A rule extraction approach from support vector machines for diagnosing hypertension among diabetics

•Classification of datasets on diabetes and its complications are considered.•Five feature selection algorithms are utilized for choosing significant features.•A hybrid rule-extraction method generating comprehensible rule sets is developed.•Experiments were performed on six datasets: one new and fi...

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Bibliographic Details
Published in:	Expert systems with applications Vol. 130; pp. 188 - 205
Main Authors:	Singh, Namrata, Singh, Pradeep, Bhagat, Deepika
Format:	Journal Article
Language:	English
Published:	New York Elsevier Ltd 15.09.2019 Elsevier BV
Subjects:	Algorithms Black boxes Datasets Decision making Diabetes Diabetes mellitus Epidemics Extreme gradient boosting Feature extraction Hypertension Machine learning Mathematical models Medical diagnosis Public health Rule extraction Signs and symptoms Support vector machine Support vector machines Hypertension Extreme gradient boosting Diabetes Support vector machine Medical diagnosis Rule extraction
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
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