Multiclass Brier score
Defined as: (1/n) sum_i sum_j (y_ij - p_ij)^2, where y_ij = 1 if observation i has class j (else 0), and p_ij is the predicted probability of observation i for class j. From http://docs.lib.noaa.gov/rescue/mwr/078/mwr-078-01-0001.pdf.
multiclass.Brier(probabilities, truth)
probabilities |
[numeric] matrix of predicted probabilities with columnnames of the classes |
truth |
vector of true values |
n = 20 set.seed(122) truth = as.factor(sample(c(1,2,3), n, replace = TRUE)) probabilities = matrix(runif(60), 20, 3) probabilities = probabilities/rowSums(probabilities) colnames(probabilities) = c(1,2,3) multiclass.Brier(probabilities, truth)
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