Weighted k-Nearest-Neighbor Techniques and Ordinal Classification

Hechenbichler, K. and Schliep, K. (2004): Weighted k-Nearest-Neighbor Techniques and Ordinal Classification. Collaborative Research Center 386, Discussion Paper 399

Abstract

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.

• Item Type: Paper
• Faculties: Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386; Special Research Fields > Special Research Field 386
• Subjects: 500 Science > 510 Mathematics
• Language: English