The guiding principle underlying most approaches to similarity-based reasoning (SBR) is the common idea that `similar causes bring about similar effects'. We propose a probabilistic framework of SBR which is based on a formal model of this assumption. This model, called a similarity profile, provides a probabilistic characterization of the similarity relation between observed cases (instances). A probabilistic approach seems reasonable since it adequately captures the heuristic (and hence uncertain) nature of the above hypothesis. Taking the concept of a similarity profile as a point of departure, we develop an inference scheme in which instance-based evidence is represented in the form of belief functions. The combination of evidence derived from individual cases can then be considered as a problem of information fusion. In this connection, we also address the problem of rating individual cases, and of modulating their influence on the prediction which is finally derived.
Hüllermeier, E. (2001). Similarity-based inference as evidential reasoning. International Journal of Approximate Reasoning, 26(2), 67–100. https://doi.org/10.1016/S0888-613X(00)00062-1