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Chang CC, Lin CJ (2001) LIBSVM: A library for Support Vector Machines Available online at: http:--www.csie.ntu.edu.tw-cjlin-libsvm

References and models cited by this paper

References and models that cite this paper

Chang MW, Lin CJ (2005) Leave-One-Out Bounds for Support Vector Regression Model Selection Neural Comput 17:1188-1222

Gunter L, Zhu J (2007) Efficient computation and model selection for the support vector regression. Neural Comput 19:1633-55 [Journal] [PubMed]

Kao WC, Chung KM, Sun CL, Lin CJ (2004) Decomposition Methods for Linear Support Vector Machines Neural Comput 16:1689-1704

Knebel T, Hochreiter S, Obermayer K (2008) An SMO algorithm for the potential support vector machine. Neural Comput 20:271-87 [Journal] [PubMed]

Zhong M, Coggeshall D, Ghaneie E, Pope T, Rivera M, Georgiopoulos M, Anagnostopoulos GC, Mollaghasemi M, Richie S (2007) Gap-based estimation: choosing the smoothing parameters for probabilistic and general regression neural networks. Neural Comput 19:2840-64 [Journal] [PubMed]

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