\(k\)-depth-nearest neighbour method and its performance on skew-normal distributons. (English) Zbl 1292.62075

Summary: In the present paper we investigate performance of the \(k\)-depth-nearest classifier. This classifier, proposed recently by Vencálek, uses the concept of data depth to improve the classification method known as the \(k\)-nearest neighbour. Simulation study which is presented here deals with the two-class classification problem in which the considered distributions belong to the family of skewed normal distributions.


62G30 Order statistics; empirical distribution functions
62H30 Classification and discrimination; cluster analysis (statistical aspects)


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