sklearn.metrics.calinski_harabaz_score()
sklearn.metrics.calinski_harabaz_score
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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
© 2007–2016 The scikit-learn developers
Licensed under the 3-clause BSD License.
http://scikit-learn.org/stable/modules/generated/sklearn.metrics.calinski_harabaz_score.html