clusfind

clusfind: A set of six stand-alone Fortran programs for cluster analysis. The programs are described and illustrated in the book ”Finding Groups in Data” by L. Kaufman and P.J. Rousseeuw, New York: John Wiley. Chapter 1: DAISY.FOR (computes dissimilarities); Chapter 2: PAM.FOR (partitions the data set into clusters with a new method using medoids); Chapter 3: CLARA.FOR (for clustering large applications); Chapter 4: FANNY.FOR (a new method for fuzzy clustering); Chapter 5+6 : TWINS.FOR (hierarchical clustering; you can choose between agglomerative and divisive); Chapter 7: MONA.FOR (divisive hierachical clustering of binary data sets.


References in zbMATH (referenced in 438 articles , 1 standard article )

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  1. Gordon, A. D.; Vichi, M.: Fuzzy partition models for fitting a set of partitions (2001)
  2. Van Breedam, Alex: Comparing descent heuristics and metaheuristics for the vehicle routing problem (2001)
  3. Zhou, Aoying; Zhou, Shuigeng; Cao, Jing; Fan, Ye; Hu, Junfa: Approaches for scaling DBSCAN algorithm to large spatial databases (2000)
  4. Augusteijn, M. F.; Steck, U. J.: Supervised adaptive clustering: A hybrid neural network clustering algorithm (1998)
  5. Cuesta-Albertos, J. A.; Gordaliza, A.; Matrán, C.: Trimmed best (k)-nets: A robustified version of an (L_\infty)-based clustering method (1998)
  6. Eom, Sean B.: Relationships between the decision support system subspecialties and reference disciplines: An empirical investigation (1998)
  7. Fan, Jianhua; Li, Deyi: An overview of data mining and knowledge discovery (1998)
  8. Cuesta-Albertos, J. A.; Gordaliza, A.; Matrán, C.: Trimmed (k)-means: An attempt to robustify quantizers (1997)
  9. Galicki, Miroslaw; Moeller, Ulrich; Witte, Herbert: Neural clustering networks based on global optimisation of prototypes in metric spaces. (1997) ioport
  10. Galicki, M.; Möller, U.; Witte, H.: Neural clustering networks based on global optimisation of prototypes in metric spaces. (1997) ioport
  11. Hansen, Pierre; Jaumard, Brigitte: Cluster analysis and mathematical programming (1997)
  12. Maravalle, Maurizio; Simeone, Bruno; Naldini, Rosella: Clustering on trees (1997)
  13. Hansen, Pierre; Jaumard, Brigitte; Simeone, Bruno: Espaliers: A generalization of dendrograms (1996)
  14. Gnanadesikan, R.; Kettenring, J. R.; Tsao, S. L.: Weighting and selection of variables for cluster analysis (1995)
  15. Rousseeuw, P. J.; Trauwaert, E.; Kaufman, L.: Fuzzy clustering with high contrast (1995)
  16. Pintér, János; Pesti, Géza: Set partition by globally optimized cluster seed points (1991)
  17. van den Broeck, Julien; Broeckx, Fernand: Decomposing stochastic frontier efficiency into secular and organisational efficiency (1991)
  18. Kaufman, Leonhard; Rousseeuw, Peter J.: Finding groups in data. An introduction to cluster analysis (1990)

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