Mann, T. 1993.Library research models: A guide to classification, cataloging, and com-
puters. New York: Oxford University Press.
Marill, T., and D. M. Green. 1963. On the effectiveness of receptors in recognition
systems.IEEE Transactions on Information Theory9(11):11–17.Martin, B. 1995. Instance-based learning: Nearest neighbour with generalisation.
MSc Thesis, Department of Computer Science, University of Waikato, New
Zealand.
McCallum, A., and K. Nigam. 1998. A comparison of event models for Naïve
Bayes text classification. In Proceedings of the AAAI-98 Workshop on
Learning for Text Categorization, Madison, WI. Menlo Park, CA: AAAI
Press, pp. 41–48.Mehta, M., R. Agrawal, and J. Rissanen. 1996. SLIQ: A fast scalable classifier for data
mining. In Apers, P., M. Bouzeghoub, and G. Gardarin,Proceedings of the Fifth
International Conference on Extending Database Technology, Avignon, France.
New York: Springer-Verlag.
Melville, P., and R. J. Mooney. 2005. Creating diversity in ensembles using artificial
data.Information Fusion6(1):99–111.Michalski, R. S., and R. L. Chilausky. 1980. Learning by being told and learning from
examples: An experimental comparison of the two methods of knowledge
acquisition in the context of developing an expert system for soybean disease
diagnosis.International Journal of Policy Analysis and Information Systems
4(2).
Michie, D. 1989. Problems of computer-aided concept formation. In J. R. Quinlan,
editor,Applications of expert systems, Vol. 2.Wokingham, England: Addison-
Wesley, pp. 310–333.Minsky, M., and S. Papert. 1969.Perceptrons.Cambridge, MA: MIT Press.
Mitchell, T. M. 1997.Machine learning.New York: McGraw Hill.Mitchell, T. M., R. Caruana, D. Freitag, J. McDermott, and D. Zabowski. 1994.
Experience with a learning personal assistant.Communications of the ACM
37(7):81–91.
Moore, A. W. 1991. Efficient memory-based learning for robot control. PhD
Dissertation, Computer Laboratory, University of Cambridge, UK.———. 2000. The anchors hierarchy: Using the triangle inequality to survive high-
dimensional data. In C. Boutilier and M. Goldszmidt, editors,Proceedings of
the Sixteenth Conference on Uncertainty in Artificial Intelligence, Stanford, CA.
San Francisco: Morgan Kaufmann, pp. 397–405.498 REFERENCES
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