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

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.

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 Creators:
Chalimourda, A, Author
Schölkopf, B1, Author           
Smola, AJ, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Dates: 2005-03
 Publication Status: Issued
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Title: Neural Networks
Source Genre: Journal
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Pages: - Volume / Issue: 18 (2) Sequence Number: - Start / End Page: 205 - 205 Identifier: -