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Publicação
Affinity coefficient vs. Euclidean distance in hierarchical clustering of patients with alcohol use disorder
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Orientador(es)
Resumo(s)
Hierarchical cluster analysis is applied to longitudinal neuropsychological and quality of life data from 67 patients with alcohol use disorder, comparing the affnity coefcient with the Euclidean distance on raw and diference score profles. Partition quality and agreement between methods are assessed using the STAT coefcient, tanglegram and Adjusted Rand Index.
Descrição
Palavras-chave
Affinity coeffcient Hierarchical clustering Complete linkage Alcohol use disorder Neuropsychological rehabilitation Longitudinal profiles Real-valued data
Contexto Educativo
Citação
Bacelar-Nicolau, L., Sousa, Á., Ferreira, S., Ribeiro, C., Nascimento, A. P., & Bacelar-Nicolau, H. (2026). Affinity coefficient vs. Euclidean distance in hierarchical clustering of patients with alcohol use disorder. Book of abstracts of the X Workshop on Computational Data Analysis and Numerical Methods, 55–56. https://w3.math.uminho.pt/WCDANM2026/img/Book.pdf
Editora
Universidade do Minho. CMAT - Centro de Matemática
Licença CC
Sem licença CC