We apply here a probabilistic method to predict the effect of quantizing the parameters of a Support Vector Machine. Thank to the particular structure of the SVM, the dependency of the output from the quantization noise can be predicted with good accuracy, and a simple closed–form formula can be derived, without imposing any hard–to–verify assumption

The Effects of Quantization on Support Vector Machines with Gaussian Kernel

ANGUITA, DAVIDE;
2005-01-01

Abstract

We apply here a probabilistic method to predict the effect of quantizing the parameters of a Support Vector Machine. Thank to the particular structure of the SVM, the dependency of the output from the quantization noise can be predicted with good accuracy, and a simple closed–form formula can be derived, without imposing any hard–to–verify assumption
2005
9780780390485
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/315647
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