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I used the dataset cars as an example

library("MLmetrics")
library("PRROC")
data(cars)
logreg <- glm(formula = vs ~ hp + wt,
              family = binomial(link = "logit"), data = mtcars)

The prauc returned by PRAUC is 0.861

PRAUC(y_pred = logreg$fitted.values, y_true = mtcars$vs)

However, the prauc returned by pr.curve is 0.932

pr.curve(scores.class0 = logreg$fitted.values, weights.class0 = mtcars$vs)

Is there anything wrong?

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The correct one is pr.curve. If you return the curve from it (via curve=T option) and plot at the values (see below), the area over the region contains approximately $53$ squares of area $(1/28)^2$, which has area approximately $0.067$, which means under it the area is nearly $0.93$.

pr curve from values

Sometimes, when the dataset is small, area calculation method matters, which is probably poorly implemented in MLmetrics.

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