- Tytuł:
- A novel grid-based clustering algorithm
- Autorzy:
-
Starczewski, Artur
Scherer, Magdalena M.
Książek, Wojciech
Dębski, Maciej
Wang, Lipo - Powiązania:
- https://bibliotekanauki.pl/articles/2031101.pdf
- Data publikacji:
- 2021
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
data mining
grid-based clustering
grid structure - Opis:
- Data clustering is an important method used to discover naturally occurring structures in datasets. One of the most popular approaches is the grid-based concept of clustering algorithms. This kind of method is characterized by a fast processing time and it can also discover clusters of arbitrary shapes in datasets. These properties allow these methods to be used in many different applications. Researchers have created many versions of the clustering method using the grid-based approach. However, the key issue is the right choice of the number of grid cells. This paper proposes a novel grid-based algorithm which uses a method for an automatic determining of the number of grid cells. This method is based on the kdist function which computes the distance between each element of a dataset and its kth nearest neighbor. Experimental results have been obtained for several different datasets and they confirm a very good performance of the newly proposed method.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 4; 319-330
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki