Approximate Confidence and Prediction Intervals for Least Squares Support Vector Regression

Abstract

Bias-corrected approximate 100(1-α)% pointwise and simultaneous confidence and prediction intervals for least squares support vector machines are proposed. A simple way of determining the bias without estimating higher order derivatives is formulated. A variance estimator is developed that works well in the homoscedastic and heteroscedastic case. In order… (More)
DOI: 10.1109/TNN.2010.2087769

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