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Table 1 CPCC analysis for 26 districts of Gujarat for different distance metric

From: Analysis of hourly road accident counts using hierarchical clustering and cophenetic correlation coefficient (CPCC)

 Distance metric

Cophenetic correlation coefficient (CPCC)

Single

Complete

Average

Ward

Weighted

Median

Centroid

Euclidean

0.784227

0.791608

0.826298

0.63921

0.760709

0.739566

0.812102

Cityblock

0.795472

0.720603

0.822869

0.617237

0.814186

0.757599

0.800933

Minkowski

0.784227

0.791608

0.826298

0.63921

0.760709

0.739566

0.812102

Chebychev

0.747701

0.621421

0.78132

0.620067

0.756454

0.684826

0.730986

Cosine

0.73324

0.73852

0.779876

0.63823

0.692975

0.70216

0.760326

Correlation

0.733247

0.738506

0.779844

0.638203

0.692964

0.702147

0.760308

Spearman

0.750498

0.528649

0.773012

0.576422

0.725262

0.742434

0.757063

  1. Italic symbol shows the highest CPCC values for average version for AGNES algorithm with Euclidean and Minkowski distance metric