NDLI: Designing fuzzy rule-based classifiers that can visually explain their classification results to human users

Content Provider	IEEE Xplore Digital Library
Author	Ishibuchi, H. Kaisho, Y. Nojima, Y.
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci. & Intell. Syst., Osaka Prefecture Univ., Sakai (Ishibuchi, H.; Kaisho, Y.; Nojima, Y.)
Abstract	In various application areas of fuzzy rule-based systems, human users want to know why a particular reasoning result is obtained. That is, fuzzy rule-based systems are required to have high explanation ability. In this paper, we propose an approach to the design of fuzzy rule-based classifiers that can visually explain their classification results to human users. That is, our fuzzy rule-based classifiers can explain to human users why an input pattern is classified as a particular class in an understandable manner. The proposed approach consists of a rule selection method and a visualization interface. Our idea is to design fuzzy rule-based classifiers using fuzzy rules with only two antecedent conditions. A genetic algorithm is employed to construct a compact fuzzy rule-based classifier by choosing only a small number of fuzzy rules. In the classification phase, we use a single winner rule-based method for classifying an input pattern. The classification result of the input pattern is visually explained in a two-dimensional space where the two antecedent conditions of the winner rule are defined. Our approach is compared with feature selection by computational experiments.
Starting Page	5
Ending Page	10
File Size	1514028
Page Count	6
File Format	PDF
ISBN	9781424416127
DOI	10.1109/GEFS.2008.4484559
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-04
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy sets Visualization Conferences Knowledge based systems Humans Fuzzy neural networks Fuzzy reasoning Fuzzy systems Genetic algorithms Design optimization
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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