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A fast version of the k-means classification algorithm for astronomical applications

Ordovás-Pascual, I. ; Sánchez Almeida, J.

Astronomy and astrophysics (Berlin), 2014-05, Vol.565, p.np-np [Periódico revisado por pares]

EDP Sciences

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  • Título:
    A fast version of the k-means classification algorithm for astronomical applications
  • Autor: Ordovás-Pascual, I. ; Sánchez Almeida, J.
  • Assuntos: Algorithms ; astronomical databases: miscellaneous ; Astronomy ; Astrophysics ; Classification ; Clustering ; Equivalence ; methods: data analysis ; methods: statistical ; Spectra
  • É parte de: Astronomy and astrophysics (Berlin), 2014-05, Vol.565, p.np-np
  • Notas: ark:/67375/80W-S16XSG0D-S
    publisher-ID:aa23806-14
    bibcode:2014A%26A...565A..53O
    istex:DDAE8CB7EE5045AC9FC2BA7DAF343EA3BD795548
    e-mail: ordovas@ifca.unican.es
    dkey:10.1051/0004-6361/201423806
    ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
  • Descrição: Context. K-means is a clustering algorithm that has been used to classify large datasets in astronomical databases. It is an unsupervised method, able to cope very different types of problems. Aims. We check whether a variant of the algorithm called single pass k-means can be used as a fast alternative to the traditional k-means. Methods. The execution time of the two algorithms are compared when classifying subsets drawn from the SDSS-DR7 catalog of galaxy spectra. Results. Single-pass k-means turn out to be between 20% and 40% faster than k-means and provide statistically equivalent classifications. This conclusion can be scaled up to other larger databases because the execution time of both algorithms increases linearly with the number of objects. Conclusions. Single-pass k-means can be safely used as a fast alternative to k-means.
  • Editor: EDP Sciences
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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