pycrostates.metrics.davies_bouldin_score

pycrostates.metrics.davies_bouldin_score(cluster)

Compute the Davies-Bouldin score.

This function computes the Davies-Bouldin score[1] with sklearn.metrics.davies_bouldin_score() from a fitted Clustering instance.

Parameters:

clusterCluster

Fitted clustering algorithm from which to compute score. For more details about current clustering implementations, check the Clustering section of the documentation.

Returns:

scorefloat

The resulting Davies-Bouldin score.

Notes

For more details regarding the implementation, please refer to sklearn.metrics.davies_bouldin_score(). This function was modified in order to use the absolute spatial correlation for distance computations instead of the euclidean distance.

References

[1]

David L. Davies and Donald W. Bouldin. A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-1(2):224–227, 1979. doi:10.1109/TPAMI.1979.4766909.

Examples using pycrostates.metrics.davies_bouldin_score

Evaluating clustering fits

Evaluating clustering fits