rvm-class {kernlab} | R Documentation |
Relevance Vector Machine Class
Objects can be created by calls of the form new("rvm", ...)
.
or by calling the rvm
function.
tol
:"numeric"
contains
tolerance of termination critiria used.kernelf
:"kfunction"
contains
the kernel function used kpar
:"list"
contains the
hyperparameter usedkcall
:"call"
contains the
function calltype
:"character"
contains type
of problemterms
:"ANY"
containing the
terms representation of the symbolic model used (when using a
formula interface)xmatrix
:"matrix"
contains the data
matrix used during computationymatrix
:"output"
contains the
response matrixfitted
:"output"
with the fitted
values, (predict on trianing set).lev
:"vector"
contains the
levels of the response (in classification)nclass
:"numeric"
contains the
number of classes (in classification)alpha
:"listI"
containing the the
resulting alpha vectornvar
:"numeric"
containing the
calculated variance (in case of regression)mlike
:"numeric"
containing the
computed maximum likelihoodRVindex
:"vector"
containing
the indexes of the resulting relevance vectors nRV
:"numeric"
containing the
number of relevance vectorscross
:"numeric"
containing the
relusting cross validation error error
:"numeric"
containing the
training errorn.action
:"ANY"
containing the
action performed on NA
signature(object = "rvm")
: returns the index
of the relevance vectors signature(object = "rvm")
: returns the resulting
alpha vectorsignature(object = "rvm")
: returns the resulting
cross validation errorsignature(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 functionsignature(object = "rvm")
: returns the levels of
the response (in classification)signature(object = "rvm")
: returns the estimated
maiximum likelihoodsignature(object = "rvm")
: returns the calculated
variance (in regression)signature(object = "rvm")
: returns the type of problemsignature(object = "rvm")
: returns the data
mmatrix used during computationsignature(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)