SuperLearnerControl parameters for the cross validation steps in SuperLearner
SuperLearner.CV.control(V = 10L, stratifyCV = FALSE, shuffle = TRUE,
validRows = NULL)Integer. Number of splits for the V-fold cross-validation step. The default is 10. In most cases, between 10 and 20 splits works well.
Logical. Should the data splits be stratified by a binary response? Attempts to maintain the same ratio in each training and validation sample.
Logical. Should the rows of X be shuffled before creating the splits.
A List. Use this to pass pre-specified rows for the sample splits. The length of the list should be V and each entry in the list should contain a vector with the row numbers of the corresponding validation sample.
A list containing the control parameters