What is the difference between DBSCAN and k-means clustering algorithms?

Question

Data Science with Python — Hard

What is the difference between DBSCAN and k-means clustering algorithms?

Accepted Answer

DBSCAN discovers clusters of arbitrary shape based on density, automatically identifying outliers as noise, and does not require specifying the number of clusters. In contrast, k-means requires specifying k clusters, assumes spherical clusters, and is sensitive to outliers.