- Tytuł:
- A complete gradient clustering algorithm formed with kernel estimators
- Autorzy:
-
Kulczycki, P.
Charytanowicz, M. - Powiązania:
- https://bibliotekanauki.pl/articles/907781.pdf
- Data publikacji:
- 2010
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
analiza danych
eksploracja danych
grupowanie
metoda statystyczna
estymacja jądrowa
obliczenia numeryczne
data analysis
data mining
clustering
gradient procedures
nonparametric statistical methods
kernel estimators
numerical calculations - Opis:
- 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. The proposed algorithm does not demand strict assumptions regarding the desired number of clusters, which allows the obtained number to be better suited to a real data structure. Moreover, a feature specific to it is the possibility to influence the proportion between the number of clusters in areas where data elements are dense as opposed to their sparse regions. Finally, the algorithm-by the detection of one-element clusters-allows identifying atypical elements, which enables their elimination or possible designation to bigger clusters, thus increasing the homogeneity of the data set.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2010, 20, 1; 123-134
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł