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Conference Papers Year : 2021

Building Intuitionistic Fuzzy Sets in Machine Learning

Abstract

The construction of intuitionistic fuzzy sets is a difficult task. Some approaches have been proposed in the literature and they have been used successfully in some application domains. However, these approaches do barely take into account the representativeness of the data used to build the intuitionistic fuzzy set. In this paper, a new approach is proposed to build intuitionistic fuzzy sets (IFS). This approach is based on the use of a representativeness degree of the data. This approach enables to build an IFS with an intuitionistic fuzzy index that is a good indicator of the lack of knowledge associated with the data that make it a good approach to be used in a Machine learning setting.
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Dates and versions

hal-03504183 , version 1 (28-12-2021)

Identifiers

  • HAL Id : hal-03504183 , version 1

Cite

Christophe Marsala. Building Intuitionistic Fuzzy Sets in Machine Learning. The 13th International Workshop on Fuzzy Logic and Applications, Dec 2021, Vietri sul Mare, Italy. ⟨hal-03504183⟩
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