mlr3 - confidence interval for predictions

Question

After tuning a learner and using it, we can use it to make predictions through the command line

predict(Learner, newdata, predict_type="response")

But, how do we compute confidence intervals for predictions?

---

task <- TaskRegr$new("data", data, "y")
learner <- lrn("regr.xgboost")
preprocess <- po("scale", param_vals = list(center = TRUE, scale = TRUE))
pp <- preprocess %>>% learner
gg<- GraphLearner$new(pp)
gg$train(task)
predict(gg, newdata = pred, predict_type="reponse")

Answer 1

Not all learners support prediction errors, xgboost being one of them. You'll have to use a different learner to get error estimates.