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Research and Application of Machine Learning Algorithm Based on Relevance Vector Machine

YANG Shu-ren,SHEN Hong-yuan(Institute of Information and Electrical Engineering,Hunan University of Science and Technology,Xiangtan 411201,China)  
Relevance Vector Machine(RVM) technique as a new machine learning method is illustrated in details.It is a novel kind of learning method which is based on Bayesian learning theory.RVM was developed on the basis of Support Vector Machine(SVM) learning theory,compared with the SVM,it has the benefits of probabilistic predictions、sparser model、the facility to utilize arbitrary basis functions('Mercer'-function) and so on.Then the research situation、theoretical basis、algorithm thought about RVM is discussed in this paper,and the validity of this method has been proved by some examples,Finally the prospect and the research aspect of RVM is discussed,and the solved key problem of RVM is presented in the future.
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