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The fuzzy representation of prior information for separating outliers in statistical experiments.

P. 167–174.
Bronevich A., Мацыпаев Д. А.

The paper presents a new fuzzy set based description which helps to distinguish the expected values of the statistical experiment from the outliers. Since the Neyman-Pearson criterion is not adequate in some real applications for such purpose, we propose to use triangular norms for conjuction of two propositions about typical and non-typical values and describe both of them as a fuzzy set that is called the typical transform. We also investigate such a property of the typical transform as stability.

Language: English
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Keywords: нечеткие множестваfuzzy setsdistortion functionsoutlierstriangular normsNeyman-Pearson criterion,Lipschitz continuityфункции искажениятриангулярные нормыкритерий Неймана-Пирсонанепрерывность по Липшицу
Publication based on the results of:
Построение и исследование моделей неточных вероятностей, основанных на агрегирующих функциях (2014)

In book

Strengthening Links Between Data Analysis and Soft Computing
Strengthening Links Between Data Analysis and Soft Computing
Vol. 315. , Dordrecht, L., Heidelberg, NY: Springer, 2015.
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