Metric DBSCAN
- Sandia National Lab. (SNL-CA), Livermore, CA (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
SAND2025-11725O Metric DBSCAN is an implementation of the popular DBSCAN clustering algorithm that works in general metric spaces. DBSCAN is a clustering algorithm, a fundamental building block in machine learning. It takes a set of objects and, given some notion of distance, identifies coherent groups of objects. With Metric DBSCAN, users can provide an arbitrary function to compute distance. Nearly all existing implementations of DBSCAN restrict distance to one of a few formulations. Metric DBScan accomplishes this cleanly and efficiently. The Python source code is on Github. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
- Site Accession Number:
- SCR #3011.0
- Software Type:
- Scientific
- License(s):
- BSD 3-clause "New" or "Revised" License
- Programming Language(s):
- Python
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOEPrimary Award/Contract Number:NA0003525
- DOE Contract Number:
- NA0003525
- Code ID:
- 167245
- OSTI ID:
- code-167245
- Country of Origin:
- United States
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