AI Concepts
DBSCAN can identify noise without choosing a cluster count first
DBSCAN builds clusters from local density and can leave points unassigned. Understand eps, min_samples and the limits before interpreting the labels.
AI · VISION · EVERYDAY SYSTEMS
clustering
AI Concepts
Feature scaling changes what distance means to k-means clustering
K-means uses distances between feature values. A worked example shows how changing measurement scales can change the clusters a model finds.