hierNet.varimp {hierNet} | R Documentation |
Variable importance for hierNet.
Description
(This is an experimental function.) Calculates a measure of the importance of each variable.
Usage
hierNet.varimp(fit, x, y, ...)
Arguments
fit |
The results of a call to the "hierNet" |
x |
The training set feature matrix used in call produced "fit" |
y |
The training set response vector used in call produced "fit" |
... |
additional arguments (not currently used) |
Value
Table of variable importance.
Author(s)
Jacob Bien and Robert Tibshirani
References
Bien, J., Taylor, J., Tibshirani, R., (2013) "A Lasso for Hierarchical Interactions." Annals of Statistics. 41(3). 1111-1141.
See Also
Examples
set.seed(12)
x=matrix(rnorm(100*10),ncol=10)
x=scale(x,TRUE,TRUE)
y=x[,1]+2*x[,2]+ x[,1]*x[,2]+3*rnorm(100)
newx=matrix(rnorm(100*10),ncol=10)
fit=hierNet(x,y,lam=50)
yhat=predict(fit,newx)
fit=hierNet.path(x,y)
yhat=predict(fit,newx)
[Package hierNet version 1.9 Index]