runSparseLogreg {SparseLogReg} | R Documentation |
This is a simplistic interface to SparseLOGREG
runSparseLogreg(numTrains=62, numGenes=2000, numExperiments=100, gammaMin=0.01, gammaMax=4.0, numGamma=5, intKfold=3, tol=1e-6, maxFeatures=20, inData, inClass, ...)
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 |
out |
result matrix of SparseLOGREG |
M. T. Mader (interface),
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