The multilayer perceptron as an approximation to a Bayes optimal discriminant function.
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.
Ruck
D W
DW
Sch. of Eng., US Air Force Inst. of Technol., Wright-Patterson AFB, OH.
Rogers
S K
SK
Kabrisky
M
M
Oxley
M E
ME
Suter
B W
BW