[source] # Homogeneity A ground-truth clustering metric that measures the ratio of samples in a cluster that are also members of the same class. A cluster is said to be *homogeneous* when the entire cluster is comprised of a single class of samples. $$ {\displaystyle Homogeneity = 1-\frac{H(C, K)}{H(C)}} $$ !!! note Since this metric monotonically improves as the number of target clusters increases, it should not be used as a metric to guide hyper-parameter tuning. **Estimator Compatibility:** Clusterer **Score Range:** 0 to 1 ## Parameters This metric does not have any parameters. ## Example ```php use Rubix\ML\CrossValidation\Metrics\Homogeneity; $metric = new Homogeneity(); ```