An expert system based on fisher score and LS-SVM for cardiac arrhythmia diagnosis

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Date

2013

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Publisher

Hindawi Ltd

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.

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Keywords

Mathematical & computational biology, Diseases, Expert systems, Cardiac arrhythmia, Data set, Feature space, Feature space, Fisher score, Least squares support vector machines, UCI machine learning repository, Support vector machines

Citation

Yılmaz, E. (2013). "An expert system based on fisher score and LS-SVM for cardiac arrhythmia diagnosis". Computational and Mathematical Methods in Medicine, 2013.