scoringrules.brier_score

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scoringrules.brier_score#

scoringrules.brier_score(obs: ArrayLike, fct: ArrayLike, *, backend: Backend = None) → Array#

Brier Score

The Brier Score is defined as

\[\text{BS}(F, y) = (F - y)^2,\]

where \(F \in [0, 1]\) is the predicted probability of an event and \(y \in \{0, 1\}\) is the outcome [1].

Parameters:
obsarray_like

Observed outcomes, either 0 or 1.

fctarray_like

Forecast probabilities, between 0 and 1.

backendstr

The name of the backend used for computations. Default is ‘numpy’.

Returns:
scorearray_like

The computed Brier Score.

References

[1]

Brier, G. W. (1950). Verification of forecasts expressed in terms of probability. Monthly Weather Review, 78, 1-3.

Examples

>>> import scoringrules as sr
>>> sr.brier_score(1, 0.2)
0.64000
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