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Comparing clusterings--an information based distance

Citations

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Cited by:

  1. Elena Farahbakhsh Touli & Hoang Nguyen & Olha Bodnar, 2022. "Monitoring the Dynamic Networks of Stock Returns," Papers 2210.16679, arXiv.org.
  2. Wang, Chao & Du, Yuyan & Li, Hailong & Wallin, Fredrik & Min, Geyong, 2019. "New methods for clustering district heating users based on consumption patterns," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  3. Calomiris, Charles W. & Mamaysky, Harry, 2019. "How news and its context drive risk and returns around the world," Journal of Financial Economics, Elsevier, vol. 133(2), pages 299-336.
  4. Piccardi, Carlo & Calatroni, Lisa & Bertoni, Fabio, 2010. "Communities in Italian corporate networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5247-5258.
  5. Huaylla, Claudia A. & Kuperman, Marcelo N. & Garibaldi, Lucas A., 2024. "Comparison of two statistical measures of complexity applied to ecological bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 642(C).
  6. Francisco J. Valverde-Albacete & Carmen Peláez-Moreno, 2024. "A Formalization of Multilabel Classification in Terms of Lattice Theory and Information Theory: Concerning Datasets," Mathematics, MDPI, vol. 12(2), pages 1-31, January.
  7. Assaf Almog & Ferry Besamusca & Mel MacMahon & Diego Garlaschelli, 2015. "Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-16, July.
  8. Stefano Tonellato, 2019. "Bayesian nonparametric clustering as a community detection problem," Working Papers 2019: 20, Department of Economics, University of Venice "Ca' Foscari".
  9. Juan Lucio & Raúl Mínguez & Asier Minondo & Francisco Requena, 2016. "Networks and the Dynamics of Firms' Export Portfolio: Evidence for Mexico," The World Economy, Wiley Blackwell, vol. 39(5), pages 708-736, May.
  10. David Samu & Anil K Seth & Thomas Nowotny, 2014. "Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity," PLOS Computational Biology, Public Library of Science, vol. 10(4), pages 1-24, April.
  11. Luciana Crosilla & Marco Malgarini, 2011. "Behavioural models for manufacturing firms: analysing survey data," ECONOMIA E POLITICA INDUSTRIALE, FrancoAngeli Editore, vol. 2011(4), pages 139-163.
  12. Christian Hennig, 2022. "An empirical comparison and characterisation of nine popular clustering methods," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(1), pages 201-229, March.
  13. Julian Maluck & Reik V Donner, 2015. "A Network of Networks Perspective on Global Trade," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-24, July.
  14. Lovro Šubelj & Nees Jan van Eck & Ludo Waltman, 2016. "Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-23, April.
  15. Daniel Straulino & Mattie Landman & Neave O'Clery, 2020. "A bi-directional approach to comparing the modular structure of networks," Papers 2010.06568, arXiv.org.
  16. Yu, Jiating & Leng, Jiacheng & Sun, Duanchen & Wu, Ling-Yun, 2023. "Network Refinement: Denoising complex networks for better community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
  17. Lou, Hao & Li, Shenghong & Zhao, Yuxin, 2013. "Detecting community structure using label propagation with weighted coherent neighborhood propinquity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(14), pages 3095-3105.
  18. Alessandro Chessa & Pierpaolo D’Urso & Livia Giovanni & Vincenzina Vitale & Alfonso Gebbia, 2023. "Complex networks for community detection of basketball players," Annals of Operations Research, Springer, vol. 325(1), pages 363-389, June.
  19. Ekaterina Kovaleva & Boris Mirkin, 2015. "Bisecting K-Means and 1D Projection Divisive Clustering: A Unified Framework and Experimental Comparison," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 414-442, October.
  20. Zema, Sebastiano Michele, 2022. "Uncovering the network structure of non-centrally cleared derivative markets: evidences from regulatory data," Working Paper Series 2721, European Central Bank.
  21. Francisco de A. T. Carvalho & Antonio Irpino & Rosanna Verde & Antonio Balzanella, 2022. "Batch Self-Organizing Maps for Distributional Data with an Automatic Weighting of Variables and Components," Journal of Classification, Springer;The Classification Society, vol. 39(2), pages 343-375, July.
  22. Efstratios K Kosmidis & Vasiliki Moschou & Georgios Ziogas & Ioannis Boukovinas & Maria Albani & Nikolaos A Laskaris, 2014. "Functional Aspects of the EGF-Induced MAP Kinase Cascade: A Complex Self-Organizing System Approach," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-12, November.
  23. Isabella Morlini & Sergio Zani, 2012. "Dissimilarity and similarity measures for comparing dendrograms and their applications," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(2), pages 85-105, July.
  24. Neave O'Clery & Samuel Heroy & Francois Hulot & Mariano Beguerisse-D'iaz, 2019. "Unravelling the forces underlying urban industrial agglomeration," Papers 1903.09279, arXiv.org, revised Jun 2019.
  25. Claudio Conversano & Massimo Cannas & Francesco Mola & Emiliano Sironi, 2019. "Random effects clustering in multilevel modeling: choosing a proper partition," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(1), pages 279-301, March.
  26. Luisa Cutillo & Annamaria Carissimo & Silvia Figini, 2012. "Network Selection: A Method for Ranked Lists Selection," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-13, August.
  27. Alan Lee & Bobby Willcox, 2014. "Minkowski Generalizations of Ward’s Method in Hierarchical Clustering," Journal of Classification, Springer;The Classification Society, vol. 31(2), pages 194-218, July.
  28. Assaf Almog & Ferry Besamusca & Mel MacMahon & Diego Garlaschelli, 2015. "Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations," Papers 1504.00590, arXiv.org.
  29. Damien A Fair & Alexander L Cohen & Jonathan D Power & Nico U F Dosenbach & Jessica A Church & Francis M Miezin & Bradley L Schlaggar & Steven E Petersen, 2009. "Functional Brain Networks Develop from a “Local to Distributed” Organization," PLOS Computational Biology, Public Library of Science, vol. 5(5), pages 1-14, May.
  30. Federico Botta & Charo I del Genio, 2017. "Analysis of the communities of an urban mobile phone network," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-14, March.
  31. Kemmawadee Preedalikit & Daniel Fernández & Ivy Liu & Louise McMillan & Marta Nai Ruscone & Roy Costilla, 2024. "Row mixture-based clustering with covariates for ordinal responses," Computational Statistics, Springer, vol. 39(5), pages 2511-2555, July.
  32. O’Hagan, Adrian & Murphy, Thomas Brendan & Gormley, Isobel Claire & McNicholas, Paul D. & Karlis, Dimitris, 2016. "Clustering with the multivariate normal inverse Gaussian distribution," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 18-30.
  33. Miloš Gligorić & Zoran Gligorić & Čedomir Beljić & Slavko Torbica & Svetlana Štrbac Savić & Jasmina Nedeljković Ostojić, 2016. "Multi-Attribute Technological Modeling of Coal Deposits Based on the Fuzzy TOPSIS and C-Mean Clustering Algorithms," Energies, MDPI, vol. 9(12), pages 1-23, December.
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