pathClass (version 0.9.4)

fit.rfe: Recursive Feature Elimination (RFE)

Description

Implementation of the Recursive Feature Elimination (RFE) algorithm.

Usage

fit.rfe(x, y, DEBUG = FALSE, scale = c("center", "scale"), Cs = 10^c(-3:3), stepsize = 0.1)

Arguments

x

a p x n matrix of expression measurements with p samples and n genes.

y

a factor of length p comprising the class labels.

DEBUG

should debugging information be plotted.

scale

a character vector defining if the data should be centered and/or scaled. Possible values are center and/or scale. Defaults to c('center', 'scale').

Cs

soft-margin tuning parameter of the SVM. Defaults to 10^c(-3:3).

stepsize

amount of features that are discarded in each step of the feature elimination. Defaults to 10%.

Value

a RFE fit object. features = selected features error.bound = span bound of the model fit = fitted SVM model

Examples

## Not run: 
# library(Biobase)
# data(sample.ExpressionSet)
# x <- t(exprs(sample.ExpressionSet))
# y <- factor(pData(sample.ExpressionSet)$sex)
# res.rfe <- crossval(x,y,DEBUG=TRUE,theta.fit=fit.rfe,folds=2,repeats=1,parallel=TRUE,Cs=10^(-3:3))
# ## End(Not run)