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Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 107))

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Summary

A method for clustering adapted to the processing of large data arrays is given; this has been made possible by the economy of memory space. It is shown that one gets the same set of solutions either by the method described here or by the Dynamic Clusters Method. Some variants are given along with the criterion they optimize.

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Bibliography

  1. Beale (1969) “Euclidean cluster analysis” Bull. I.S.E., 43 Book 2, pp. 92–94 (London).

    Google Scholar 

  2. Benzecri J.P. (1973) “Taxonomie — L’analyse des Données” (Dunod).

    Google Scholar 

  3. Benzecri J.P. (1969) “Construction ascendante d’une classification hiérarchique” (L.S.M. I.S.U.P.).

    Google Scholar 

  4. Benzecri J.P. (1970) “Algorithmes rapides d’agrégation” (Sup. Class.) (L.S.M. I.S.U.P.)

    Google Scholar 

  5. Brianne J.P. (1972) “L’algorithme d’échange”. Thèse de 3° cycle (L.S.M. I.S.U.P.)

    Google Scholar 

  6. Cormack R.M. (1971) “A review of classification”. The journal of the Royal Statistical Society serie A vol. 134, Part 3.

    Google Scholar 

  7. Diday E. (1971) “Une nouvelle méthode en classification automatique et reconnaissance des formes: la méthode des nuées dynamiques”. Revue de statistique appliquée. Vol. XIX n° 2.

    Google Scholar 

  8. Diday E. (1972) “Optimisation en classification automatique et reconnaissance des formes” RAIRO vol. 3,p. 61 à

    MathSciNet  Google Scholar 

  9. Diday E. (1972) “Optimisation en classification automatique et reconnaissance des formes” RAIRO vol. 3,p. 96.

    Google Scholar 

  10. Diday E. (1973) “Introduction à l’analyse factorielle typologique”. Rapport Laboria n° 27 (IRIA Rocquencourt (78)).

    Google Scholar 

  11. Forgey E.W. (1965) “Cluster analysis of multivariate data” ARAS Biometric Society (WNRR) Riverside California USA.

    Google Scholar 

  12. Gower J.C. and Ross G.J.S. (1969) “Minimum spanning trees and single-linkage cluster analysis”. Appl. Stat. 18, 54–64.

    Article  MathSciNet  Google Scholar 

  13. Jardine N and Sibson R. (1971) “Mathematical Taxonomy”. J. Wiley and Sons ltd.

    MATH  Google Scholar 

  14. Jambu M. (1972) “Techniques de classification automatique” Thèse de 3° cycle (L.S.M. I.S.U.P.).

    Google Scholar 

  15. Jancey R.C. (1966) “Multidimensional group analysis” Aust. J. Bot. vol 14 p. 127.

    Article  Google Scholar 

  16. Lerman I.C. (1970) “Les bases de la classification automatique” Gauthiers Villars.

    MATH  Google Scholar 

  17. Hall & Ball (1967) “A clustering techniques for summerizing multivariate data “. Behavioral Science vol. 12 n° 2.

    Google Scholar 

  18. Northouse R.A., From F.R. (1973) “Some results of Non-parametric clustering on large Date Problems”. Proc. of the First Int. Joint Conf. on Pattern recognition.

    Google Scholar 

  19. McQueen J. (1967) “Some methods for classification and analysis of multivariable observations”. 5th. Berkeley Symposium on Mathematical statistics and Probability vol. 1 n° 1 pp. 281–297.

    Google Scholar 

  20. Roux M. (1968) “Un algorithme pour construire une hiérarchie particulière”. Thèse de 3° cycle (L.S.M. I.S.U.P.).

    Google Scholar 

  21. Thorndike R.L. (1953) “Who belongs in the family ?” Psychometrika, vol. 18 pp. 267–276.

    Article  Google Scholar 

  22. Zahn C.T. (1971) “Graph theoretical methods for detecting and describing gestalt clusters” I.E.E.E. Trans, and Comp. Vol C 20 n° 1.

    Google Scholar 

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© 1975 Springer-Verlag Berlin · Heidelberg

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Diday, E. (1975). Automatic Sequential Clustering of Large Tables. In: Bensoussan, A., Lions, J.L. (eds) Control Theory, Numerical Methods and Computer Systems Modelling. Lecture Notes in Economics and Mathematical Systems, vol 107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46317-4_50

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  • DOI: https://doi.org/10.1007/978-3-642-46317-4_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-07020-7

  • Online ISBN: 978-3-642-46317-4

  • eBook Packages: Springer Book Archive

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