On developing Sugeno fuzzy measure densities in problems of face recognition
by Paweł Karczmarek; Adam Kiersztyn; Witold Pedrycz
International Journal of Machine Intelligence and Sensory Signal Processing (IJMISSP), Vol. 2, No. 1, 2017

Abstract: Fuzzy measures and Choquet integral are efficient aggregation operators utilised intensively in decision-making theory. To produce sound classification results based on a family of classifiers, the parameters of the fuzzy measure (especially, so-called fuzzy densities) have to be determined. In this study, we propose a method based on particle swarm optimisation (PSO) and discuss in detail a new concept of a so-called positive and negative optimisation to fully utilise specific properties of classifiers to carry out efficient classification. A suite of experiments is conducted to illustrate this approach and discuss its scope of applicability.

Online publication date: Mon, 27-Nov-2017

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