[1]ZHAO Chunhui,ZHANG Yi.Research progress and analysis on methods for classification of RVM[J].CAAI Transactions on Intelligent Systems,2012,7(4):294-301.
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Research progress and analysis on  methods for classification of RVM

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 7 Number of periods: 2012 4 Page number: 294-301 Column: 综述 Public date: 2012-08-25
Title:
Research progress and analysis on  methods for classification of RVM
Author(s):
ZHAO Chunhui;  ZHANG Yi
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001,China
Keywords:
relevance vector machine; improved relevance vector machine; hyperspectral image; classification algorithm
CLC:
TP751.1
DOI:
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Abstract:
The relevance vector machine (RVM) is a machine learning algorithm which is based on supervision of a Bayesian model. It can be used to deal with regression and classification problems. Compared with the support vector machine (SVM), the relevance vector machine has the advantage that its output is a probability model and the number of relevance vectors is far fewer than the number of support vectors. In this paper, the application was summarized with a relevance vector machine and the classification of a hyperspectral image with RVM was introduced; the RVM model and the method of classification were also explained. In light of the disadvantage of classification, some improved methods were summarized. Various methods were generalized and analyzed while attempting to find breakthroughs and promote further research.
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