Returns the number of classes in each prediction set.
See also
Other diagnostics:
conformal_compare(),
conformal_pvalue(),
coverage(),
coverage_by_bin(),
coverage_by_group(),
interval_width()
Examples
set.seed(42)
n <- 300
x <- matrix(rnorm(n * 4), ncol = 4)
y <- factor(ifelse(x[,1] > 0, "A", "B"))
x_new <- matrix(rnorm(50 * 4), ncol = 4)
clf <- make_model(
train_fun = function(x, y) glm(y ~ ., data = data.frame(y = y, x),
family = "binomial"),
predict_fun = function(object, x_new) {
df <- as.data.frame(x_new)
names(df) <- paste0("X", seq_len(ncol(x_new)))
p <- predict(object, newdata = df, type = "response")
cbind(A = 1 - p, B = p)
},
type = "classification"
)
result <- conformal_lac(x, y, model = clf, x_new = x_new)
#> Warning: glm.fit: algorithm did not converge
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
sizes <- set_size(result)
table(sizes)
#> sizes
#> 1
#> 50