Article ID Journal Published Year Pages File Type
535440 Pattern Recognition Letters 2014 8 Pages PDF
Abstract

•No confidence and prediction intervals have been derived yet for mixed effect LS-SVM.•We derive analytical formulas for quantifying uncertainty for mixed effect LS-SVM.•Derived formulas closely match results from the wild cluster bootstrap-t procedure.

We consider estimating the confidence and prediction intervals for semiparametric mixed-effect least squares support vector machine (LS-SVM). Explicit formulas are derived for confidence and prediction intervals. The accuracy of the derived analytical equations is assessed by comparing with wild cluster bootstrap-t method on simulated and real-world data with different levels of random-effect and residual variances, and different numbers of clusters. Close match between the derived expressions and the bootstrap results is observed.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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