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A probabilistic framework for SVM regression and error bar estimation
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DOI：10.1023/A:1012494009640.png)
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摘要
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In this paper, we elaborate on the well-known relationship between Gaussian Processes (GP) and Support Vector Machines (SVM) under some convex assumptions for the loss functions. This paper concentrates on the derivation of the evidence and error bar approximation for regression problems. An error bar formula is derived based on the epsilon -insensitive loss function.
Keyword:
support vector machine (SVM)
Gaussian process
epsilon-loss function
error bar estimation
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