AAI Handbook
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algorithm

K-Means

beginnerunsupervised
parametricclusteringtabular

K-Means divides points into $k$ groups by repeatedly assigning each point to its nearest center and moving centers to the assigned averages.

Mechanisms

centroid optimizationdistance

Properties

interpretable

Constraints

requires scalingsensitive to high dimensionsensitive to outliers

Practical profile

Explainability
medium
Training cost
low
Inference cost
low
Data appetite
medium