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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.17 No.3
- 발행연도
- 2017.9
- 수록면
- 187 - 193 (7page)
- DOI
- 10.5391/IJFIS.2017.17.3.187
이용수
초록· 키워드
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In this paper, we compared the performance of support vector machine (SVM) and fuzzy SVM (FSVM) for reduction of learning time when classifying large-scale time series data into two classes. The fast learning time of the pattern classifier for large time series data is very useful in decision support systems. Considering the high interest in healthcare, including big data analysis, it is necessary to design a pattern classifier with a fast learning capability. We used large-scale time series data of 32 patients with sleep apnea (SA) for this study. The experiment was conducted by extending the parameter n, of the fuzzy membership function of FSVM, from 1 to 500. The result shows that the shortest learning time of FSVM is 3 s for radial base function (RBF), 17 s for a polynomial, and 35 s for a linear kernel, where the parameter n of the fuzzy membership function is n = 2, n = 433, and n = 4, respectively. The maximum classification hit rate of FSVM is 93.23%, and the learning time is significantly faster than conventional SVM. Therefore, FSVM can be used as a good classifier for the large-scale time series SA database.
목차
Abstract
1. Introduction
2. Related Work
3. Database
4. Experiments
5. Conclusions
References
참고문헌 (15)
참고문헌 신청
N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines. Cambridge: Cambridge University Press, 2000.
C. F. Lin and S. D. Wang, “Fuzzy support vector machines,” IEEE Transactions on Neural Networks, vol. 13, no. 2, pp. 464-471, 2002. http://doi.org/10.1109/72.991432
S. Y. Lee, S. Y. Sohn, C. E. Kim, and Y. B. Lee, “Fuzzy support vector machine for pattern classification of time series data of KOSPI200 Index,” Journal of Fuzzy Logic and Intelligent Systems, vol. 14, no. 1, pp. 52-56, 2004. http://doi.org/10.5391/JKIIS.2004.14.1.052
S. Y. Lee, “A comparative study of model design and performance test in financial index pattern classification system,” Ph.D. dissertation, Yonsei University, Seoul, Korea, 2004.
S. Y. Lee, “On the fuzzy membership function of time series data,” Journal of Fuzzy Logic and Intelligent Systems, vol. 17, no. 6, pp. 799-803, 2007.
C. F. Lin and S. D. Wang, “Fuzzy support vector machines,” IEEE Transactions on Neural Networks, vol. 13, no. 2, pp. 464-471, 2002. http://doi.org/10.1109/72.991432
S. Y. Lee, S. Y. Sohn, C. E. Kim, and Y. B. Lee, “Fuzzy support vector machine for pattern classification of time series data of KOSPI200 Index,” Journal of Fuzzy Logic and Intelligent Systems, vol. 14, no. 1, pp. 52-56, 2004. http://doi.org/10.5391/JKIIS.2004.14.1.052
S. Y. Lee, “A comparative study of model design and performance test in financial index pattern classification system,” Ph.D. dissertation, Yonsei University, Seoul, Korea, 2004.
S. Y. Lee, “On the fuzzy membership function of time series data,” Journal of Fuzzy Logic and Intelligent Systems, vol. 17, no. 6, pp. 799-803, 2007.
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