# How to obtain the minimum set of variables required in a model to produce accurate estimation?

I have a system which I assume is linear. I have a matrix $A$ of which each row is a coefficient of a unknown variables in vector $x$. I have vector $B$ which contains the result of each $Ax$.

Solving this system I can obtain the vector x.

Question: How do I obtain the smallest set of variables in $A$ which result in accurate computation of $b$ ?. i.e., how do I eliminate variables which don't contribute useful information to the solution?

• Hi Kobrien, and welcome to scicomp! Have you ever heard of Principal Component Analysis? en.wikipedia.org/wiki/Principal_component_analysis – Paul Mar 10 '13 at 18:17
• @Paul Hi, I've heard it mentioned, but being a computer scientist, I've no background in this sort of thing. Thanks for the link. – kobrien Mar 10 '13 at 18:35