Performance Evaluation of Kernel-Based Supervised Noise Clustering Approach

Author:

SenGupta IshuitaORCID,Kumar Anil,Dwivedi Rakesh Kumar

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Geography, Planning and Development

Reference62 articles.

1. Awan, A. M., & Sap, M. N. M. (2005). Clustering spatial data using a kernel-based algorithm. In Proceedings of the Annual Research Seminar (pp. 306–310).

2. Ayat, N. E., Cheriet, M., Remaki, L., & Suen, C. Y. (2001). KMOD—a new support vector machine kernel with moderate decreasing. In Document analysis and recognition, 2001. Proceedings, 6th international conference (pp. 1215–1219).

3. Ben-Hur, A., Horn, D., Siegelmann, H. T., & Vapinik, V. (2001). Support vector clustering. Journal of Machine Learning Research, 2, 125–137.

4. Bezdek, J. C., Ehrlich, R., & Full, W. (1984). FCM: The fuzzy c-means clustering algorithm. Computers and Geosciences, 10(2–3), 191–203.

5. Bhatt, S. R., & Mishra, P. K. (2013). Study of local kernel with fuzzy c-mean algorithm. International Journal of Advanced Research in Computer and Software Engineering, 3(12), 636–639.

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