A Novel Grid-Based Clustering Algorithm
| Autor: | Wojciech Książek, Lipo Wang, Magdalena Scherer, Maciej Dębski, Artur Starczewski |
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| Přispěvatelé: | School of Electrical and Electronic Engineering |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
computer.software_genre Grid based Artificial Intelligence Hardware and Architecture Modeling and Simulation Electrical and electronic engineering [Engineering] Data Mining Computer Vision and Pattern Recognition Data mining Cluster analysis Grid-Based Clustering computer Information Systems |
| Zdroj: | Journal of Artificial Intelligence and Soft Computing Research. 11:319-330 |
| ISSN: | 2449-6499 |
| DOI: | 10.2478/jaiscr-2021-0019 |
| Popis: | 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. Published version The paper is financed under the program of the Polish Minister of Science and Higher Education under the name ”Regional Initiative of Excellence” in the years 2019-2022; project number 020/RID/2018/19; the amount of financing PLN 12,000,000.00. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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