dataeval.core.ber_mst¶

dataeval.core.ber_mst(data, labels)¶

An estimator for Multi-class Bayes error rate using FR with a minimum spanning tree (MST) test statistic basis.

Parameters:¶

data : NDArray[np.float64]¶

Array of image embeddings

labels : NDArray[np.intp]¶

Array of labels for each image

Returns:¶

The upper and lower bounds, respectively, of the Bayes Error Rate

Return type:¶

tuple[float, float]

References

[1] Learning to Bound the Multi-class Bayes Error (Th. 3 and Th. 4)

Examples

>>> import sklearn.datasets as dsets
>>> from dataeval.core._ber import ber_mst

>>> images, labels = dsets.make_blobs(n_samples=50, centers=2, n_features=2, random_state=0)
>>> ber_mst(images, labels)
(0.04, 0.020416847668728033)