Relevance Vector Machine

From Wikipedia, the free encyclopedia

Relevance Vector Machine (RVMs) is a machine learning technique that uses Bayesian theory to obtain sparse solutions for regression and classification. The RVM has an identical functional form to the Support Vector Machine, but provides probabilistic classification.

[edit] External links

• The Relevance Vector Machine Tipping's article on the relevance vector machine.