sklearn.metrics.calinski_harabasz_score

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

Compute the Calinski and Harabasz 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
Xarray-like of shape (n_samples, n_features)

A list of n_features-dimensional data points. Each row corresponds to a single data point.

labelsarray-like of shape (n_samples,)

Predicted labels for each sample.

Returns
scorefloat

The resulting Calinski-Harabasz score.

References

1

T. Calinski and J. Harabasz, 1974. “A dendrite method for cluster analysis”. Communications in Statistics

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https://scikit-learn.org/0.24/modules/generated/sklearn.metrics.calinski_harabasz_score.html