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Vortrag

Semi-Supervised Support Vector Machines and Application to Spam Filtering

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84331

Zien,  A
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

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


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-D01D-8
Zusammenfassung
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.