SVM.OVA.wrap {MCRestimate}R Documentation

SVM with 'One-Versus-All' multiclass approach

Description

Multiclass approach where k binary SVM classifiers are constructed for a classification problem with k classes: Every classifier is trained to distinguish samples of one class from samples of all other classes. For prediction of the class of a new sample, the sample is classified by all k classifiers, and the class corresponding to the classifier with the maximum decision value is chosen.

Usage

SVM.OVA.wrap(x,y,gamma = NULL, kernel = "radial", ...)

Arguments

x,y x is a matrix where each row refers to a sample and each colum refers to a gene; y is a factor which includes the class for each sample
gamma parameter for support vector machines
kernel parameter for support vector machines
... Further parameters

Value

A predict function which can be used to predict the classes for a new data set.

Author(s)

Patrick Warnat mailto:p.warnat@dkfz-heidelberg.de

See Also

MCRestimate

Examples






[Package MCRestimate version 1.4.0 Index]