Tradeoff Search Methods between Interpretability and Accuracyof the Identification Fuzzy Systems Based on Rules

Detaylı Bibliyografya
Parent link:Pattern Recognition and Image Analysis
Vol. 27, No. 2.— 2017.— [P. 243–266]
Yazar: Yankovskaya A. E. Anna Efimovna
Müşterek Yazar: Национальный исследовательский Томский политехнический университет Инженерная школа энергетики Отделение электроэнергетики и электротехники
Diğer Yazarlar: Gorbunov I. V., Khodashinsky I. A.
Özet:Title screen
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.
Режим доступа: по договору с организацией-держателем ресурса
Baskı/Yayın Bilgisi: 2017
Konular:
Online Erişim:https://doi.org/10.1134/S1054661817020134
Materyal Türü: Elektronik Kitap Bölümü
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=664555

MARC

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330 |a 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. 
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