A Distributional Approach for Soft Clustering Comparison and Evaluation

@article{Campagner2022ADA,
  title={A Distributional Approach for Soft Clustering Comparison and Evaluation},
  author={Andrea Campagner and Davide Ciucci and Thierry Denoeux},
  journal={ArXiv},
  year={2022},
  volume={abs/2206.09827}
}
. 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… 

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