IRAP > Séminaires > Calendrier des séminaires > Unsupervised classification: exploring the high dimension

Unsupervised classification: exploring the high dimension

Séminaire exceptionnel le 26 avr 2018 de 11h00 à 12h00

Intervenant : Didier Fraix-Burnet


Dealing with large amount of data  is  a new problematic task in astrophysics. One may distinguish the management of these data (astroinformatics) and their scientific use (astrostatistics) even if the border is rather fuzzy. Dimensionality reduction  in both the number of observations and the number of parameters (observables) is necessary for an easier physical understanding. This is the purpose of classification which has been traditionally eye-based and essentially still is but becomes not possible anymore. In this talk, I present a general overview of machine learning approaches for unsupervised classification, with applications to stars (chemical abundances) and galaxies (spectra).

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