An algorithm represents each example, applies a distance or density assumption, and assigns groups or hierarchical relationships. The resulting clusters reflect those modeling choices and need domain interpretation.
Clustering groups examples according to similarity without requiring predefined class labels.
An algorithm represents each example, applies a distance or density assumption, and assigns groups or hierarchical relationships. The resulting clusters reflect those modeling choices and need domain interpretation.