Extending Dempster Shafer method by multilayer decision template in classifier fusion

Abstract

In this paper, a new classifier fusion method is introduced based on a decision template structure as an extension to Dempster Shafer method. It employs multilayer neural networks as base classifiers. The idea relies on the fact that in a multilayer neural network, behavior of each layer can be a guide for modeling decision-making process. The new decision template based method constructs decision template for each layer of the neural networks including all hidden layers such that a complete model of the base classifiers decision making process is built. In the combiner part, a new strategy based on extension to Dempster Shafer method is introduced. Efficiency of this method is compared with some known benchmark datasets.