OWA aggregation based CxK-nearest neighbor classification algorithm

A new OWA (Ordered Weighted Averaging) distance based CxK-nearest neighbor algorithm (CxK-NN) is proposed. In this approach, K-nearest neighbors from each of the classes are taken into account instead of the well-known K-nearest neighbor (K-NN) algorithm in which only the total number, K of neighbors are considered. Distance between the classified point and its K-nearest set is determined based on the OWA operator. After experiments with well-known classification datasets, we conclude that average accuracy results of the OWA distance-based CxK-NN algorithm are better than that of K-NN and weighted K-NN algorithms.