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.
Estimator Compatibility: Clusterer
Output Range: 0 to 1
|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);
- A. Rosenberg et al. (2007). V-Measure: A conditional entropy-based external cluster evaluation measure.