New Approach to Clustering Random Attributes

Autor:	Zenon Gniazdowski
Jazyk:	English<br />Polish
Rok vydání:	2024
Předmět:	numerical attributes nominal attributes numerical encoding similarity of random attributes clustering of random attributes factor analysis Electronic computers. Computer science QA75.5-76.95
Zdroj:	Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki, Vol 18, Iss 31, Pp 41-90 (2024)
Druh dokumentu:	article
ISSN:	1896-396X 2082-8349
DOI:	10.26348/znwwsi.31.41
Popis:	This paper proposes a new method for similarity analysis and, consequently, a new algorithm for clustering different types of random attributes, both numerical and nominal. However, in order for nominal attributes to be clustered, their values must be properly encoded. In the encoding process, nominal attributes obtain a new representation in numerical form. Only the numeric attributes can be subjected to factor analysis, which allows them to be clustered in terms of their similarity to factors. The proposed method was tested for several sample datasets. It was found that the proposed method is universal. On the one hand, the method allows clustering of numerical attributes. On the other hand, it provides the ability to cluster nominal attributes. It also allows simultaneous clustering of numerical attributes and numerically encoded nominal attributes.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/b0fca5f95b754d3180d6f38298d9b329 Zobrazit plný text záznamu View record in DOAJ