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Theoretically Optimal Parameter Choices for Support Vector Regression Machines with Noisy Input

✍ Scribed by Wang Shitong; Zhu Jiagang; F. L. Chung; Lin Qing; Hu Dewen

Publisher: Springer
Year: 2004
Tongue: English
Weight: 429 KB
Volume: 9
Category: Article
ISSN: 1432-7643
DOI: 10.1007/s00500-004-406-3

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## Abstract Partial least squares (PLS) is one of the most used tools in chemometrics. Other data analysis techniques such as artificial neural networks and least squares support vector machines (LS‐SVMs) have however made their entry in the field of chemometrics. These techniques can also model no