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Article detail · 2013

Comparison of hierarchical cluster analysis methods by cophenetic correlation

YÖKSİS OpenAlex Open access · gold SJR Q3 JCR Q1 Citations 357 Top 10% Percentile 98.8% FWCI 10.67
Year
2013
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue Journal of Inequalities and Applications
  • Catalog match (ISSN) Journal of Inequalities and Applications
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

This study proposes the best clustering method(s) for different distance measures under two different conditions using the cophenetic correlation coefficient. In the first one, the data has multivariate standard normal distribution without outliers for and the second one is with outliers (5%) for . The proposed method is applied to simulated multivariate normal data via MATLAB software. According the results of simulation the Average (especially for ) and Centroid (especially for and ) methods are recommended at both conditions. This study hopes to contribute to literature for making better decisions on selection of appropriate cluster methods by using subgroup sizes, variable numbers, subgroup means and variances.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

357 citations

OpenAlex cited_by_count (cache / database)

Authors

  1. SİNAN SARAÇLI BALIKESİR ÜNİVERSİTESİ
  2. İSMET DOĞAN AFYONKARAHİSAR SAĞLIK BİLİMLERİ ÜNİVERSİTESİ
  3. NURHAN DOĞAN AFYONKARAHİSAR SAĞLIK BİLİMLERİ ÜNİVERSİTESİ