Variable stars' light curve detection and classification using supervised machine learning
We present two applications of supervised machine learning aimed at addressing the light curve classification problem in stellar variability. Our main goal is to streamline the analysis of light curves obtained from large-scale photometric and multi-epoch astronomic surveys. In the first application...
- Autores:
-
Elizabethson, Astaroth
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2024
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/73980
- Acceso en línea:
- https://hdl.handle.net/1992/73980
- Palabra clave:
- Astronomy
Machine Learning
KNN
CART
RF
SVM
RR Lyrae stars
Cepheid stars
T Tauri stars
VVV Survey
Vista Variable Stars in the Via Lactea
TESS
Transiting Exoplanet Survey Satellite
Física
- Rights
- openAccess
- License
- https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf