Abstract
In this study, OWA (Ordered Weighted Averaging) distance based C × K-nearest neighbor algorithm (C × K-NN) is considered. In this approach, from each class, where the number of classes is C, K-nearest neighbors are taken. The distance between the new sample and its K-nearest set is determined based on the OWA operator. It is shown that by adjusting the weights of the OWA operator, it is possible to obtain the results of various clustering strategies like single-linkage, complete-linkage, average-linkage, etc.
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