Compute confusion matrix to evaluate the accuracy of a classification.
ConfusionMatrix(y_pred, y_true)
Arguments
- y_pred
Predicted labels vector, as returned by a classifier
- y_true
Ground truth (correct) 0-1 labels vector
Value
a table of Confusion Matrix
Examples
data(cars)
logreg <- glm(
formula = vs ~ hp + wt,
family = binomial(link = "logit"), data = mtcars
)
pred <- ifelse(logreg$fitted.values < 0.5, 0, 1)
ConfusionMatrix(y_pred = pred, y_true = mtcars$vs)
#> y_pred
#> y_true 0 1
#> 0 15 3
#> 1 1 13