sklearn.metrics.davies_bouldin_score — scikit-learn 0.20.4 documentation (original) (raw)
sklearn.metrics. davies_bouldin_score(X, labels)[source]¶
Computes the Davies-Bouldin score.
The score is defined as the ratio of within-cluster distances to between-cluster distances.
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. |
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| Returns: | score: float The resulting Davies-Bouldin score. |
References
| [1] | Davies, David L.; Bouldin, Donald W. (1979).“A Cluster Separation Measure”. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-1 (2): 224-227 |
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