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A hypothesis test for comparing two partitions obtained from the same dataset

Author

Listed:
  • Mathias Bourel

    (IMERL - Instituto de Matemática y Estadística Rafael Laguardia [Montevideo] - UDELAR - Universidad de la República [Montevideo])

  • Badih Ghattas

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Meliza González

    (Universita de la Republica)

Abstract

We propose a non parametric hypothesis test to compare two partitions of a same data set. The partitions may result from two different clustering approaches. The test may be done using any comparison index but we focus in particular on the Matching Error (ME) that is related to the misclassification error in supervised learning. Some properties of the ME and, especially, its distribution function for the case of two different partitions are analyzed. Extensive simulations and experiments show the efficiency of the test.

Suggested Citation

  • Mathias Bourel & Badih Ghattas & Meliza González, 2025. "A hypothesis test for comparing two partitions obtained from the same dataset," Post-Print hal-05072705, HAL.
    • Handle: RePEc:hal:journl:hal-05072705
    DOI: 10.1080/03610918.2025.2458574
    as

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