HDBSCAN — how does it improve on DBSCAN?
hardAnswer
- Runs DBSCAN over all density levels and extracts the most stable clusters — avoids picking a single eps.
- Handles clusters of varying density (DBSCAN's biggest failure mode).
- Output: cluster labels + outlier scores + soft memberships.
- Standard practice for real-world clustering when densities are heterogeneous (customer segments, sensor data).
- Slightly slower but no eps tuning needed.
Check yourself — multiple choice
- Same as DBSCAN
- Runs DBSCAN over all density thresholds and picks stable clusters → no eps to tune, handles varying densities
- Random
- Only tiny data
HDBSCAN: multi-density DBSCAN; no eps; handles varying densities.
#clustering#density
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