# Bayes classification based on minimum bounding spheres

@article{Wang2007BayesCB, title={Bayes classification based on minimum bounding spheres}, author={Jigang Wang and Predrag Neskovic and Leon N. Cooper}, journal={Neurocomputing}, year={2007}, volume={70}, pages={801-808} }

- Published 2007 in Neurocomputing
DOI:10.1016/j.neucom.2006.10.023

The minimum bounding sphere of a set of data, defined as the smallest sphere enclosing the data, was first used by Schölkopf et al. to estimate the VC-dimension of support vector classifiers and later applied by Tax and Duin to data domain description. Given a set of data, the minimum bounding sphere of each class can be computed by solving a quadratic programming problem. Since the spheres are constructed for each class separately, they can be used to deal with the multi-class classification… CONTINUE READING