A complete gradient clustering algorithm formed with kernel estimators - Kulczycki, Piotr; Charytanowicz, Małgorzata (Zielona Góra: Uniwersytet Zielonogórski)
The aim of this paper is to provide a gradient clustering algorithm in its complete form, suitable for direct use without requiring a deeper statistical knowledge. The values of all parameters are effectively calculated using optimizing procedures. Moreover, an illustrative analysis of the meaning of particular parameters is shown, followed by the effects resulting from possible modifications with respect to their primarily assigned optimal values.
Keywords: data analysis and mining; clustering; gradient procedures; nonparametric statistical methods; kernel estimators; numerical calculations