Bootstrap Ensemble Learner with SE Prediction

Wraps any regression learner and trains a bootstrap ensemble. Predictions return mean and SE across bootstrap samples.

Creates a new instance of this R6 class.

Arguments

learner

(mlr3::LearnerRegr)
Base learner to bootstrap.

Details

This learner creates a bootstrap ensemble by:

1. Taking n_bootstrap bootstrap samples (sampling with replacement)

2. Training the base learner on each sample and storing the trained state

3. During prediction, restoring each state and computing predictions

4. Computing mean and SD of predictions across the ensemble

The standard deviation across bootstrap predictions serves as the standard error estimate.

The wrapped base learner ($wrapped) remains untrained after training the wrapper. Use $base_learner() to get a trained clone of the base learner.

Fields

wrapped

(LearnerRegr)
Read-only access to the wrapped base learner.

param_set

(paradox::ParamSet)
The combined parameter set.

Fields

• $wrapped :: mlr3::LearnerRegr
  Read-only access to the wrapped base learner.

Examples

if (FALSE) { # \dontrun{
# Wrap ranger with bootstrap SE
learner <- lrn("regr.bootstrap_se", learner = lrn("regr.ranger"))
learner$param_set$set_values(n_bootstrap = 10)

# Train on a task
task <- tsk("mtcars")
learner$train(task)

# Predict with SE
pred <- learner$predict(task)
pred$se  # Standard errors
} # }