A new C × k - Nearest neighbor linkage approach to the classification problem

A new C × k nearest neighbor algorithm with a new point of view is proposed. In this algorithm K neighbors from each of the classes are taken into account instead of the well-known K neighbor algorithm in which only the total number of neighbors are considered. After experiments with well-known classification datasets, we conclude that K-NN, weighted K-NN, and average linkage neighbors results are between the single-linkage and complete-linkage algorithms. After the evaluation of the average accuracy results, we realized that the best results are obtained for the values of K between 1 and 10. On the other hand, it is determined that using single-linkage strategy provides high values of the results at most of the times