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Please note that a newer version of this item is available:
https://pure.mpg.de/pubman/item/item_1793148_2
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Summary
Normalization in Support Vector Machines
Graf, A.
(2001).
Normalization in Support Vector Machines.
DAGM 2001: Pattern Recognition.,
277-282.
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https://hdl.handle.net/11858/00-001M-0000-0013-E212-F
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https://hdl.handle.net/11858/00-001M-0000-0013-E213-D
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Conference Paper
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Creators
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Graf, ABA
1, 2
, Author
Radig S. Florczyk, B., Editor
Affiliations
:
1
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795
2
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797
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Abstract
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This article deals with various aspects of normalization in the context of Support Vector Machines. We consider fist normalization of the vectors in the input space and point out the inherent limitations. A natural extension to the feature space is then represented by the kernel function normalization. A correction of the position of the Optimal Separating Hyperplane is subsequently introduced so as to suit better these normalized kernels. Numerical experiments finally evaluate the different approaches.
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Date issued:
2001-09
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Issued
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ISBN: 3-540-45404-7
URI:
http://www.springerlink.com/content/q3068112g9332857/fulltext.pdf
DOI:
10.1007/3-540-45404-7_37
BibTex Citekey: 305
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Title
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23rd DAGM Symposium
Place of Event
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München, Germany
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Title
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DAGM 2001: Pattern Recognition.
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Berlin, Germany : Springer
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Start / End Page
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277 - 282
Identifier
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