Relevance vector machine
US6633857B1 · kind B1 · utility
Assignee
Inventor
Key dates
| Filing date | Sep 4, 1999 |
| Grant date | Oct 14, 2003 |
| Priority date | — |
| Expiry date | Sep 4, 2019 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/0985
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A relevance vector machine (RVM) for data modeling is disclosed. The RVM is a probabilistic basis model. Sparsity is achieved through a Bayesian treatment, where a prior is introduced over the weights governed by a set of hyperparameters. As compared to a Support Vector Machine (SVM), the non-zero weights in the RVM represent more prototypical examples of classes, which are termed relevance vectors. The trained RVM utilizes many fewer basis functions than the corresponding SVM, and typically superior test performance. No additional validation of parameters (such as C) is necessary to specify the model, except those associated with the basis.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.