title: An expert system based on Fisher score and LS-SVM for cardiac arrhythmia diagnosis.
abstract: 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.
authors.affiliation: Electrical-Electronic Engineering Department, Uludag University, Gorukle, 16059 Bursa, Turkey. ersen@uludag.edu.tr
authors.forename: Ersen
authors.initials: E
authors.lastname: Yılmaz
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis*; D001185:Artificial Intelligence; D019295:Computational Biology; D016208:Databases, Factual / Q000706:statistics & numerical data; D003936:Diagnosis, Computer-Assisted / Q000706:statistics & numerical data*; D004562:Electrocardiography / Q000706:statistics & numerical data; D005103:Expert Systems; D006801:Humans; D016018:Least-Squares Analysis; D060388:Support Vector Machine