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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.

Note: Since homogeneity monotonically improves as the number of target clusters increases, it should not be used as a metric for hyper-parameter tuning.

Estimator Compatibility: Clusterer

Output Range: 0 to 1

Parameters#

This metric does not have any parameters.

Example#

use Rubix\ML\CrossValidation\Metrics\Homogeneity;

$metric = new Homogeneity();