nu.svm.robust.RFE: nu.svm.robust.RFE noise constrained & recursive feature...

In elmerfer/MIXTURE: MIXTURE: a nu-SVR based recursive feature extraction mdoel with noise constraints for molecular signature deconvolution of bulk tumor tissues

nu.svm.robust.RFE noise constrained & recursive feature extraction based support vector nu-regression it will solve the y = X*B problem, providing B>0

Description

nu.svm.robust.RFE noise constrained & recursive feature extraction based support vector nu-regression it will solve the y = X*B problem, providing B>0

Usage

nu.svm.robust.RFE(X, y, nu = c(0.25, 0.5, 0.75), minProp = 0.007, maxiter = 6)

Arguments

X	the signature matrix, a NxL matrix of N genes and L cell lines
y	a vector of bulk gene expression sample
nu	(float) the nu value, default nu = c(0.25,0.5,0.75)
minProp	float. noise threshold level
maxiter	default 6

Author(s)

Elmer A. Fernández

elmerfer/MIXTURE documentation built on Aug. 20, 2024, 8:03 p.m.