Arbeitspapier
A Simple Method For Estimating Conditional Probabilities For SVMs
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Technical Report ; No. 2004,56
- Thema
-
Mustererkennung
Schätztheorie
Theorie
Klassifikationsanalyses
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Rüping, Stefan
- Ereignis
-
Veröffentlichung
- (wer)
-
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (wo)
-
Dortmund
- (wann)
-
2004
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Rüping, Stefan
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Entstanden
- 2004
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