title: The multilayer perceptron as an approximation to a Bayes optimal discriminant function.
abstract: The multilayer perceptron, when trained as a classifier using backpropagation, is shown to approximate the Bayes optimal discriminant function. The result is demonstrated for both the two-class problem and multiple classes. It is shown that the outputs of the multilayer perceptron approximate the a posteriori probability functions of the classes being trained. The proof applies to any number of layers and any type of unit activation function, linear or nonlinear.
authors.affiliation: Sch. of Eng., US Air Force Inst. of Technol., Wright-Patterson AFB, OH.
authors.forename: D W
authors.initials: DW
authors.lastname: Ruck
authors.forename: S K
authors.initials: SK
authors.lastname: Rogers
authors.forename: M
authors.initials: M
authors.lastname: Kabrisky
authors.forename: M E
authors.initials: ME
authors.lastname: Oxley
authors.forename: B W
authors.initials: BW
authors.lastname: Suter