An implementation of the FuzzyDBSCAN algorithm [1].
FuzzyDBSCAN is an agglomerative fuzzy clustering algorithm that groups set of points in such a way that one point can belong to more than one group. A points degree of membership is expressed as a category (core, border, noise) and a soft label (between 0.0 and 1.0).
See documentation for an example.
[1] Dino Ienco, and Gloria Bordogna. "Fuzzy extensions of the DBScan clustering algorithm." Soft Computing (2016).
This project is maintained under the Semantic Versioning guidelines.
Licensed under the Apache 2.0 License. Copyright © 2018 Christoph Schulz.