Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxy Data

@article{Lawlor2016MappingTS,
  title={Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxy Data},
  author={David Lawlor and Tamas Budavari and Michael W. Mahoney},
  journal={ArXiv},
  year={2016},
  volume={abs/1609.03932}
}
  • David Lawlor, Tamas Budavari, Michael W. Mahoney
  • Published 2016
  • Physics, Computer Science, Mathematics
  • ArXiv
  • We present a novel approach to studying the diversity of galaxies. It is based on a novel spectral graph technique, that of locally-biased semi-supervised eigenvectors. Our method introduces new coordinates that summarize an entire spectrum, similar to but going well beyond the widely used Principal Component Analysis (PCA). Unlike PCA, however, this technique does not assume that the Euclidean distance between galaxy spectra is a good global measure of similarity. Instead, we relax that… CONTINUE READING

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