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[ascl:2003.003] acorns: Agglomerative Clustering for ORganising Nested Structures

acorns generates a hierarchical system of clusters within discrete data by using an n-dimensional unsupervised machine-learning algorithm that clusters spectroscopic position-position-velocity data. The algorithm is based on a technique known as hierarchical agglomerative clustering. Although acorns was designed with the analysis of discrete spectroscopic position-position-velocity (PPV) data in mind (rather than uniformly spaced data cubes), clustering can be performed in n-dimensions and the algorithm can be readily applied to other data sets in addition to PPV measurements.

Code site:
https://github.com/jdhenshaw/acorns
Described in:
https://ui.adsabs.harvard.edu/abs/2019MNRAS.485.2457H
Bibcode:
2020ascl.soft03003H

Views: 777

ascl:2003.003
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