Applicational aspects of support vector machines

The special emphasis of support vector machines (SVMs) on generalization ability makes this approach particularly interesting for real‐world applications with limited amounts of training data. In this paper we analyse the applicational aspects of SVMs, illustrating them with the step‐by‐step constru...

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Bibliographic Details
Published in:Journal of chemometrics 2002-08, Vol.16 (8-10), p.482-489
Main Authors: Belousov, A. I., Verzakov, S. A., von Frese, J.
Format: Article
Language:English
Subjects:
Chemistry
classification
Exact sciences and technology
General and physical chemistry
General. Nomenclature, chemical documentation, computer chemistry
mid-infrared spectroscopy
polymer recognition
support vector machines
Theory of reactions, general kinetics. Catalysis. Nomenclature, chemical documentation, computer chemistry
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Summary:The special emphasis of support vector machines (SVMs) on generalization ability makes this approach particularly interesting for real‐world applications with limited amounts of training data. In this paper we analyse the applicational aspects of SVMs, illustrating them with the step‐by‐step construction of a classifier for polymers by means of their mid‐infrared spectra. With this example we show how the main difficulties of a typical industrial classification task can be addressed using SVMs. Copyright © 2002 John Wiley & Sons, Ltd.
ISSN:0886-9383
1099-128X
DOI:10.1002/cem.744