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Table 3 The assessment of the cluster dissimilarities

From: The discrimination of interaural level difference sensitivity functions: development of a taxonomic data template for modelling

Cophenetic correlation Linkage algorithms
Coefficients (CCC) Single Average Complete Ward
Pairwise - distance algorithms
Euclidian   0.69391 0.77691 0.6625 0.57017
Seuclidian   0.75833 0.80679 0.64322 0.48974
Minkowski   0.69391 0.77691 0.6625 0.57017
Mahalanobis   0.75833 0.80679 0.64322 0.48974
Cityblock   0.72678 0.79032 0.57675 0.54419
Cosine   0.34928 0.81656 0.73456 0.83168
  1. CCC measures the cluster dissimilarities. The most suitable algorithms produce the coefficient which is closer to one “1”. In this case, Ward linkage and Cosine pairwise-distance algorithms generate a coefficient (0.83168) that is the closest to one ‘1’ among other coefficients.