Hi, I am doing a research on dimension reduction and one of the steps involved requires me to project the L-dimensional data orthogonally onto a d-space spanned by the d original coordinates with the largest variances.
The L-dimensional data is actually a matrix with L cols. d-space is a matrix which is smaller then the L-space. Which means that if L = 15, d can be any value lesser than 15.
What I would like to know is how do I execute the statement underlined above. Is there any maths formula I can go about projecting a matrix orthogonally onto another matrix of a different dimension?
Thanks.
Hi,
I'd suggest that you refer to books relevant to your area of research or search for conference/journal articles on the Internet of work done in this area. Thanks!
Cheers,
Wen Shih
Hi, the problem is that there are no books relevant to the research topics. Conference papers are really brief and does not explain much about the mathematical part of it. I am just trying my luck to see if anyone has done anything similar to this and might be able to provide me with some clue.
Thanks.
What subject is this? Discrete mathematics?