Does it make sense to run partial least squares (PLS) on a data set that has many more columns (variables) than it has rows (data points)? I am using
plsr in R.
I remember hearing this rule applied to principal component analysis (PCA). I'm not sure why though, and given that PLS is like PCA with Y response, I was wondering if this situation should be avoided here too.
I'd really like an explanation of this, if it is true for PLS or PCA.