Base-Learner Description Arguments
BaselearnerPolynomial Fit polynomial base-learner. Note that this base-learner takes just the power of the selected feature. For instance, there is no linear part when using degree = 2.
degree
Polynomial degree of feature (default: 1)
intercept
Specification if an intercept column should be added (default: TRUE)
BaselearnerPSpline Fit (penalized) spline regression base-learner.
degree
Polynomial degree of bases (default: 3)
n_knots
Number of inner knots (default: 20)
penalty
Penalty term to control the smoothness of the curve (default: 2)
differences
Number of penalized differences (default: 2)
BaselearnerCustom Define a custom base-learner by using custom R functions.
instantiate_fun
Feature transformation, e.g., create spline bases.
train_fun
Function to train on the data generated by instantiate_fun
predict_fun
Function to predict on the object returned by train_fun
param_fun
Function to extract parameters as matrix from the object returned by train_fun
BaselearnerCustomCpp Define a custom base-learner by using custom C++ functions.
instantiate_ptr
External pointer containing the reference to the C++ feature transformation
train_ptr
Function to train on the data generated by instantiate_ptr which always returns the parameter as matrix
predict_ptr
Function to predict by using the parameter returned by train_ptr