Categorical Data Clustering: A Bibliometric Analysis and Taxonomy

Numerous real-world applications apply categorical data clustering to find hidden patterns in the data. The K-modes-based algorithm is a popular algorithm for solving common issues in categorical data, from outlier and noise sensitivity to local optima, utilizing metaheuristic methods. Many studies...

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Bibliographic Details
Published in:	Machine learning and knowledge extraction Vol. 6; no. 2; pp. 1009 - 1054
Main Authors:	Cendana, Maya, Kuo, Ren-Jieh
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.06.2024
Subjects:	Algorithms bibliometric analysis Bibliometrics categorical data clustering Cluster analysis Clustering Comparative analysis Data mining Data processing Heuristic methods K-modes algorithm Methods Noise sensitivity Outliers (statistics) Research design Science Taxonomy taxonomy of clustering algorithm Taiwan
ISSN:	2504-4990, 2504-4990
Online Access:	Get full text
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