Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/22569 
Autor:innen: 
Erscheinungsjahr: 
2004
Schriftenreihe/Nr.: 
Technical Report No. 2004,56
Verlag: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Zusammenfassung: 
Support Vector Machines (SVMs) have become a popular learning algorithm, in particular for large, high-dimensional classification problems. SVMs have been shown to give most accurate classification results in a variety of applications. Several methods have been proposed to obtain not only a classification, but also an estimate of the SVMs confidence in the correctness of the predicted label. In this paper, several algorithms are compared which scale the SVM decision function to obtain an estimate of the conditional class probability. A new simple and fast method is derived from theoretical arguments and empirically compared to the existing approaches.
Dokumentart: 
Working Paper

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