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A Simple Method For Estimating Conditional Probabilities For SVMs

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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.

Language: Englisch

Bibliographic citation: Series: Technical Report ; No. 2004,56

Subject: Mustererkennung
Schätztheorie
Theorie
Klassifikationsanalyses

Event: Geistige Schöpfung

(who): Rüping, Stefan

Event: Veröffentlichung

(who): Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen

(where): Dortmund

(when): 2004

Handle: http://hdl.handle.net/10419/22569

Last update: 10.03.2025, 11:45 AM CET

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Object type

Arbeitspapier

Associated

Rüping, Stefan
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen

Time of origin

2004

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