Soft-Margin SVM Incorporating Feature Selection Using Improved Elitist GA for Arrhythmia Classification-Reference-Cited by-同舟云学术

Soft-Margin SVM Incorporating Feature Selection Using Improved Elitist GA for Arrhythmia Classification

Published:2019-04-14 Issue: Volume: Page:965-976
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Kadam Vinod J.,Yadav Samir S.,Jadhav Shivajirao M.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-16660-1_94

Reference24 articles.

1. Kadam, V.J., Jadhav, S.M.: Feature ensemble learning based on sparse autoencoders for diagnosis of Parkinson’s Disease. In: Iyer, B., Nalbalwar, S., Pathak, N. (eds.) Computing, Communication and Signal Processing. Advances in Intelligent Systems and Computing, vol. 810. Springer, Singapore (2019)

2. Why Arrhythmia Matters. Heart.org (2017). http://www.heart.org/HEARTORG/Conditions/Arrhythmia/WhyArrhythmiaMatters/Why-Arrhythmia-Matters_UCM_002023_Article.jsp . Accessed 08 Feb 2018

3. Leng, S., San Tan, R., Chai, K.T.C., Wang, C., Ghista, D., Zhong, L.: The electronic stethoscope. Biomed. Eng. OnLine 14(1), 66 (2015). https://doi.org/10.1186/s12938-015-0056-y

4. Guvenir, H.A., Acar, B., Demiroz, G., Cekin, A.: A supervised machine learning algorithm for arrhythmia analysis. In: Computers in Cardiology 1997, Lund, Sweden, pp. 433–436 (1997)

5. Dua, D., Taniskidou, E.K.: UCI Machine Learning Repository. School of Information and Computer Science, University of California, Irvine, CA (2017). http://archive.ics.uci.edu/ml

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