Abstract
The main idea of case-based inference is to exploit the information provided by the similarity structure of a problem 〈∑, s 0 〉 in order to improve the prediction of an unknown outcome r 0 = ϕ(s 0 ).
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© 2007 Springer
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Hüllermeier, E. (2007). Probabilistic Modeling of Case-Based Inference. In: Case-Based Approximate Reasoning. Theory and Decision Library, vol 44. Springer, Dordrecht. https://doi.org/10.1007/1-4020-5695-8_4
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DOI: https://doi.org/10.1007/1-4020-5695-8_4
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-5694-9
Online ISBN: 978-1-4020-5695-6
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