NDLI: Rough-Fuzzy Classifier: A System to Predict the Heart Disease by Blending Two Different Set Theories

Content Provider	Springer Nature Link
Author	Srinivas, K. Rao, G. Raghavendra Govardhan, A.
Copyright Year	2014
Abstract	Heart disease prediction has been a significant research over the past decade, because the major cause of death worldwide is due to heart disease. To predict the heart disease, several researchers combined fuzzy technique with some other technique for efficient classification purpose, since the fuzzy is efficient only if proper fuzzy rules are given in the rule base. Here, we have introduced a rough-fuzzy classifier that combined rough set theory with the fuzzy set. The overall process of the rough-fuzzy classifier is divided into two major steps, such as (1) rule generation using rough set theory, and (2) prediction using fuzzy classifier. At first, reduct and core analysis is used to identify the relevant attributes and the fuzzy rules are generated from the rough set theory after forming the indiscernibility matrix. Then, the fuzzy system is designed with the help of fuzzy rules and membership functions so that the prediction can be carried out within the fuzzy system designed. Finally, the experimentation is carried out using the Cleveland, Hungarian and Switzerland datasets. From the results, we ensure that the proposed rough-fuzzy classifier outperformed the previous approach by achieving the accuracy of 80 % in Switzerland and 42 % in Hungarian datasets.
Starting Page	2857
Ending Page	2868
Page Count	12
File Format	PDF
ISSN	13198025
Journal	Arabian Journal for Science and Engineering
Volume Number	39
Issue Number	4
e-ISSN	21914281
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-02-09
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Heart disease Rough set Fuzzy set classification Engineering Science
Content Type	Text
Resource Type	Article

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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
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