R: Method to estimate the coefficients for the super learner
write.method.template
R Documentation
Method to estimate the coefficients for the super learner
Description
These functions contain the information on the loss function and the model to combine algorithms
Usage
write.method.template(file = "", ...)
## a few built in options:
method.NNLS()
method.NNLS2()
method.NNloglik()
method.CC_LS()
method.CC_nloglik()
method.AUC(optim_method = "Nelder-Mead")
Arguments
file
A connection, or a character string naming a file to print to. Passed to cat.
optim_method
Passed to the optim call method. See optim for details.
...
Additional arguments passed to cat.
Details
A SuperLearner method must be a list (or a function to create a list) with exactly 3 elements. The 3 elements must be named require, computeCoef and computePred.
Value
A list containing 3 elements:
require
A character vector listing any required packages. Use NULL if no additional packages are required
computeCoef
A function. The arguments are: Z, Y, libraryNames, obsWeights, control, verbose. The value is a list with two items: cvRisk and coef. This function computes the coefficients of the super learner. As the super learner minimizes the cross-validated risk, the loss function information is contained in this function as well as the model to combine the algorithms in SL.library.
computePred
A function. The arguments are: predY, coef, control. The value is a numeric vector with the super learner predicted values.
providing 
.