Compute the normalized zero-one classification loss.
Predicted labels vector, as returned by a classifier
Ground truth (correct) 0-1 labels vector
logreg <- glm(formula = vs ~ hp + wt,
family = binomial(link = "logit"), data = mtcars)
pred <- ifelse(logreg$fitted.values < 0.5, 0, 1)
ZeroOneLoss(y_pred = pred, y_true = mtcars$vs)
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