Journal of the Korean Data and Information Science Society
- 제17권2호
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- Pages.609-617
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- 2006
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- 1598-9402(pISSN)
Switching Regression Analysis via Fuzzy LS-SVM
- Hwang, Chang-Ha (Division of Information and Computer Science, Dankook University)
- 발행 : 2006.05.30
초록
A new fuzzy c-regression algorithm for switching regression analysis is presented, which combines fuzzy c-means clustering and least squares support vector machine. This algorithm can detect outliers in switching regression models while yielding the simultaneous estimates of the associated parameters together with a fuzzy c-partitions of data. It can be employed for the model-free nonlinear regression which does not assume the underlying form of the regression function. We illustrate the new approach with some numerical examples that show how it can be used to fit switching regression models to almost all types of mixed data.
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