Weighted k-nearest-neighbor techniques and ordinal classification - Klaus Hechenbichler; Klaus Schliep (Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen, 2004)
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 distance 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 technique.
urn:nbn:de:bvb:19-epub-1769-9
Keywords: 519