[source] # V Measure V Measure is an entropy-based clustering metric that balances [Homogeneity](homogeneity.md) and [Completeness](completeness.md). 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 ## Parameters | # | Name | Default | Type | Description | |---|---|---|---|---| | 1 | beta | 1.0 | float | The ratio of weight given to homogeneity over completeness. | ## Example ```php use Rubix\ML\CrossValidation\Metrics\VMeasure; $metric = new VMeasure(1.0); ``` ## References [^1]: A. Rosenberg et al. (2007). V-Measure: A conditional entropy-based external cluster evaluation measure.