The widely applied density peak clustering (DPC) algorithm makes an intuitive cluster formation assumption that centers are often surrounded by data points with lower local and far away from other higher density. However, this suffers one limitation it is problematic when identifying clusters because they might be easily merged into As a result, DPC may not able to identify variational To addre...

Aims. We present pyUPMASK, an unsupervised clustering method for stellar clusters that builds upon the original UPMASK package. The general approach of this makes it plausible to be applied analyses deal with binary classes any kind as long fundamental hypotheses are met. code is written entirely in Python and made available through a public repository. Methods. core algorithm follows developed...