| 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:"function" contains
the kernel function used kpar:"list" contains the
hyperparameter usedkcall:"ANY" contains the
function calltype:"character" contains type
of problemkterms:"ANY" containing the
terms representation of the symbolic model used (when using a
formula interface)xmatrix:"matrix" contains the data
matrix used during computationymatrix:"ANY" contains the
response matrixfit:"ANY" 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:"ANY" 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:"ANY" 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 = "rvm"): 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) fit(foo) kernelf(foo) nvar(foo) ## show slots slotNames(foo)