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
rvm
,
ksvm-class
# 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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