AI engineering glossary · Evaluation metrics
What is v-measure?
V-measure (also called homogeneity and completeness): The harmonic mean of two clustering scores against known classes: homogeneity (each cluster holds members of only one class) and completeness (all members of a class fall in the same cluster). It ranges from 0 to 1 and needs ground-truth labels.
V-measure: an example
Splitting one true class across many pure clusters has high homogeneity but low completeness, which lowers the V-measure.
Related terms
More Evaluation metrics terms
- Weighted averaging
- Weighted kappa
- Word error rate
- Youden's J statistic
- Accuracy
- Accuracy paradox
- Adjusted Rand index
- AUC-ROC
Where you learn it
V-measure is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.