Armin Shmilovici Leib

Senior Academic

Kernels for the Relevance Vector Machine - An empirical study

David Ben-Shimon, Armin Shmilovici

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.

Publication language English
Pages 253-263
Publication status Published - 27.09.2006

Keywords

Kernel Regression
Machine learning
Relevance vector machine
matérn kernel

ASJC Scopus subject areas

Artificial Intelligence
Access to Document
10.1007/3-540-33880-2_26
Other files and links
Link to publication in Scopus