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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Vydané v:	Expert systems with applications Ročník 130; s. 188 - 205
Hlavní autori:	Singh, Namrata, Singh, Pradeep, Bhagat, Deepika
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Elsevier Ltd 15.09.2019 Elsevier BV
Predmet:	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
On-line prístup:	Získať plný text
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