Please use this identifier to cite or link to this item:
Title: Classifying astronomical sources with machine learning
Author: Sabatés de la Huerta, Jordi
Director/Tutor: Solanes, José M. (José María)
Salamó Llorente, Maria
Keywords: Objecte astronòmic
Aprenentatge automàtic
Treballs de fi de grau
Astronomical object
Machine learning
Bachelor's theses
Issue Date: Feb-2022
Abstract: 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
Note: Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2022, Tutors: José Maria Solanes Majúa, Maria Salamó Llorente
Appears in Collections:Treballs Finals de Grau (TFG) - Física

Files in This Item:
File Description SizeFormat 
SABATÉS DE LA HUERTA JORDI_5181450_assignsubmission_file_TFG_Sabatés_Jordi_final.pdf300.67 kBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons