mapie.metrics.calibration.spiegelhalter_p_value
- mapie.metrics.calibration.spiegelhalter_p_value(y_true: ndarray[tuple[Any, ...], dtype[_ScalarT]], y_score: ndarray[tuple[Any, ...], dtype[_ScalarT]]) float[source]
Compute Spiegelhalter statistic p-value. Deduced from the corresponding statistic and CDF, which is no more than the normal distribution. It represents the probability of the observed statistic under the null hypothesis of perfect calibration.
- Parameters:
- y_trueNDArray of shape (n_samples,)
An array of ground truth.
- y_scoreNDArray of shape (n_samples,)
An array of scores.
- Returns:
- float
The Spiegelhalter statistic p_value.
References
Spiegelhalter DJ. Probabilistic prediction in patient management and clinical trials. Statistics in medicine. 1986 Sep;5(5):421-33.
Examples
>>> import numpy as np >>> from mapie.metrics.calibration import spiegelhalter_p_value >>> y_true = np.array([1, 0, 1, 0, 1, 0]) >>> y_score = np.array([0.8, 0.3, 0.5, 0.5, 0.7, 0.1]) >>> sp_p_value = spiegelhalter_p_value(y_true, y_score) >>> print(np.round(sp_p_value, 4)) 0.8486
