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  Support vector machines

Hearst, M., Dumais, S., Osman, E., Platt, J., & Schölkopf, B. (1998). Support vector machines. IEEE Intelligent Systems and their Applications, 13(4), 18-28. doi:10.1109/5254.708428.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-E849-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-C795-2
Genre: Journal Article

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 Creators:
Hearst, MA, Author
Dumais, ST, Author
Osman, E, Author
Platt, J, Author
Schölkopf, B1, 2, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: My first exposure to Support Vector Machines came this spring when heard Sue Dumais present impressive results on text categorization using this analysis technique. This issue's collection of essays should help familiarize our readers with this interesting new racehorse in the Machine Learning stable. Bernhard Scholkopf, in an introductory overview, points out that a particular advantage of SVMs over other learning algorithms is that it can be analyzed theoretically using concepts from computational learning theory, and at the same time can achieve good performance when applied to real problems. Examples of these real-world applications are provided by Sue Dumais, who describes the aforementioned text-categorization problem, yielding the best results to date on the Reuters collection, and Edgar Osuna, who presents strong results on application to face detection. Our fourth author, John Platt, gives us a practical guide and a new technique for implementing the algorithm efficiently.

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 Dates: 1998-07
 Publication Status: Published in print
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 Identifiers: DOI: 10.1109/5254.708428
BibTex Citekey: 731
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Title: IEEE Intelligent Systems and their Applications
Source Genre: Journal
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Pages: - Volume / Issue: 13 (4) Sequence Number: - Start / End Page: 18 - 28 Identifier: -