Extracting easily interpreted diagnostic rules

DOI10.1016/J.INS.2017.10.034zbMath1436.68355OpenAlexW2766615515MaRDI QIDQ781281

Ewa Straszecka, Sebastian Porebski

Publication date: 16 July 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2017.10.034

zbMATH Keywords

Dempster-Shafer theoryrule extractionfuzzy focal elementsmedical diagnosis support

Mathematics Subject Classification ID

Medical applications (general) (92C50) Reasoning under uncertainty in the context of artificial intelligence (68T37) Computing methodologies for information systems (hypertext navigation, interfaces, decision support, etc.) (68U35)

Cites Work

• Fuzzy logic-based generalized decision theory with imperfect information
• Decision-theoretic rough fuzzy set model and application
• Achieving a compromise between performance and complexity of structure: an incremental approach
• Genetic learning of the membership functions for mining fuzzy association rules from low quality data
• Fuzzy valued probability
• Generalized probabilities of fuzzy events from fuzzy belief structures
• Set-theoretic methodology using fuzzy sets in rule extraction and validation -- consistency and coverage revisited
• Fuzzy sets as a basis for a theory of possibility
• Membership Functions for Fuzzy Focal Elements
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