Finding the optimal metric in classification problems with ordinal features |
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Authors: | G V Iofina |
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Institution: | (1) Department of Computing, Oxford Brookes University, Oxford, OX33 1HX, UK |
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Abstract: | A method for finding the optimal distance function for the classification problem with two classes in which the objects are
specified by vectors of their ordinal features is proposed. An optimal distance function is sought by the minimization of
the weighted difference of the average intraclass and interclass distances. It is assumed that a specific distance function
is given for each feature, which is defined on the Cartesian product of the set of integer numbers in the range from 0 to
N − 1 and takes values from 0 to M. Distance functions satisfy modified metric properties. The number of admissible distance functions is calculated, which
enables one to significantly reduce the complexity of the problem. To verify the appropriateness of metric optimization and
to perform experiments, the nearest neighbor algorithm is used. |
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Keywords: | |
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