runSparseLogreg {SparseLogReg}R Documentation

R interface for SparseLOGREG

Description

This is a simplistic interface to SparseLOGREG

Usage

runSparseLogreg(numTrains=62, numGenes=2000, numExperiments=100,
                gammaMin=0.01, gammaMax=4.0, numGamma=5,
                intKfold=3, tol=1e-6, maxFeatures=20, 
                inData, inClass, ...)

Arguments

numTrains Number of training cases
numGenes Number of variables/genes
numExperiments Number of measurements/experiments
gammaMin
gammaMax
numGamma number of Gamma
intKfold number of internal k-folds
tol tolerance
maxFeatures
inData Input data matrix
inClass Classification vector (consisting of c(0,1)
... additional arguments are piped through to subfunctions

Value

out result matrix of SparseLOGREG

Author(s)

M. T. Mader (interface),

References

Shevade, S. K. and Keerthi, S. S. (2003): A simple and efficient algorithm for gene selection using sparse logistic regression.- Bioinformatics 19(17): 2246-2253


[Package SparseLogReg version 0.1 Index]