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We propose a procedure for supervised classification that is based on potential functions. The potential of a class is defined as a kernel density estimate multiplied by the class’s prior probability. The method transforms the data to a potential-potential (pot-pot) plot, where each data point is mapped to a vector of potentials. Separation of the classes, as well as classification of new data ...
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ژورنال
عنوان ژورنال: Statistical Papers
سال: 2016
ISSN: 0932-5026,1613-9798
DOI: 10.1007/s00362-016-0854-8