1. Introduction¶
The Relevance Vector Machines (RVMs) are a set of supervised learning methods for regression and classification problems that only require a sparse kernel representation.
Advantages of the RVM are:
Disadvantages of the RVM are:
The Relevance Vector Machines (RVMs) are a set of supervised learning methods for regression and classification problems that only require a sparse kernel representation.
Advantages of the RVM are:
Disadvantages of the RVM are: