SVMAccess: SVM Access for Training and Prediction

In kebabs: Kernel-Based Analysis Of Biological Sequences

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)

kebabs documentation built on Nov. 8, 2020, 7:38 p.m.