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V Measure#

V Measure is an entropy-based clustering metric that balances Homogeneity and Completeness. It has the additional property of being symmetric in that the predictions and ground-truth can be swapped without changing the score.

\[ {\displaystyle V_{\beta} = \frac{(1+\beta)hc}{\beta h + c}} \]

Estimator Compatibility: Clusterer

Score Range: 0 to 1


# Name Default Type Description
1 beta 1.0 float The ratio of weight given to homogeneity over completeness.


use Rubix\ML\CrossValidation\Metrics\VMeasure;

$metric = new VMeasure(1.0);


  1. A. Rosenberg et al. (2007). V-Measure: A conditional entropy-based external cluster evaluation measure.