AI engineering glossary · Classical ML algorithms
What is DBSCAN?
DBSCAN: Density-Based Spatial Clustering of Applications with Noise: it grows clusters from points that have at least min_samples neighbours within radius eps, and labels isolated points as noise. It finds odd-shaped clusters and needs no preset cluster count.
DBSCAN: an example
On delivery GPS data, eps=0.5 km and min_samples=10 group busy neighbourhoods and mark stray one-off points as noise.
Related terms
More Classical ML algorithms terms
- Decision boundary
- Decision stump
- Decision tree
- Dendrogram
- Dimensionality reduction
- Elastic net
- Elbow method
- Ensemble learning
Where you learn it
DBSCAN is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.