Konferenzbeitrag
Support vector machines in relational databases
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Dokumententyp
Text/Conference Paper
Datum
2002
Autor:innen
Zeitschriftentitel
ISSN der Zeitschrift
Bandtitel
Quelle
Informatik bewegt: Informatik 2002 - 32. Jahrestagung der Gesellschaft für Informatik e.v. (GI)
Regular Research Papers
Verlag
Gesellschaft für Informatik e.V.
Zusammenfassung
Today, most of the data in business applications is stored in relational databases. Relational database systems are so popular, because they offer solutions to many problems around data storage, such as efficiency, effectiveness, usability, security and multi-user support. To benefit from these advantages in Support Vector Machine (SVM) learning, we will develop an implementation of the SVM learning algorithm, that can be run inside a relational database system. Even if this kind of implementation obviously cannot be as efficient as a standalone implementation, it will be favorable in situations, where requirements other than efficiency for learning play an important role.