brier_score | R Documentation |
Computes the Brier Score for probabilistic forecasts of binary outcomes.
brier_score(true_values, predictions)
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. |
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.
Brier_Score = 1/N sum_{t = 1}^{n} (prediction_t - outcome_t)²
A numeric value with the Brier Score, i.e. the mean squared error of the given probability forecasts
true_values <- sample(c(0, 1), size = 30, replace = TRUE) predictions <- runif(n = 30, min = 0, max = 1) brier_score(true_values, predictions)
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