optimize_weights {socceR} | R Documentation |
Computes the optimal weights to obtain the minimal loss function from a list of prediction matrices.
optimize_weights(predictionlist, outcome, FUN = trps)
predictionlist |
A list of R x T prediction matrices where each column sum to 1 and each row sums to |
outcome |
An integer vector listing the |
FUN |
The function used for optimizing the predictions. The default is top use rps for the rank probability score. Another option is logloss for log loss. |
Returns a numeric vector containing an optimal vector of weights that sum to 1 and that minimizes the loss function.
Claus Ekstrom ekstrom@sund.ku.dk
m1 <- matrix(c(1, 0, 0, 0, 0, 1, 0, 0, 0, 0, .5, .5, 0, 0, .5, .5), 4) m1 # Prediction where certain on the top ranks m2 <- matrix(c(.5, .5, 0, 0, .5, .5, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1), 4) m2 # Prediction where the groups are okay m3 <- matrix(c(.5, .5, 0, 0, .5, .5, 0, 0, 0, 0, .5, .5, 0, 0, .5, .5), 4) m3 # Prediction where no clue about anything m4 <- matrix(rep(1/4, 16), 4) optimize_weights(list(m1, m2, m3, m4), 1:4)