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| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidad Nacional Autónoma de México
2001
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| Online Access: | https://www.redalyc.org/articulo.oa?id=57101046 |
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Table of Contents:
- Prediction of stellar atmospheric parameters from spectra, spectral indices and spectral lines using machine learning Olac Fuentes Ravi K. Gulati Física, Astronomía y Matemáticas CAL METHODS: NUMERI STARS: ATMOSPHERES METHODS: DATA ANALYSIS In this paper we present an experimental study of the performance of a simplemachine learning algorithm applied to the prediction of the stellar atmosphericparameters Teff ; log g and [Fe=H] using as input three di erent sets of spectralfeatures. We compare the performance of the distance-weighted 3-nearest-neighboralgorithm using as input spectra, a set of spectral indices taken from the samewavelength region, and absorption lines obtained by removing from the spectrathe contribution of the continuum, which is computed by means of a linear timeconvex hull algorithm. Our experiments show that the predictions obtained usingspectral indices and spectral lines have very similar accuracy levels, and that bothare superior to those obtained using spectra. 2001 artículo científico 0185-1101 https://www.redalyc.org/articulo.oa?id=57101046 en http://www.redalyc.org/revista.oa?id=571 Revista Mexicana de Astronomía y Astrofísica application/pdf Universidad Nacional Autónoma de México Revista Mexicana de Astronomía y Astrofísica (México) Vol.10