DBSCAN-like clustering method for various data densities

• Published in: Pattern analysis and applications : PAA Vol. 23; no. 2; pp. 541 - 554
• Main Authors: Scitovski, Rudolf, Sabo, Kristian
• Format: Journal Article
• Language: English
• Published: London Springer London 01.05.2020; Springer Nature B.V
• Subjects: Algorithms; Clustering; Computer Science; Data points; Parameters; Partitions; Pattern Recognition; Theoretical Advances; Incremental algorithm; Various data densities; Clusters merging; DBSCAN; Least Squares distance-like function; Clustering

In this paper, we propose a modification of the well-known DBSCAN algorithm, which recognizes clusters with various data densities in a given set of data points A = { a i ∈ R n : i = 1 , ⋯ , m } . First, we define the parameter M i n P t s = ⌊ ln | A | ⌋ and after that, by using a standard procedure...