gausspr-class function

Class "gausspr"

The Gaussian Processes object class class

Objects from the Class

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

Slots

• tol:: Object of class "numeric" contains tolerance of termination criteria
• kernelf:: Object of class "kfunction" contains the kernel function used
• kpar:: Object of class "list" contains the kernel parameter used
• kcall:: Object of class "list" contains the used function call
• type:: Object of class "character" contains type of problem
• terms:: Object of class "ANY" contains the terms representation of the symbolic model used (when using a formula)
• xmatrix:: Object of class "input" containing the data matrix used
• ymatrix:: Object of class "output" containing the response matrix
• fitted:: Object of class "output" containing the fitted values
• lev:: Object of class "vector" containing the levels of the response (in case of classification)
• 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).
• sol: Object of class "matrix" containing the solution to the Gaussian Process formulation, it is used to compute the variance in regression problems.
• scaling: Object of class "ANY" containing the scaling coefficients of the data (when case scaled = TRUE is used).
• nvar:: Object of class "numeric" containing the computed variance
• 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

Methods

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

Author(s)

Alexandros Karatzoglou

alexandros.karatzoglou@ci.tuwien.ac.at

See Also

gausspr, ksvm-class, vm-class

Examples

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