kernlab (version 0.9-24)

rvm-class: Class "rvm"

Description

Relevance Vector Machine Class

Objects from the Class

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

Slots

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

Methods

RVindex

signature(object = "rvm"): returns the index of the relevance vectors

alpha

signature(object = "rvm"): returns the resulting alpha vector

cross

signature(object = "rvm"): returns the resulting cross validation error

error

signature(object = "rvm"): returns the training error

fitted

signature(object = "vm"): returns the fitted values

kcall

signature(object = "rvm"): returns the function call

kernelf

signature(object = "rvm"): returns the used kernel function

kpar

signature(object = "rvm"): returns the parameters of the kernel function

lev

signature(object = "rvm"): returns the levels of the response (in classification)

mlike

signature(object = "rvm"): returns the estimated maximum likelihood

nvar

signature(object = "rvm"): returns the calculated variance (in regression)

type

signature(object = "rvm"): returns the type of problem

xmatrix

signature(object = "rvm"): returns the data matrix used during computation

ymatrix

signature(object = "rvm"): returns the used response

See Also

rvm, ksvm-class

Examples

# 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)