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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Expert systems with applications Jg. 130; S. 188 - 205
Hauptverfasser:	Singh, Namrata, Singh, Pradeep, Bhagat, Deepika
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 15.09.2019 Elsevier BV
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!