| brier_score {scoringutils} | R Documentation |
Brier Score
Description
Computes the Brier Score for probabilistic forecasts of binary outcomes.
Usage
brier_score(true_values, predictions)
Arguments
true_values |
A vector with the true observed values of size n with all values equal to either 0 or 1 |
predictions |
A vector with a predicted probability that true_value = 1. |
Details
The Brier score is a proper score rule that assesses the accuracy of probabilistic binary predictions. The outcomes can be either 0 or 1, the predictions must be a probability that the true outcome will be 1.
The Brier Score is then computed as the mean squared error between the probabilistic prediction and the true outcome.
\textrm{Brier\_Score} = \frac{1}{N} \sum_{t = 1}^{n} (\textrm{prediction}_t -
\textrm{outcome}_t)^2
Value
A numeric value with the Brier Score, i.e. the mean squared error of the given probability forecasts
Examples
true_values <- sample(c(0, 1), size = 30, replace = TRUE)
predictions <- runif(n = 30, min = 0, max = 1)
brier_score(true_values, predictions)