AI engineering glossary · Classical ML algorithms
What is WCSS (inertia)?
Inertia (also called Within-cluster sum of squares, WCSS): In k-means, the sum of squared distances from every point to the centre of its assigned cluster. Lower means tighter clusters, but it always falls as k rises, so it is compared across k rather than minimised.
Inertia: an example
With k=3 inertia is 1,200 and with k=4 it is 900; the gain from adding a cluster shows whether it is worthwhile.
Related terms
More Classical ML algorithms terms
- Information gain
- Isolation forest
- K-means
- k-nearest neighbours
- KD-tree
- Kernel PCA
- Kernel trick
- Laplace smoothing
Where you learn it
Inertia is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.