rvm-class {kernlab} | R Documentation

## 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

### Author(s)

Alexandros Karatzoglou
alexandros.karatzoglou@ci.tuwien.ac.at

### 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)

[Package kernlab version 0.9-27 Index]