set.seed(1231)
x <- rnorm(100)
y <- as.integer((.2*x + rnorm(100)) > 0)
p <- stats::predict(stats::glm(y~0+x, family=binomial("probit")), type="response")
ans0 <- auc(p, y, 100)
ans1 <- AUC::auc(AUC::roc(p, as.factor(y)))
# Default way
expect_equal(ans0$auc, ans1, tol=0.01)
# Now using lists
pscore0 <- prediction_score(
as.list(x),
as.list(y)
)
# Now using vectors
pscore1 <- prediction_score(
x,
y
)
pscore2 <- # Now using matrix
prediction_score(
cbind(x),
cbind(y)
)
pscore3 <- # Now using a data frame
prediction_score(
data.frame(x),
data.frame(y)
)
expect_equal(
pscore0$auc,
pscore1$auc
)
expect_equal(
pscore0$auc,
pscore2$auc
)
expect_equal(
pscore0$auc,
pscore3$auc
)
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