Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/73263
Title: Comparison of the support Vector Machine and Relevant Vector Machine in regression and classification problems
Authors: Yu, W.M.
Du, T.
Lim, K.B. 
Issue Date: 2004
Source: Yu, W.M.,Du, T.,Lim, K.B. (2004). Comparison of the support Vector Machine and Relevant Vector Machine in regression and classification problems. 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV) 2 : 1309-1314. ScholarBank@NUS Repository.
Abstract: In this paper, we introduce the Relevant Vector Machine (RVM) from Michael Tipping. The formulation of the RVM in regression and classification is reviewed. Then we analyze why the RVM can reach a sparse solution. In the experiment, we use the real application data to compare the performance of SVM and RVM. The advantages and disadvantage of the SVM and RVM is analyzed based on the experimental results. Some suggestion for the RVM is presented in the discussion section. © 2004 IEEE.
Source Title: 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
URI: http://scholarbank.nus.edu.sg/handle/10635/73263
ISBN: 0780386531
Appears in Collections:Staff Publications

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