Abstract
The paper presents the comparison of performance of the individual and ensemble of SVM classifiers for the recognition of abnormal heartbeats on the basis of the registered ECG waveforms. The recognition system applies two different Support Vector Machine based classifiers and the ensemble systems composed of the individual classifiers combined together in different way to obtain the best possible performance on the ECG data. The results of numerical experiments using the data of MIT BIH Arrhythmia Database have confirmed the superior performance of the proposed solution.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11550907_163 .
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Osowski, S., Linh, T.H., Markiewicz, T. (2005). Recognition of Heartbeats Using Support Vector Machine Networks – A Comparative Study. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550907_101
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DOI: https://doi.org/10.1007/11550907_101
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28755-1
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