Skip to contents

Fit a BART (Bayesian Additive Regression Tree) meta learner. It takes predictions of other models such as kriging, GLM, machine learning models as input and fits a BART Model

Source: R/meta_learner.R
meta_learner_fit.Rd

Fit a BART (Bayesian Additive Regression Tree) meta learner. It takes predictions of other models such as kriging, GLM, machine learning models as input and fits a BART Model

Usage

meta_learner_fit(base_predictor_list, kfolds, y, ...)

Arguments

base_predictor_list

  • P x 1 list where P = p is a base predictor vector (numeric). Each predictor vector should be the same length and named.

kfolds

integer, index of k-folds for cross-validation. This should be produced with regards to spatial and/or temporal considerations

y

dependent variable

...

Passed arguments to wbart

Value

meta_fit_obj object of meta learner

Examples

NULL
#> NULL