2006 | OriginalPaper | Chapter
Kernels for the Relevance Vector Machine - An Empirical Study
Authors: David Ben-Shimon, Armin Shmilovici
Publisher: Springer Berlin Heidelberg
The Relevance Vector Machine (RVM) is a generalized linear model that can use kernel functions as basis functions. Experiments with the Matérn kernel indicate that the kernel choice has a significant impact on the sparsity of the solution. Furthermore, not every kernel is suitable for the RVM. Our experiments indicate that the Matérn kernel of order 3 is a good initial choice for many types of data.