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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/189820
Classifying astronomical sources with machine learning
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More than 4 million astronomical sources extracted from the Sloan Digital Sky Survey catalog have been used to train a set of machine learning models, selected with a benchmarking program, in order to identify the best basic classifier of astronomical sources for future observations.
We have also applied different filters to our dataset that modify its selection function, measuring the accuracy of the selected model to evaluate under which observational constraints this model performs better
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Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2022, Tutors: José Maria Solanes Majúa, Maria Salamó Llorente
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SABATÉS DE LA HUERTA, Jordi. Classifying astronomical sources with machine learning. [consulted: 6 of October of 2026]. Available at: https://hdl.handle.net/2445/189820