Classifying astronomical sources with machine learning

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

Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2022, Tutors: José Maria Solanes Majúa, Maria Salamó Llorente

Country

Spain

Related Organizations

University of Barcelona
Spain

Keywords

Astronomical object, Objecte astronòmic, Bachelor's thesis, Bachelor's theses, Aprenentatge automàtic, Machine learning, Treballs de fi de grau

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