Comparison of cluster methods agglomerative hierarchical in sustainability indicators in municipalities of Pará state (Research, Society and Development, 2020)
This study aimed to compare the performance of hierarchical agglomerative clustering methods using a data set composed of several sustainability indicators referring to the municipalities of the state of Pará. As well as determining the number of initial groups to be formed by applying of validity indexes. For the selection of indicators, a check-list of national, regional and local scientific studies addressing the theme of sustainability was carried out. Subsequently, the indicators were standardized due to the units and scales of different measures, not interfering in the result and having similar weights in the calculation of the coefficient of similarity. The measure of dissimilarity used was the Euclidean distance, and to determine the hierarchical grouping method was used the agglomerative coefficient (AC). Validation indexes were used to establish the initial grouping number. The agglomerative method with the best performance regarding the (AL) was Ward with 0.94, indicating a better strength and quality among the agglomerative techniques. The Davies Bouldin (DB), Dunn (D) and Silhouette (SIL) validation indexes indicated that the ideal amount of initial clusters to be formed is 2, however the PBM index found that the ideal formation is with 4 groups. Regarding the municipalities with greater homogeneity, it was found that in the composition with 2 groups, the most similar observations were m105 (Salinópolis) and m109 (Santa Izabel do Pará), followed by the observations m102 (Rio Maria) and m144 (Xinguara), all inserted in group 1.