Classification performance comparison between RVM and SVM

2007 IEEE International Workshop on Anti-counterfeiting, Security, Identification, ASID

Volumn , Issue , 2007, Pages 208-211

  Xu, Xiang Min ^a   Mao, Yun Feng ^a   Xiong, Jia Ni ^a   Zhou, Feng Le ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Bayesian learning; Machine learning; RVM; SVM

Indexed keywords

BAYESIAN NETWORKS; PATTERN RECOGNITION;

SPARSE PROPERTY; TRAINING EFFICIENCY;

SUPPORT VECTOR MACHINES;

EID: 34548846919     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IWASID.2007.373728     Document Type: Conference Paper

References (4)

1. QI Heng-nian,Support Vector Machines and Application Research Overview,Computer Engineerings,Vol.30,May 2004,pp.8-9
2. V.Vapnik, Statistical Learning Theory New York: Wiley, 1998
3. M.E.Tipping, Sparse Bayesian learning and the relevance vector machine, J. Mach. Learn. Res., no.1,2001, pp.211-244.
4. Xiao Jian-hua,Intelligent Pattern Recognition methods, SCUT press,2005,pp. 148-152