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Experimentally optimal ν in support vector regression for different noise models and parameter settings

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84193

Schölkopf,  B
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Chalimourda, A., Schölkopf, B., & Smola, A. (2005). Experimentally optimal ν in support vector regression for different noise models and parameter settings. Neural Networks, 18(2), 205-205. doi:10.1016/j.neunet.2004.11.001.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-D5E3-D
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