Tradeoff Search Methods between Interpretability and Accuracyof the Identification Fuzzy Systems Based on Rules
| Parent link: | Pattern Recognition and Image Analysis Vol. 27, No. 2.— 2017.— [P. 243–266] |
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| Resumo: | 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 |
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2017
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| Acesso em linha: | https://doi.org/10.1134/S1054661817020134 |
| Formato: | Recurso Eletrônico Capítulo de Livro |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=664555 |