GMM covariance types — which do you pick?
hardAnswer
- Full: each cluster has its own general — most flexible, most parameters .
- Tied: all clusters share one Σ.
- Diagonal: axis-aligned ellipsoids (p params per cluster).
- Spherical: I (1 param) — closest to k-means.
- Rule: use full for small p, tied or diagonal for high p to avoid overfitting.
- Cross-validate log-likelihood or BIC to choose.
Check yourself — multiple choice
- Only full
- Full (shared) / diagonal (axis-aligned) / spherical (~k-means). Full for small p, diagonal/tied for high p; select by BIC
- Random
- Same as k-means
GMM covariance: full / tied / diagonal / spherical; trade flexibility vs params.
#clustering#density
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