predictSVM {kebabs} | R Documentation

## SVM Access for Training and Prediction

### Description

Functions for SVM access (used only for testing purpose)

### Usage

    predictSVM.KernelMatrix(x, model, predictionType, verbose, ...)

    ## S4 method for signature 'missing'
    predictSVM(x, model, predictionType, verbose, ...)

    ## S4 method for signature 'ExplicitRepresentation'
    predictSVM(x, model, predictionType, verbose,
      ...)

    ## S4 method for signature 'KernelMatrix'
    trainSVM(x, y = NULL, svmInfo, verbose, ...)

    ## S4 method for signature 'ExplicitRepresentation'
    trainSVM(x, y = NULL, svmInfo, verbose,
      ...)

### Arguments

`x` | kernel matrix or explicit representation
`model` | KeBABS model
`predictionType` | type of prediction
`verbose` | controlling verbosity
`...` | additional arguments to be passed to the selected SVM
`y` | label vector
`svmInfo` | SVM related info

### Details

These methods are exported only for test purpose and are not meant to be generally used.

### Value

`trainSVM:` returns the SVM specific model
`predictSVM:` returns the prediction in native format

### Examples

    ## this function is exported only for testing purpose
    ## use function kbsvm instead for examples see help page of kbsvm
    data(TFBS)

[Package kebabs version 1.14.0 Index]