Abstract
NNS stands for Nonlinear Nonparametric Statistics, henceforth "NNS". What is NNS clustering analysis? NNS clustering is a method of partitioning the joint distribution into partial moment quadrants (clustering), and assigning identifiers to observations (classification). NNS clustering is very similar to k-means clustering, and we direct the reader to Vinod and Viole [1] for a proof and comparison between the methods. This article is intended to present working examples of several classification problems using NNS clustering analysis.We demonstrate how NNS clustering is quite effective, as well as an alternative method NNS employs for classification tasks. We compare predictions of test sets with NNS, k-means using the "cl.predict" routine offered in R to predict class ids or memberships from R objects representing partitions", and K nearest neighbors classification using the "knn" routine in R-package "class".
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