Local search genetic algorithm-based possibilistic weighted fuzzy c-means for clustering mixed numerical and categorical data

Clustering for mixed numerical and categorical attributes has attracted many researchers due to its necessity in many real-world applications. One crucial issue concerned in clustering mixed data is to select an appropriate distance metric for each attribute type. Besides, some current clustering me...

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Veröffentlicht in:	Neural computing & applications Jg. 34; H. 20; S. 18059 - 18074
Hauptverfasser:	Nguyen, Thi Phuong Quyen, Kuo, R. J., Le, Minh Duc, Nguyen, Thi Cuc, Le, Thi Huynh Anh
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.10.2022 Springer Nature B.V
Schlagworte:	Artificial Intelligence Centroids Clustering Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Datasets Genetic algorithms Image Processing and Computer Vision Machine learning Original Article Probability and Statistics in Computer Science Searching Local search genetic algorithm Possibilistic fuzzy means Variable neighborhood search Mixed data
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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