caa a22 4500 477072933 CHVBK 20180405111431.0 cr unu---uuuuu 170330e19960901xx s 000 0 eng 10.1007/BF01414873 doi (NATIONALLICENCE)springer-10.1007/BF01414873 Bayesian regression filters and the issue of priors [Elektronische Daten] [Huaiyu Zhu, Richard Rohwer] We propose a Bayesian framework for regression problems, which covers areas usually dealt with by function approximation. An online learning algorithm is derived which solves regression problems with a Kalman filter. Its solution always improves with increasing model complexity, without the risk of over-fitting. In the infinite dimension limit it approaches the true Bayesian posterior. The issues of prior selection and over-fitting are also discussed, showing that some of the commonly held beliefs are misleading. The practical implementation is summarised. Simulations using 13 popular publicly available data sets are used to demonstrate the method and highlight important issues concerning the choice of priors. Springer-Verlag London Limited, 1996 Approximation nationallicence Bayesian method nationallicence Kalman filter nationallicence Online learning nationallicence Prior selection nationallicence Radial Basis Functions nationallicence Regression nationallicence Zhu Huaiyu Neural Computing Research Group, Department of Computer Science and Applied Mathematics, Aston University, B4 7ET, Birmingham, UK aut Rohwer Richard Neural Computing Research Group, Department of Computer Science and Applied Mathematics, Aston University, B4 7ET, Birmingham, UK aut Neural Computing & Applications Springer-Verlag 4/3(1996-09-01), 130-142 0941-0643 4:3<130 1996 4 521 https://doi.org/10.1007/BF01414873 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF01414873 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhu Huaiyu Neural Computing Research Group, Department of Computer Science and Applied Mathematics, Aston University, B4 7ET, Birmingham, UK aut NATIONALLICENCE 700 1- Rohwer Richard Neural Computing Research Group, Department of Computer Science and Applied Mathematics, Aston University, B4 7ET, Birmingham, UK aut NATIONALLICENCE 773 0- Neural Computing & Applications Springer-Verlag 4/3(1996-09-01), 130-142 0941-0643 4:3<130 1996 4 521 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer