Simultaneous learning of several bayesian and mahalanobis discriminant functions by a neural network with memory nodes

Authors:
Yoshifusa Ito;Hiroyuki Izumi;Cidambi Srinivasan
Affiliations:
Aichi Medical University, Nagakute, Japan;Aichigakuin University, Nisshin, Iwasaki, Japan;University of Kentucky, Lexington
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Year:
2012

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Abstract

We construct a one-hidden-layer neural network capable of learning simultaneously several Bayesian discriminant functions and converting them to the corresponding Mahalanobis discriminant functions in the two-category, normal-distribution case. The Bayesian discriminant functions correspond to the respective situations on which the priors and means depend. The algorithm is characterized by the use of the inner potential of the output unit and additional several memory nodes. It is remarkably simpler when compared with our previous algorithm.