Ordination-based verification of feature selection in pattern evolution research

Article type: Research Article

Authors: Hosszú, Gábor

Affiliations: Department of Electron Devices, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, H-1111 Budapest, Hungary | Tel.: +36 1 4632724; Fax: +36 1 4632973; E-mail: hosszu.gabor@vik.bme.hu

Correspondence: [*] Corresponding author: Department of Electron Devices, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, H-1111 Budapest, Hungary. Tel.: +36 1 4632724; Fax: +36 1 4632973; E-mail: hosszu.gabor@vik.bme.hu. https://orcid.org/0000-0002-2856-9552.

Abstract: This article explains the idea of pattern systems that develop gradually. These systems involve symbolic communication that includes symbols, syntax, and layout rules. Some pattern systems change over time, like historical scripts. The scientific study of pattern systems is called pattern evolution research, and scriptinformatics is concerned with the modelling of the evolution of scripts. The symbol series consists of symbols from a pattern system, while the graph sequence is a symbol sequence applied with a specific technology. This article describes a method for examining tested pattern systems to confirm their classification, which focuses on more ancient features. The method’s effectiveness was tested on Rovash scripts and graph sequences. Multivariate analysis was carried out by using PAST4 software, employing principal coordinates analysis ordination and k-means clustering algorithms.

Keywords: Feature selection, k-means, machine learning, principal coordinates analysis, scriptinformatics

DOI: 10.3233/IDA-230326

Journal: Intelligent Data Analysis, vol. 28, no. 4, pp. 891-907, 2024