mapie.metrics.length_scale

mapie.metrics.length_scale(s: numpy.ndarray[Any, numpy.dtype[numpy._typing._array_like._ScalarType_co]]) → float

Compute the mean square root of the sum of s * (1 - s). This is basically the standard deviation of the cumulative differences.

Parameters

sNDArray of shape (n_samples,)

An array of scores.

Returns

float

The length_scale array.

References

Arrieta-Ibarra I, Gujral P, Tannen J, Tygert M, Xu C. Metrics of calibration for probabilistic predictions. The Journal of Machine Learning Research. 2022 Jan 1;23(1):15886-940.

Examples

>>> import numpy as np
>>> from mapie.metrics import length_scale
>>> s = np.array([0, 0, 0.4, 0.3, 0.8])
>>> res = length_scale(s)
>>> print(np.round(res, 2))
0.16

Examples using mapie.metrics.length_scale

Testing for calibration in binary classification settings