# sklearn.metrics.calinski_harabaz_score¶

sklearn.metrics.calinski_harabaz_score(X, labels)[source]

Compute the Calinski and Harabaz score.

It is also known as the Variance Ratio Criterion.

The score is defined as ratio between the within-cluster dispersion and the between-cluster dispersion.

Read more in the User Guide.

Parameters: X : array-like, shape (n_samples, n_features) List of n_features-dimensional data points. Each row corresponds to a single data point. labels : array-like, shape (n_samples,) Predicted labels for each sample. score : float The resulting Calinski-Harabaz score.

References