SVM Classification Algorithm in ECG Classification
Support Vector Machine classification was studied by this article. Kernel function was used on Electrocardiogram (ECG) classification. Classification results show that the support vector machine classification algorithm reduce the complexity of the classification algorithm, and to ensure that the ECG classification accuracy, while the feasibility and effectiveness of the classification of ideas in the ECG classification.
KeywordsSupport Vector Machine (SVM) Kernel function Classification Electrocardiogram
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- 1.Zhang, X.: Clinical ecg analysis and diagnosis. People’s Medical Publishing House (2007)Google Scholar
- 4.Deng, N., et al.: Support vector Machine Theory, algorithms and Development, p. 176. Science Press, Beijing (2009) (in Chinese)Google Scholar
- 5.Miller, J.M., Rochitte, C.E., Dewey, M., et al.: Diagnostic performance of coronary angiography by64-row CT (2008)Google Scholar
- 6.Liu, J., Li, S., Luo, X.: Classification Algorithm of Support Vector Machine via p-norm Regularization. Acta Automatica Sinica (1) (2012) (in Chinese)Google Scholar
- 7.Teo, C.H., Vishwanathan, S.V.N., Smola, A., et al.: Bundle methods for regularized risk minimization. Journal of Machine Learning Research (2010)Google Scholar
- 8.Zhang, Z., Wang, S., Deng, Z., Chung, F.: A fast decision algorithm of support vector machine. Control and Decision (3) (2012) (in Chinese) Google Scholar
- 9.Tang, Y., Li, Y.: Geometric Construction Method of Linear SVM Multi-class Classifier. Computer Engineering (4) (2012) (in Chinese) Google Scholar
- 10.Li, S., Zhou, W., Cai, D., Liu, K., Zhao, J.: EEG Signal Classification Based on EMD and SVM. Journal of Biomedical Engineering (5) (2011) (in Chinese)Google Scholar
- 11.Xu, Z.-x., Wang, Y., et al.: Recognition of TCM syndrome types of cardiovascular diseases based on support vector machine and artificial neural networks. Journal of Beijing University of Traditional Chinese Medicine (8) (2011) (in Chinese)Google Scholar