The development of external evaluation criteria for soft clustering (SC) has received limited attention: existing methods do not provide a general approach to extend comparison measures to SC, and are unable to account for the uncertainty represented in the results of SC algorithms. In this article, we propose a general method to address these limitations, grounding on a novel interpretation of SC as distributions over hard clusterings, which we call distributional measures. We provide an in-depth study of complexity- and metric-theoretic properties of the proposed approach, and we describe approximation techniques that can make the calculations tractable. Finally, we illustrate our approach through a simple but illustrative experiment.

Campagner, A., Ciucci, D., Denœux, T. (2022). A Distributional Approach for Soft Clustering Comparison and Evaluation. In 7th International Conference, BELIEF 2022, Paris, France, October 26–28, 2022, Proceedings (pp.3-12). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-17801-6_1].

A Distributional Approach for Soft Clustering Comparison and Evaluation

Campagner, Andrea
Primo
;
Ciucci, Davide;
2022

Abstract

The development of external evaluation criteria for soft clustering (SC) has received limited attention: existing methods do not provide a general approach to extend comparison measures to SC, and are unable to account for the uncertainty represented in the results of SC algorithms. In this article, we propose a general method to address these limitations, grounding on a novel interpretation of SC as distributions over hard clusterings, which we call distributional measures. We provide an in-depth study of complexity- and metric-theoretic properties of the proposed approach, and we describe approximation techniques that can make the calculations tractable. Finally, we illustrate our approach through a simple but illustrative experiment.
paper
Evidential clustering; External validation; Soft clustering;
English
7th International Conference, BELIEF 2022 - October 26–28, 2022
2022
Le Hégarat-Mascle, S; Bloch, I; Aldea, E
7th International Conference, BELIEF 2022, Paris, France, October 26–28, 2022, Proceedings
9783031178009
2022
13506 LNAI
3
12
none
Campagner, A., Ciucci, D., Denœux, T. (2022). A Distributional Approach for Soft Clustering Comparison and Evaluation. In 7th International Conference, BELIEF 2022, Paris, France, October 26–28, 2022, Proceedings (pp.3-12). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-17801-6_1].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/394433
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