Partial least squares regression

How to extract variable importance in projection from partial least squares regression model?
As predictors, visible near-infrared spectroscopic data was used.

1 Like

Hi, Elton. Could you help us out with a reproducible example, called a reprex?

PLSR is a sort of unholy alliance between principal component analysis and linear regression. Instead of minimizing the variance on the cartesian plane, some varieties minimize it on the orthagonal plane.

You generally see it used with high-dimensional data, with more predictors than observations.

The principal R package seems to be pls and I think I'll be able to help you with cross validation and diagnostics. But to do that, of course, require some representative data and a fitted model.

1 Like

Hi, thanks for your reply and help aid. It seems to me I found the solution using "plsVarSel" package that insures filter method to extract VIP values, it is really easy in use.


1 Like

Thanks for letting everyone know!

This topic was automatically closed 21 days after the last reply. New replies are no longer allowed.