2016
DOI: 10.7868/s0320965216020169
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Методы Сравнительной Оценки Результатов Кластерного Анализа Структуры Гидробиоценозов (На Примере Зоопланктона Реки Линда Нижегородской Области)

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“…Indicators of the sum of squares of distances between points within the cluster and the average width of the silhouette [24,25] allow us to assess the quality of clustering. For the sum of squared distances, the "elbow bend" method is used [22,26] to determine the optimal number of clusters, and the local maximum of the silhouette width value allows you to select the number of clusters with the best separation. Thus, the optimal number of partitioning groups -clusters is five for the agglomerative and eight for the divisional clustering algorithm (Figure 5).…”
Section: Economic Effectmentioning
confidence: 99%
“…Indicators of the sum of squares of distances between points within the cluster and the average width of the silhouette [24,25] allow us to assess the quality of clustering. For the sum of squared distances, the "elbow bend" method is used [22,26] to determine the optimal number of clusters, and the local maximum of the silhouette width value allows you to select the number of clusters with the best separation. Thus, the optimal number of partitioning groups -clusters is five for the agglomerative and eight for the divisional clustering algorithm (Figure 5).…”
Section: Economic Effectmentioning
confidence: 99%