Generalizations of Aggregation Functions for Face Recognition

The problem of aggregation of the classification results is one of the most important task in image recognition or decision-making theory. There are many approaches to solve this problem as well as many operators and algorithms proposed such as voting, scoring, averages, and more advanced ones. In this paper, we examine the well-known existing and recently introduced to the practice of classification tasks generalizations of aggregation functions. Moreover, we introduce a few operators which have not been presented in the literature of the subject. The findings of this paper can shed a new light onto the theory of face recognition and help build advanced ensembles of classifiers.

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