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  Fast Pattern Selection for Support Vector Classifiers

Shin, H., & Cho, S. (2003). Fast Pattern Selection for Support Vector Classifiers. In K.-Y. Whang, J. Jeon, K. Shim, & J. Srivastava (Eds.), Advances in Knowledge Discovery and Data Mining: 7th Pacific-Asia Conference, PAKDD 2003, Seoul, Korea, April 30 – May 2 (pp. 376-387). Berlin, Germany: Springer.

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 Creators:
Shin, H1, Author              
Cho, S, Author
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1External Organizations, ou_persistent22              

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 Abstract: Training SVM requires large memory and long cpu time when the pattern set is large. To alleviate the computational burden in SVM training, we propose a fast preprocessing algorithm which selects only the patterns near the decision boundary. Preliminary simulation results were promising: Up to two orders of magnitude, training time reduction was achieved including the preprocessing, without any loss in classification accuracies.

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 Dates: 2003-05
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1007/3-540-36175-8_37
BibTex Citekey: 2693
 Degree: -

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Title: 7th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2003)
Place of Event: Seoul, South Korea
Start-/End Date: 2003-04-30 - 2003-05-02

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Title: Advances in Knowledge Discovery and Data Mining: 7th Pacific-Asia Conference, PAKDD 2003, Seoul, Korea, April 30 – May 2
Source Genre: Proceedings
 Creator(s):
Whang, K-Y, Editor
Jeon, J, Editor
Shim, K, Editor
Srivastava, J, Editor
Affiliations:
-
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 376 - 387 Identifier: ISBN: 978-3-540-04760-5