Details

Title

Membership Functions for Fuzzy Focal Elements

Journal title

Archives of Control Sciences

Yearbook

2016

Numer

No 3

Publication authors

Divisions of PAS

Nauki Techniczne

Abstract

<jats:title>Abstract</jats:title> <jats:p>The paper presents a study on data-driven diagnostic rules, which are easy to interpret by human experts. To this end, the Dempster-Shafer theory extended for fuzzy focal elements is used. Premises of the rules (fuzzy focal elements) are provided by membership functions which shapes are changing according to input symptoms. The main aim of the present study is to evaluate common membership function shapes and to introduce a rule elimination algorithm. Proposed methods are first illustrated with the popular Iris data set. Next experiments with five medical benchmark databases are performed. Results of the experiments show that various membership function shapes provide different inference efficiency but the extracted rule sets are close to each other. Thus indications for determining rules with possible heuristic interpretation can be formulated.</jats:p>

Publisher

Committee of Automatic Control and Robotics PAS

Date

2016

Identifier

ISSN 1230-2384

References

Coomans (1992), Thyroid Gland Data https : archive ics uci edu ml machine - learning - databases / thyroid - disease new thyroid data accessed February, Online, 18. ; BEZDEK (1993), Fuzzy models what are they and why ? editorial ] IEEE on Fuzzy Systems, Trans, 1, 1. ; STRASZECKA (2006), Combining uncertainty and imprecision in models of medical diagnosis Information, Sciences, 20, 176. ; FISHER (1988), Iris Plants Database https : archive ics uci edu ml machine - learning - databases iris iris data accessed February, Online, 10. ; WOLBERG (1992), Wisconsin Breast Cancer Database Original ) https archive ics uci edu ml machine - learning - databases / breast - cancer - wisconsin / breast - cancer - wisconsin data accessed February, Online, 18. ; SIGILLITO (1990), Pima Indians Diabetes Database https archive ics uci edu ml machine - learning - databases / pima - indians - diabetes / pima - indians - diabetes data accessed February, Online, 18. ; KANTARCI (2015), Influence of t - norm and t - conorm operators in fuzzy id algorithm In IEEE Int Conf on Fuzzy Systems ( FUZZ, IEEE, 1. ; MEDAGLIA (2002), - An efficient and flexible mechanism for constructing membership functions European of Operational Research PORE BSKI Design of fuzzy rule - based classifiers with semantic cointension Information Special Issue on Interpretable Fuzzy Systems, Sciences, 139, 84. ; YAGER (2002), Uncertainty representation using fuzzy measures IEEE Trans on Systems Man and Cybernetics Part, Cybernetics, 32, 13. ; DETRANO (1990), Heart Disease Database Cleveland ) https archive ics uci edu ml machine - learning - databases / heart - disease processed cleveland data accessed February, Online, 18.

DOI

10.1515/acsc-2016-0022

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