Learning under Concept Drift with Support Vector Machines

Author:

Ayad Omar

Publisher

Springer International Publishing

Reference8 articles.

1. Ripley, B.D.: Pattern Recognition and Neural Networks. Cambridge University Press, Cambridge (1996)

2. Cha, S.H.: Comprehensive survey on distance/similarity measures between probability density functions. International Journal of Mathematical Models and Methods in Applied Sciences 4, 300–307 (2007)

3. Medasani, S., Zliobaite, K., Kuncheva, L.I.: Theoretical window size for classification in the presence of sudden concept drift. Technical Report # BCS-TR-001-2010. Bangor University, UK (2010)

4. Lecture Notes in Computer Science;P. Sobhani,2011

5. Rutkowski, L.: Adaptive probabilistic neural networks for pattern classification in time-varying environment. IEEE Transactions on Neural Networks 15(4), 811–827 (2004)

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