Blackmore, Kim; Williamson, Robert C.; Mareels, Iven M. Y.
We give degree of approximation results for decision regions which are defined by polynomial and neural network
parametrizations. The volume of the misclassified region is used to measure the approximation error, and results for the degree
of L1 approximation of functions are used. For polynomial parametrizations, we show that the degree of approximation is at
least 1, whereas for neural network parametrizations we prove the slightly weaker result that the degree of approximation is at least...[Show more]
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