Class "rvm"
Relevance Vector Machine Class
Objects can be created by calls of the form new("rvm", ...).
or by calling the rvm function.
tol:Object of class "numeric" contains
tolerance of termination criteria used.
kernelf:Object of class "kfunction" contains
the kernel function used
kpar:Object of class "list" contains the
hyperparameter used
kcall:Object of class "call" contains the
function call
type:Object of class "character" contains type
of problem
terms:Object of class "ANY" containing the
terms representation of the symbolic model used (when using a
formula interface)
xmatrix:Object of class "matrix" contains the data
matrix used during computation
ymatrix:Object of class "output" contains the
response matrix
fitted:Object of class "output" with the fitted
values, (predict on training set).
lev:Object of class "vector" contains the
levels of the response (in classification)
nclass:Object of class "numeric" contains the
number of classes (in classification)
alpha:Object of class "listI" containing the the
resulting alpha vector
coef:Object of class "ANY" containing the the
resulting model parameters
nvar:Object of class "numeric" containing the
calculated variance (in case of regression)
mlike:Object of class "numeric" containing the
computed maximum likelihood
RVindex:Object of class "vector" containing
the indexes of the resulting relevance vectors
nRV:Object of class "numeric" containing the
number of relevance vectors
cross:Object of class "numeric" containing the
resulting cross validation error
error:Object of class "numeric" containing the
training error
n.action:Object of class "ANY" containing the
action performed on NA
signature(object = "rvm"): returns the index
of the relevance vectors
signature(object = "rvm"): returns the resulting
alpha vector
signature(object = "rvm"): returns the resulting
cross validation error
signature(object = "rvm"): returns the training
error
signature(object = "vm"): returns the fitted values
signature(object = "rvm"): returns the function call
signature(object = "rvm"): returns the used
kernel function
signature(object = "rvm"): returns the parameters
of the kernel function
signature(object = "rvm"): returns the levels of
the response (in classification)
signature(object = "rvm"): returns the estimated
maximum likelihood
signature(object = "rvm"): returns the calculated
variance (in regression)
signature(object = "rvm"): returns the type of problem
signature(object = "rvm"): returns the data
matrix used during computation
signature(object = "rvm"): returns the used response
Alexandros Karatzoglou
alexandros.karatzoglou@ci.tuwien.ac.at
# create data x <- seq(-20,20,0.1) y <- sin(x)/x + rnorm(401,sd=0.05) # train relevance vector machine foo <- rvm(x, y) foo alpha(foo) RVindex(foo) fitted(foo) kernelf(foo) nvar(foo) ## show slots slotNames(foo)
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