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Adapting two-class support vector classification methods to many class problems

Abstract:
A geometric construction is presented which is shown to be an effective tool for understanding and implementing multi-category support vector classification. It is demonstrated how this construction can be used to extend many other existing two-class kernel-based classification methodologies in a straightforward way while still preserving attractive properties of individual algorithms. Reducing training times through incorporating the results of pairwise classification is also discussed and experimental results presented.

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Pages:
313-320
Publication date:
2005
URN:
uuid:7639f864-fc93-4e89-a3bc-0682cb7dc91a
Source identifiers:
172726
Local pid:
pubs:172726
ISBN:
1595931805

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