

• 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
• alphaindex: Object 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

Methods

• alpha: signature(object = "lssvm"): returns the alpha vector
• cross: signature(object = "lssvm"): returns the cross validation error
• error: signature(object = "lssvm"): returns the training error
• fitted: signature(object = "vm"): returns the fitted values
• kcall: signature(object = "lssvm"): returns the call performed
• kernelf: signature(object = "lssvm"): returns the kernel function used
• kpar: signature(object = "lssvm"): returns the kernel parameter used
• param: signature(object = "lssvm"): returns the regularization parameter used
• lev: signature(object = "lssvm"): returns the response levels (in classification)
• type: signature(object = "lssvm"): returns the type of problem
• scaling: signature(object = "ksvm"): returns the scaling values
• xmatrix: signature(object = "lssvm"): returns the data matrix used
• ymatrix: signature(object = "lssvm"): returns the response matrix used

Author(s)

Alexandros Karatzoglou

alexandros.karatzoglou@ci.tuwien.ac.at

See Also

lssvm, ksvm-class

Examples

# train model
data(iris)
test <- lssvm(Species~.,data=iris,var=2)
test
alpha(test)
error(test)
lev(test)