In this paper we address learning rates for the density level detection (DLD) problem. We begin by proving a ``No Free Lunch Theorem'' showing that rates cannot be obtained in general. Then we apply a recently established classification framework to obtain rates for DLD support vector machines under mild assumptions on the density.
C. Scovel, D. Hush, C. Scovel and I. Steinwart, Learning Rates for Density Level Detection. Analysis and Applications, Vol. 3, No. 4 (2005) 356-371. Los Alamos National Laboratory Technical Report LA-UR-05-2088. [ Abstract | Postscript (262 KB) | PDF (287 KB) ]
