Abstract
The problem of inducing a concept from a given set of examples has been studied extensively in machine learning during the recent years. In this context, it is usually assumed that concepts are precisely defined, which means that an object either belongs to a concept or not. This assumption is obviously over-simplistic. In fact, most real-world concepts have fuzzy rather than sharp boundaries, an observation that motivates the development of methods for fuzzy concept learning. In this paper, we introduce generic algorithms for inducing fuzzy concepts within the framework of version space learning.
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References
K. Cao-Van and B. De Baets. Impurity measures in ranking problems. Technical report, Ghent University, Beligium, 2001.
E. Frank and M. Hall. A simple approach to ordinal classification. In Proc. ECML-2001, 12th European Conference on Machine Learning, pages 145–156, Freiburg, Germany, 2001.
R. Herbrich, T. Graepel, and K. Obermayer. Regression models for ordinal data: A machine learning approach. Technical Report TR 99-3, Department of Computer Science, Technical University of Berlin, Berlin, Germany, 1999.
S. Kramer, G. Widmer, B. Pfahringer, and M. De Groeve. Prediction of ordinal classes using regression trees. Fundamenat Informaticae, 34:1–15, 2000.
P. McCullagh and J.A. Nelder. Generalized Linear Models. Chapman & Hall, London, 1983.
T.M. Mitchell. Version spaces: An approach to concept learning. PhD thesis, Electrical Engineering Department, Stanford University, Stanford, CA, 1979.
A.L. Ralescu and J.F. Baldwin. Concept learning from examples and counter examples. International Journal of Man-Machine Studies, 30(3):329–354, 1989.
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Hüllermeier, E. (2003). Inducing Fuzzy Concepts through Extended Version Space Learning. In: Bilgiç, T., De Baets, B., Kaynak, O. (eds) Fuzzy Sets and Systems — IFSA 2003. IFSA 2003. Lecture Notes in Computer Science, vol 2715. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44967-1_81
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DOI: https://doi.org/10.1007/3-540-44967-1_81
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