Abstract
A simple manipulation of the Euclidian distance expression permits to obtain a scaled dissimilarity index measure, varying within a range of values lying in the interval [0,1]. Here is presented the theoretical background, its application to quantum similarity and use for artificial intelligence general purposes as well. The origin of Hodgkin-Richards index is analyzed and compared with quantum similarity Carbó index.
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Carbó-Dorca, R. Scaled Euclidian distances: a general dissimilarity index with a suitably defined geometrical foundation. J Math Chem 50, 734–740 (2012). https://doi.org/10.1007/s10910-011-9920-6
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DOI: https://doi.org/10.1007/s10910-011-9920-6