Simultaneous Row and Column Partitioning: Evaluation of a Heuristic

  • Gilbert Ritschard
  • Djamel A. Zighed
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2871)

Abstract

This paper is concerned with the determination, in a cross table, of the simultaneous merging of rows and columns that maximizes the association between the row and column variables. We present a heuristic, first introduced in [2], and discuss its reliability. The heuristic reduces drastically the complexity of the exhaustive scanning of all possible groupings. Reliability is assessed by means of a series of simulation runs. The outcomes reported show that though the quasi optima may often miss the true global optima, they provide very close solutions.

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References

  1. 1.
    Olszak, M., Ritschard, G.: The behaviour of nominal and ordinal partial association measures. The Statistician 44, 195–212 (1995)CrossRefGoogle Scholar
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    Ritschard, G., Nicoloyannis, N.: Aggregation and association in cross tables. In: Zighed, D.A., Komorowski, J., Żytkow, J.M. (eds.) PKDD 2000. LNCS (LNAI), vol. 1910, pp. 593–598. Springer, Heidelberg (2000)CrossRefGoogle Scholar
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    Ritschard, G., Zighed, D.A., Nicoloyannis, N.: Maximisation de l’association par regroupement de lignes ou colonnes d’un tableau croisé. Revue Mathématiques Sciences Humaines 39, 81–97 (2001)Google Scholar
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    Zighed, D.A., Rabaseda, S., Rakotomalala, R., Feschet, F.: Discretization methods in supervised learning. Encyclopedia of Computer Science and Technology 40, 35–50 (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Gilbert Ritschard
    • 1
  • Djamel A. Zighed
    • 2
  1. 1.Dept of EconometricsUniversity of GenevaGeneva 4Switzerland
  2. 2.Laboratoire ERICUniversity of Lyon 2Bron CedexFrance

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