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Nearest-Neighbor classification was developed to perform discriminant analysis when reliable parametric estimates of probability densities are unknown or difficult to determine. The major disadvantages of NN are its sensitivity to the distance function and using all training instances in the generalization phase. This can cause slow execution speed and high storage requirement when dealing with large data sets. In our past research, an adaptive distance weighted nearest neighbor algorithmdoi:10.1016/j.procs.2011.01.001 fatcat:zy7ctvmrzrbzdlwfjvcbpjegqy