DBSCAN - Density-Based Spatial Clustering of Applications with Noise
Description: DBSCAN groups together points that are close to each other based on distance and density, and identifies outliers as points that lie alone in low-density regions.
Key Points:
- Can find arbitrarily shaped clusters.
- Robust to noise and outliers.
- Requires tuning of the density parameters.
Applications: Geographic data analysis, fraud detection, biology.