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

被引：0

作者：

Bourel, Mathias ^{[1
]}

Ghattas, Badih ^{[2
]}

Gonzalez, Meliza ^{[1
]}

机构：

[1] Univ Republica, Inst Matemat & Estadist, Montevideo, Uruguay

[2] Aix Marseille Sch Econ, Marseille, France

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2025年

关键词：

Clustering; Comparing partitions; Hypothesis test; Matching error; CLUSTERINGS; CRITERIA;

D O I：

10.1080/03610918.2025.2458574

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页数：23

共 50 条

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