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A Review on the Development of Fuzzy Classifiers with Improved Interpretability and Accuracy Parameter

Farheen Azad, Praveen Kumar Shukla
Review Paper | Journal Paper
Volume 2 , Issue 2: Special Issue on Artificial Intelligence (ICAI-2021) , PP 1-9
DOI: https://doi.org/10.54060/JIEEE/002.02.020

Abstract

This review paper of fuzzy classifiers with improved interpretability and accuracy parameter discussed the most fundamental aspect of very effective and powerful tools in form of probabilistic reasoning, The fuzzy logic concept allows the effective realization of ap-proximate, vague, uncertain, dynamic, and more realistic conditions, which is closer to the actual physical world and human thinking. The fuzzy theory has the competency to catch the lack of preciseness of linguistic terms in a speech of natural language. The fuzzy theory provides a more significant competency to model humans like com-mon-sense reasoning and conclusion making to fuzzy set and rules as good membership function. Also, in this paper reviews discussed the evaluation of the fuzzy set, type-1, type-2, and interval type-2 fuzzy system from traditional Boolean crisp set logic along with interpretability and accuracy issues in the fuzzy system.

Key-Words / Index Term

Fuzzy logic, Fuzzy set, Crisp sets, Accuracy and Interpretability trade off, Type-2 fuzzy system, Interval type-2 fuzzy system

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