Using radial basis functions to approximate a function and its error bounds
IEEE Transactions on Neural NetworksPublished 1 July 1992
James A. Leonard, Mark A. Kramer, Lyle Ungar
Citations252
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TL;DR
A novel network called the validity index network (VI net), derived from radial basis function networks, fits functions and calculates confidence intervals for its predictions, indicating local regions of poor fit and extrapolation.
Abstract
A novel network called the validity index network (VI net) is presented. The VI net, derived from radial basis function networks, fits functions and calculates confidence intervals for its predictions, indicating local regions of poor fit and extrapolation.
Keywords
Computer SciencePhysics and Astronomy
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