AI engineering glossary · Classical ML algorithms
What is linkage criterion?
Linkage criterion (also called Ward's method): The rule for measuring distance between two clusters when merging: single (closest pair), complete (farthest pair), average (mean of all pairs) or Ward (smallest increase in within-cluster variance). It strongly shapes the clusters found.
Linkage criterion: an example
Single linkage can chain far-apart points through a thin bridge, while Ward tends to give compact, similar-sized clusters.
Related terms
More Classical ML algorithms terms
- Local outlier factor
- Log-odds
- Logistic regression
- Manhattan distance
- Matrix factorisation
- Maximum margin classifier
- Mini-batch k-means
- Multicollinearity
Where you learn it
Linkage criterion is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.