Comparison between similarity coefficients with application in forest sciences
DOI:
https://doi.org/10.33448/rsd-v11i2.26046Keywords:
Clustering analysis; (Dis)similarity coefficient; Validation.Abstract
The multivariate statistic has been used in divergence studies concerning plants species. Analysis of the similarity or distance among individuals is an important tool for population. This among aims to present the main show the main coefficients of similarity and dissimilarity and their properties and the importance of axioms for the complement of similarity for the methods in cluster analysis. We evaluated the changes caused by five different similarity coefficients in the group of 11 plots and 17 species. We tested the coefficients of Jaccard, Sorensen-Dice, Simple Agreement, Russel e Rao e Rogers e Tanimoto comparisons being made between them by cophenetic correlations, Rand, adjusted Rand and stress between the distances obtained by the addition of these coefficients, and also by means of dendrograms (visual inspection), projection efficiency in a two-dimensional space and groups formed by the method of average linkage. The results showed that the use of different similarity coefficients caused few changes in the grouping of installments in groups, and the validation obtained between similar plots. Even though few changes in the structure of most different groups, these coefficients changed some relationships between plots with high similarity.
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Copyright (c) 2022 Mácio Augusto de Albuquerque; Emanuela Rodrigues do Nascimento; Kleber Napoleão Nunes de Oliveira Barros; Patrícia Silva Nascimento Barros
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