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Cluster differences scaling with a within-clusters loss component and a fuzzy successive approximation strategy to avoid local minima

Citations

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Cited by:

  1. van Rosmalen, J.M. & Groenen, P.J.F. & Trejos, J. & Castilli, W., 2005. "Global Optimization strategies for two-mode clustering," Econometric Institute Research Papers EI 2005-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Vichi, Maurizio & Saporta, Gilbert, 2009. "Clustering and disjoint principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3194-3208, June.
  3. J. Fernando Vera & Rodrigo Macías, 2021. "On the Behaviour of K-Means Clustering of a Dissimilarity Matrix by Means of Full Multidimensional Scaling," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 489-513, June.
  4. Elizabeth Ann Maharaj & Pierpaolo D’Urso & Don Galagedera, 2010. "Wavelet-based Fuzzy Clustering of Time Series," Journal of Classification, Springer;The Classification Society, vol. 27(2), pages 231-275, September.
  5. Renato Coppi & Pierpaolo D’Urso & Paolo Giordani, 2010. "A Fuzzy Clustering Model for Multivariate Spatial Time Series," Journal of Classification, Springer;The Classification Society, vol. 27(1), pages 54-88, March.
  6. Renato Coppi & Pierpaolo D'Urso, 2002. "Fuzzy K-means clustering models for triangular fuzzy time trajectories," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(1), pages 21-40, February.
  7. Van Mechelen, Iven & Schepers, Jan, 2007. "A unifying model involving a categorical and/or dimensional reduction for multimode data," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 537-549, September.
  8. Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari, 2015. "Trimmed fuzzy clustering for interval-valued data," 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. 9(1), pages 21-40, March.
  9. Patrick Groenen & Willem Heiser, 1996. "The tunneling method for global optimization in multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 529-550, September.
  10. DeSarbo, Wayne S. & Selin Atalay, A. & Blanchard, Simon J., 2009. "A three-way clusterwise multidimensional unfolding procedure for the spatial representation of context dependent preferences," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3217-3230, June.
  11. Joost Rosmalen & Patrick Groenen & Javier Trejos & William Castillo, 2009. "Optimization Strategies for Two-Mode Partitioning," Journal of Classification, Springer;The Classification Society, vol. 26(2), pages 155-181, August.
  12. Heungsun Hwang & Wayne Desarbo & Yoshio Takane, 2007. "Fuzzy Clusterwise Generalized Structured Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 181-198, June.
  13. J. Vera & Rodrigo Macías & Willem Heiser, 2013. "Cluster Differences Unfolding for Two-Way Two-Mode Preference Rating Data," Journal of Classification, Springer;The Classification Society, vol. 30(3), pages 370-396, October.
  14. Pierpaolo D’Urso & Leonardo Salvatore Alaimo & Livia Giovanni & Riccardo Massari, 2022. "Well-Being in the Italian Regions Over Time," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 599-627, June.
  15. Vera, J. Fernando & Macas, Rodrigo & Heiser, Willem J., 2009. "A dual latent class unfolding model for two-way two-mode preference rating data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3231-3244, June.
  16. Tianyu Tan & Hye Suk & Heungsun Hwang & Jooseop Lim, 2013. "Functional fuzzy clusterwise regression analysis," 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. 7(1), pages 57-82, March.
  17. Pierpaolo D’Urso & Livia De Giovanni & Riccardo Massari & Francesca G. M. Sica, 2019. "Cross Sectional and Longitudinal Fuzzy Clustering of the NUTS and Positioning of the Italian Regions with Respect to the Regional Competitiveness Index (RCI) Indicators with Contiguity Constraints," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(3), pages 609-650, December.
  18. B. Lafuente-Rego & P. D’Urso & J. A. Vilar, 2020. "Robust fuzzy clustering based on quantile autocovariances," Statistical Papers, Springer, vol. 61(6), pages 2393-2448, December.
  19. C Mar-Molinero & J Mingers, 2007. "An evaluation of the limitations of, and alternatives to, the Co-Plot methodology," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(7), pages 874-886, July.
  20. Frank Busing & Mark Rooij, 2009. "Unfolding Incomplete Data: Guidelines for Unfolding Row-Conditional Rank Order Data with Random Missings," Journal of Classification, Springer;The Classification Society, vol. 26(3), pages 329-360, December.
  21. Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari & Dario Lallo, 2013. "Noise fuzzy clustering of time series by autoregressive metric," METRON, Springer;Sapienza Università di Roma, vol. 71(3), pages 217-243, November.
  22. D’Urso, Pierpaolo & Manca, Germana & Waters, Nigel & Girone, Stefania, 2019. "Visualizing regional clusters of Sardinia's EU supported agriculture: A Spatial Fuzzy Partitioning Around Medoids," Land Use Policy, Elsevier, vol. 83(C), pages 571-580.
  23. Coppi, Renato & D'Urso, Pierpaolo, 2003. "Three-way fuzzy clustering models for LR fuzzy time trajectories," Computational Statistics & Data Analysis, Elsevier, vol. 43(2), pages 149-177, June.
  24. Pierpaolo D'Urso & Girish Prayag & Marta Disegna & Riccardo Massari, 2013. "Market Segmentation using Bagged Fuzzy C–Means (BFCM): Destination Image of Western Europe among Chinese Travellers," BEMPS - Bozen Economics & Management Paper Series BEMPS13, Faculty of Economics and Management at the Free University of Bozen.
  25. J. Vera & Rodrigo Macías & Willem Heiser, 2009. "A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data," Psychometrika, Springer;The Psychometric Society, vol. 74(2), pages 297-315, June.
  26. Paolo Giordani & Henk Kiers, 2012. "FINDCLUS: Fuzzy INdividual Differences CLUStering," Journal of Classification, Springer;The Classification Society, vol. 29(2), pages 170-198, July.
  27. J. Fernando Vera & Rodrigo Macías, 2017. "Variance-Based Cluster Selection Criteria in a K-Means Framework for One-Mode Dissimilarity Data," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 275-294, June.
  28. Roberto Rocci & Maurizio Vichi, 2005. "Three-Mode Component Analysis with Crisp or Fuzzy Partition of Units," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 715-736, December.
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