Clustering data by reordering them

Axel Descamps; Sélène Forget; Aliénor Lahlou; Claire Lavergne; Camille Berthelot; Guillaume Stirnemann; Rodolphe Vuilleumier; Nicolas Chéron

arXiv · 2503.19067

Clustering data by reordering them

Axel Descamps·Sélène Forget·Aliénor Lahlou·Claire Lavergne·Camille Berthelot·Guillaume Stirnemann·Rodolphe Vuilleumier·Nicolas Chéron

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Abstract

Grouping elements into families to analyse them separately is a standard analysis procedure in many areas of sciences. We propose herein a new algorithm based on the simple idea that members from a family look like each other, and don't resemble elements foreign to the family. After reordering the data according to the distance between elements, the analysis is automatically performed with easily-understandable parameters. Noise is explicitly taken into account to deal with the variety of problems of a data-driven world. We applied the algorithm to sort biomolecules conformations, gene sequences, cells, images, and experimental conditions.

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Axel Descamps, Sélène Forget, Aliénor Lahlou, Claire Lavergne, Camille Berthelot, Guillaume Stirnemann, Rodolphe Vuilleumier, Nicolas Chéron. 2025-03-24. Clustering data by reordering them. https://arxiv.org/abs/2503.19067

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