A Novel Framework for Spam Hunting by Tracking Concept Drift

Author:

Bindu V.,Thomas Ciza

Publisher

Springer International Publishing

Reference17 articles.

1. Schlimmer, J.C., Granger, R.H.: Incremental learning from noisy data. Mach. Learn. 1(3), 317–354 (1986)

2. Widmer, G., Kubat, M.: Learning in the presence of concept drift and hidden contexts. Mach. Learn. 23(1), 69–101 (1996)

3. Aha, D.W., Kibler, D., Albert, M.K.: Instance-based learning algorithms. Mach. Learn. 6(1), 37–66 (1991)

4. Narendra, K.S., Parthasarathy, K.: Identification and control of dynamical systems using neural networks. IEEE Trans. Neural Netw. 1(1), 4–27 (1990)

5. Harries, M., Horn, K.: Detecting concept drift in financial time series prediction using symbolic machine learning. In: Proceedings of the 8th Australian Joint Conference on Artificial Intelligence (ACAI) (1995)

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