linearFsel: linearFsel

In gbonte/gbcode: Code from the handbook "Statistical foundations of machine learning"

linearFsel

Description

Wrapper feature selection based on forward selection and linear regression

Usage

linearFsel(X, Y, nmax = 5, nmax2 = NCOL(X), loo = FALSE, back = FALSE)

Arguments

X:	input dataset
Y:	output dataset
nmax:	number of top returned features
nmax2:	number of forward selection steps
back:	if TRUE, backward reordering based on linear regression
loo:	if TRUE, assessment based on leave-one-out MSE

Details

linearFsel

Wrapper feature selection based on forward selection and linear regression

Value

Indices of nmax top ranked features

Author(s)

Gianluca Bontempi [e-mail]

References

Handbook Statistical foundations of machine learning available in https://tinyurl.com/sfmlh

Examples

N<-100
n<-5
neff<-3
R<-regrDataset(N,n,neff,0.1,seed=0)
X<-R$X
Y<-R$Y
real.features<-R$feat
ranked.features<-linearFsel(X,Y,nmax=3)

gbonte/gbcode documentation built on Feb. 27, 2024, 7:38 a.m.