Abstract
This paper examines the role of prototypicality in exemplarbased concept learning methods. It proposes two approaches to prototypicality: a shared-properties approach, and a similarity-based approach, and suggests measures that implement the different approaches. The proposed measures are tested in a set of experiments. The results of the experiments show that prototypicality serves as a good storing filter in storage reduction algorithms; combining it in algorithms that store all the training set does not improve significantly the accuracy of the algorithm. Finally, prototypicality is a useful notion only in a subset of the domains; a preliminary examination of those domains and their characteristics is proposed.
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Biberman, Y. (1995). The role of prototypicality in exemplar-based learning. In: Lavrac, N., Wrobel, S. (eds) Machine Learning: ECML-95. ECML 1995. Lecture Notes in Computer Science, vol 912. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59286-5_50
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DOI: https://doi.org/10.1007/3-540-59286-5_50
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