Weighted k-Nearest-Neighbor Techniques and Ordinal Classification

In the field of statistical discrimination k-nearest neighbor
classification is a well-known, easy and successful method. In this
paper we present an extended version of this technique, where the
distances of the nearest neighbors can be taken into account. In
this sense there is a close connection to LOESS, a local regression
technique. In addition we show possibilities to use nearest
neighbor for classification in the case of an ordinal class
structure. Empirical studies show the advantages of the new
techniques.