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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
doc_scikit_learn
doc_scikit_learn
2017-01-15 04:26:17
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