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Tradeoff search methods between interpretability and accuracy of the identification fuzzy systems based on rules.
- Source :
- Pattern Recognition & Image Analysis; Apr2017, Vol. 27 Issue 2, p243-265, 23p
- Publication Year :
- 2017
-
Abstract
- This paper starts a brief historical overview of occurrence and development of fuzzy systems and their applications. Integration methods are proposed to construct a fuzzy system using other AI methods, achieving synergy effect. Accuracy and interpretability are selected as main properties of rule-based fuzzy systems. The tradeoff between interpretability and accuracy is considered to be the actual problem. The purpose of this paper is the in-depth study of the methods and tools to achieve a tradeoff for accuracy and interpretability in rule-based fuzzy systems and to describe our interpretability indexes. A comparison of the existing ways of interpretability estimation has been made We also propose the new way to construct heuristic interpretability indexes as a quantitative measure of interpretability. In the main part of this paper we describe previously used approaches, the current state and original authors' methods for achieving tradeoff between accuracy and complexity. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10546618
- Volume :
- 27
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Pattern Recognition & Image Analysis
- Publication Type :
- Academic Journal
- Accession number :
- 123586016
- Full Text :
- https://doi.org/10.1134/S1054661817020134