Causal Interpretation of DBSCAN Algorithm: A Dynamic Modeling for Epsilon Estimation
K. Garcia-Sanchez, J.-L. Perez-Ramos, S. Ramirez-Rosales, A.-M. Herrera-Navarro, H. Jiménez-Hernández, D. Canton-Enriquez · 2026
Read Causal Interpretation of DBSCAN Algorithm: A Dynamic Modeling for Epsilon Estimation by K. Garcia-Sanchez, J.-L. Perez-Ramos, S. Ramirez-Rosales, A.-M. Herrera-Navarro, H. Jiménez-Hernández, D. Canton-Enriquez (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13114442.txt.
Description
DBSCAN is widely used to identify structured regions in unlabeled data, but its performance depends critically on the selection of the neighborhood parameter ε. Traditional heuristics for estimating ε often become unreliable in high-dimensional or varying-density settings because they rely heavily on local geometric criteria and may fail under smooth transitions or topological ambiguity.
Catalog record
| CREATOR | K. Garcia-Sanchez, J.-L. Perez-Ramos, S. Ramirez-Rosales, A.-M. Herrera-Navarro, H. Jiménez-Hernández, D. Canton-Enriquez |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 75 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |