RF.wrap {MCRestimate}R Documentation

Wrapper function for different classification methods

Description

Wrapper function for different classification methods used by MCRestimator. These functions are mainly used within the function MCRestimate

Usage

RF.wrap(x,y,...)
PAM.wrap(x,y,threshold,...)
PLR.wrap(x,y,kappa=0,eps=1e-4,...)
SVM.wrap(x,y,gamma = NULL, kernel = "radial", ...)
GPLS.wrap(x,y,...)

Arguments

x,y x is a matrix where each row refers to a sample a each colum refers to a gene; y is a factor which includes the class for each sample
threshold the threshold for PAM
kappa the penalty parameter for the penalised logistic regression
eps
gamma parameter for support vector machines
kernel parameter for support vector machines
... Further parameters

Value

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

Author(s)

Markus Ruschhaupt mailto:m.ruschhaupt@dkfz.de

See Also

MCRestimate

Examples






[Package MCRestimate version 1.4.0 Index]