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https://hdl.handle.net/1959.11/4597| Title: | Critical Vector Learning to Construct Sparse Kernel Modeling with PRESS Statistic | Contributor(s): | Gao, Junbin (author); Zhang, Lei (author); Shi, D (author) | Publication Date: | 2004 | DOI: | 10.1109/ICMLC.2004.1378591 | Handle Link: | https://hdl.handle.net/1959.11/4597 | Abstract: | A novel critical vector (CV) regression algorithm is proposed in the paper based on our previous work and PRESS statistics. The proposed regularized CV algorithm finds critical vectors in a successive greedy process in which, compared to the classical OLS algorithm, the orthogonalization has been removed from the algorithm. The performance of the proposed algorithm is comparable to the OLS algorithm while it saves a lot of time complexities in implementing orthogonalization needed in the OLS algorithm. | Publication Type: | Conference Publication | Conference Details: | ICMLC 2004: 2004 International Conference on Machine Learning and Cybernetics, Shanghai, China, 26th - 29th August, 2004 | Source of Publication: | Proceedings of 2004 International Conference On Machine Learning and Cybernetics, v.Volume 5, 26-29 Aug, p. 3223-3228 | Publisher: | Institute of Electrical and Electronics Engineers (IEEE) | Place of Publication: | Los Alamitos, United States of America | Fields of Research (FoR) 2008: | 080110 Simulation and Modelling | Socio-Economic Objective (SEO) 2008: | 890205 Information Processing Services (incl. Data Entry and Capture) | Peer Reviewed: | Yes | HERDC Category Description: | E1 Refereed Scholarly Conference Publication | Publisher/associated links: | http://www.icmlc.com/icmlc_welcome.htm |
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| Appears in Collections: | Conference Publication |
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