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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.