pyUPMASK: Unsupervised clustering method for stellar clusters
Abstract: pyUPMASK is an unsupervised clustering method for stellar clusters that builds upon the original UPMASK (ascl:1504.001) package. Its general approach makes it applicable to analyses that deal with binary classes of any kind, as long as the fundamental hypotheses are met. The core of the algorithm follows the method developed in UPMASK but introducing several key enhancements that make it not only more general, they also improve its performance.
Credit: Pera, M. S.; Perren, G. I.; Moitinho, A.; Navone, H. D.; Vazquez, R. A.
Site: https://github.com/msolpera/pyUPMASK
https://ui.adsabs.harvard.edu/abs/2021arXiv210101660P
Bibcode: 2021ascl.soft01016P
Preferred citation method: https://ui.adsabs.harvard.edu/abs/2021arXiv210101660P
ID: ascl:2101.016