An Expert System Based on Fisher Score and LS-SVM for Cardiac Arrhythmia Diagnosis | Zendy

Ersen Yılmaz | Zendy

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An Expert System Based on Fisher Score and LS-SVM for Cardiac Arrhythmia Diagnosis

Author(s) -

Ersen Yılmaz

Publication year - 2013

Publication title -

computational and mathematical methods in medicine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.462

H-Index - 48

eISSN - 1748-6718

pISSN - 1748-670X

DOI - 10.1155/2013/849674

Subject(s) - cardiac arrhythmia , feature selection , artificial intelligence , support vector machine , classifier (uml) , pattern recognition (psychology) , computer science , feature vector , feature (linguistics) , data set , data mining , machine learning , medicine , atrial fibrillation , linguistics , philosophy

An expert system having two stages is proposed for cardiac arrhythmia diagnosis. In the first stage, Fisher score is used for feature selection to reduce the feature space dimension of a data set. The second stage is classification stage in which least squares support vector machines classifier is performed by using the feature subset selected in the first stage to diagnose cardiac arrhythmia. Performance of the proposed expert system is evaluated by using an arrhythmia data set which is taken from UCI machine learning repository.

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