Base learner functionality

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