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https://hdl.handle.net/2183/45993

Unsupervised clustering visualisation tool for Gaia DR3

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Alvarez_Marco_2025_Unsupervised_Clustering_Visualisation_Tool_for_Gaia_DR3.pdf (395.88 KB)

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URI: https://hdl.handle.net/2183/45993
DOI: 10.1017/S1743921323000716

Publication date

2025-08

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Bibliographic citation

Álvarez M, Dafonte C, Manteiga M, Garabato D, Santoveña R, Pallas L. Unsupervised clustering visualisation tool for Gaia DR3. In Machine Learning in Astronomy: Possibilities and Pitfalls. Proceedings of the International Astronomical Union. 2025; 19(S368):98-100. J. McIver, A. Mahabal & C. Fluke, eds. doi:10.1017/S1743921323000716

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Abstract

[Abstract]: The Gaia mission DR3 provides accurate data of around two billion stars in the Galaxy, including a classification based on astronomical classes of objects. In this work we present a web visualization tool to analyze one of the products published in the DR3, the Outlier Analysis Self-Organizing Map.

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Gaia DR3 Self-Organizing Maps Visualization Big Data

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https://doi.org/10.1017/S1743921323000716

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