By Islam BarakaDefinitions
In plain terms
Core points seed density-connected clusters.
Technical
Point i is core when |N_delta(i)| >= min_touches, with the point itself included in the count.
Scope
Core status depends on epsilon and data history; it is not a confidence score.
Formula
core when the inclusive neighborhood contains at least min_touches points|N_\delta(i)|\ge m| Symbol | Meaning | Unit |
|---|---|---|
m | minimum touches | count |
Output unit: boolean state
Examples
- A reviewer computes DBSCAN Core Point on a small deterministic fixture and checks timing, units, and boundary behavior before publication.
Common misconceptions
- Core status depends on epsilon and data history; it is not a confidence score.
Concept relationships
Related
Required by
Where this concept is used
Tutorials planned
These catalogued topics use this concept, but their complete build has not shipped yet.
- D08-F01-A03 Important
Evidence and governance
- sklearn.cluster.DBSCAN scikit-learn · first party technical publication
Supports: preferred label, short definition, technical definition, formula
Limits: The package implements deterministic one-dimensional DBSCAN directly for Python/TypeScript parity.
- Pine Script pivot techniques TradingView · official platform documentation
Supports: preferred label, short definition, technical definition, formula
Limits: The package freezes its own equality, separation, and OHLC policies rather than claiming one universal pivot definition.
- numpy.log NumPy · first party technical publication
Supports: preferred label, short definition, technical definition, formula
Limits: A log transform requires positive finite prices and does not by itself define a financial level.
- Reviewed by
- fintech-builder-batch-011
- Last reviewed
- 2026-08-09
- Next review
- 2027-08-09
- Record status
- evidence reviewed
This record is evidence-reviewed and readable, but not yet promoted to published — it is served noindex,follow and excluded from the sitemap.