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  Semi-Supervised Support Vector Machines and Application to Spam Filtering

Zien, A. (2006). Semi-Supervised Support Vector Machines and Application to Spam Filtering. Talk presented at ECML/PKDD Discovery Challenge Workshop. Berlin, Germany. 2006-09-22.

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http://www.ecmlpkdd2006.org/challenge.html (Table of contents)
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 Creators:
Zien, A1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: After introducing the semi-supervised support vector machine (aka TSVM for "transductive SVM"), a few popular training strategies are briefly presented. Then the assumptions underlying semi-supervised learning are reviewed. Finally, two modern TSVM optimization techniques are applied to the spam filtering data sets of the workshop; it is shown that they can achieve excellent results, if the problem of the data being non-iid can be handled properly.

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 Dates: 2006-09
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 4162
 Degree: -

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Title: ECML/PKDD Discovery Challenge Workshop
Place of Event: Berlin, Germany
Start-/End Date: 2006-09-22
Invited: Yes

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