I am working in an extremely memory constrained environment, and the number of support vectors my Matlab design is generating is just not something that scales. That led me to move to finding a way to lower the number of support vectors. And I came across this paper from MIT: http://dspace.mit.edu/handle/1721.1/54725
The paper is available for free download.
Now on Page 4203 (look at the bottom, journal page indexing prolly), the last paragraph states: The application of Reduced Set Methods , a model order reduction technique, allowsthe nonlinear descriminant function tobe expressed using N M << support-vectors.
Now the 8th Reference for this paper is only a link to a toolbox, here: Statistical PatternRecognition Toolbox ForMatlab (STPRTool): http://cmp.felk.cvut.cz/cmp/software/stprtool/index.html
My question is: does anyone have any idea how to reduce support vectors? Some simple algorithm and its implementation? I will be grateful for a response.