sklearn.metrics.calinski_harabaz_score¶
- sklearn.metrics.calinski_harabaz_score(X, labels)[source]¶
Compute the Calinski and Harabaz score.
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.
Returns: score: float :
The resulting Calinski-Harabaz score.
References
[R198] T. Calinski and J. Harabasz, 1974. “A dendrite method for cluster analysis”. Communications in Statistics